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{"parentUuid":"e09f5714-c3b2-4ff7-a328-2ac24646410e","isSidechain":false,"promptId":"5cf2b9aa-1e4c-4000-a379-b7377df30c86","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01TEUXAMScDLBNaWBCDAkonq","type":"tool_result","content":"1\t# CreatorFlow Punch List\n2\t\n3\tThis list tracks the work needed to prove the first local AI workflow before broadening into a platform.\n4\t\n5\t## Project Standards\n6\t\n7\t- [x] Keep a repo-level todo/punch list as a standard project operating artifact.\n8\t- [x] Add project-level agent instructions requiring the punch list to stay current.\n9\t\n10\t## Discovery\n11\t\n12\t- [x] Prepare a first-agent discovery packet and acceptance criteria worksheet.\n13\t- [ ] Collect 5-8 raw walkthrough videos from the first real estate agent.\n14\t- [ ] Collect examples of posts/videos the agent considers publishable.\n15\t- [ ] Confirm target turnaround time, revision expectations, and pricing signal.\n16\t- [ ] Capture real estate compliance preferences and required brokerage/disclaimer language.\n17\t- [ ] Define first workflow acceptance criteria from the discovery conversation.\n18\t\n19\t## Product Guardrails\n20\t\n21\t- [x] Keep the first version concierge-first: client sends raw input, operator reviews, client receives finished output.\n22\t- [x] Require human approval before final rendered output is considered publishable.\n23\t- [x] Do not automate posting in the first version.\n24\t- [x] Use a licensed stock voice or explicitly approved voice only.\n25\t- [x] Track manual touch time per video to identify the next automation target.\n26\t\n27\t## Technical Foundation\n28\t\n29\t- [x] Initialize Python project scaffold with test runner.\n30\t- [x] Add local Postgres setup and initial migrations.\n31\t- [x] Model tenants, media assets, jobs, and job steps with approval state.\n32\t- [x] Build workflow config parser and runner with approval gates.\n33\t- [x] Build CLI commands for running workflows, checking status, and approving scripts.\n34\t- [x] Add media utilities for ffmpeg command construction and rendering.\n35\t- [x] Add a local no-paid-API demo render path that produces a playable vertical MP4 from the phone video.\n36\t- [x] Render transcript-derived TTS narration with synchronized captions and source audio muted by default.\n37\t- [x] Wire real transcription via OpenAI Whisper (`--transcription-provider whisper`). Audio is extracted before submission to avoid container format issues with the API.\n38\t- [x] Improve transcript cleanup: remove filler words, hesitation sounds, consecutive duplicate words. Re-capitalize after removal.\n39\t- [x] Caption timing uses Whisper segment timestamps (scaled to TTS duration) when available, with equal-duration chunks as the offline fallback.\n40\t- [x] Evaluate provider-backed word-level timestamps for tighter per-word caption sync (current path uses sentence-level segments).\n41\t- [x] Make local TTS verification stricter and investigate macOS `say` intermittently producing header-only audio before falling back to silent demo audio.\n42\t\n43\t## Listing URL Reel\n44\t\n45\t- [x] Research real-estate reel competitors, HeyGen/HyperFrames capabilities, listing-source terms, Instagram output requirements, and voice-cloning constraints.\n46\t- [x] Write an implementation-ready listing URL to Instagram reel plan.\n47\t- [x] Add a canonical authorized listing manifest with source policy, path confinement, rights attestation, and photo integrity hashes.\n48\t- [x] Add a single approval bundle covering facts, narration, caption, photo order, cover choice, and contact outro.\n49\t- [x] Render a 9:16 photo reel with restrained pan/zoom motion, captions, narration, and a contact outro.\n50\t- [x] Generate a designed property cover and include it in the manual Instagram handoff package.\n51\t- [x] Require consent and audible output when cloned narration is requested.\n52\t- [x] Run and inspect a local approval-resume end-to-end listing reel render with a real fixture (intentional silent provider; live cloned-voice validation still requires owner consent and credentials).\n53\t\n54\t## Testing\n55\t\n56\t- [x] Use TDD for deterministic business logic, config parsing, tenant scoping, approval gates, and media command construction.\n57\t- [x] Use BDD-style scenarios for the video narration workflow.\n58\t- [x] Mock paid/external APIs in the default test suite.\n59\t- [x] Add opt-in live integration tests only after mocked contracts are stable.\n60\t- [x] Add a short test video fixture for the end-to-end path.\n61\t- [x] Verify local render execution against the committed short video fixture.\n62\t\n63\t## Provider Setup\n64\t\n65\t- [x] Document local `.env` setup.\n66\t- [x] Document Neon database creation and migration steps.\n67\t- [x] Document Vercel env vars and deployment steps for any later approval UI/API.\n68\t- [x] Document Cloudflare DNS setup for the chosen domain/subdomain.\n69\t- [x] Keep long-running video rendering out of Vercel request handlers.\n70\t"}]},"uuid":"2deb35b4-0d93-4638-8ad3-9aff417c6985","timestamp":"2026-07-08T15:07:00.603Z","toolUseResult":{"type":"text","file":{"filePath":"/workspace/extra/projects/stagehand/docs/punch-list.md","content":"# CreatorFlow Punch List\n\nThis list tracks the work needed to prove the first local AI workflow before broadening into a platform.\n\n## Project Standards\n\n- [x] Keep a repo-level todo/punch list as a standard project operating artifact.\n- [x] Add project-level agent instructions requiring the punch list to stay current.\n\n## Discovery\n\n- [x] Prepare a first-agent discovery packet and acceptance criteria worksheet.\n- [ ] Collect 5-8 raw walkthrough videos from the first real estate agent.\n- [ ] Collect examples of posts/videos the agent considers publishable.\n- [ ] Confirm target turnaround time, revision expectations, and pricing signal.\n- [ ] Capture real estate compliance preferences and required brokerage/disclaimer language.\n- [ ] Define first workflow acceptance criteria from the discovery conversation.\n\n## Product Guardrails\n\n- [x] Keep the first version concierge-first: client sends raw input, operator reviews, client receives finished output.\n- [x] Require human approval before final rendered output is considered publishable.\n- [x] Do not automate posting in the first version.\n- [x] Use a licensed stock voice or explicitly approved voice only.\n- [x] Track manual touch time per video to identify the next automation target.\n\n## Technical Foundation\n\n- [x] Initialize Python project scaffold with test runner.\n- [x] Add local Postgres setup and initial migrations.\n- [x] Model tenants, media assets, jobs, and job steps with approval state.\n- [x] Build workflow config parser and runner with approval gates.\n- [x] Build CLI commands for running workflows, checking status, and approving scripts.\n- [x] Add media utilities for ffmpeg command construction and rendering.\n- [x] Add a local no-paid-API demo render path that produces a playable vertical MP4 from the phone video.\n- [x] Render transcript-derived TTS narration with synchronized captions and source audio muted by default.\n- [x] Wire real transcription via OpenAI Whisper (`--transcription-provider whisper`). Audio is extracted before submission to avoid container format issues with the API.\n- [x] Improve transcript cleanup: remove filler words, hesitation sounds, consecutive duplicate words. Re-capitalize after removal.\n- [x] Caption timing uses Whisper segment timestamps (scaled to TTS duration) when available, with equal-duration chunks as the offline fallback.\n- [x] Evaluate provider-backed word-level timestamps for tighter per-word caption sync (current path uses sentence-level segments).\n- [x] Make local TTS verification stricter and investigate macOS `say` intermittently producing header-only audio before falling back to silent demo audio.\n\n## Listing URL Reel\n\n- [x] Research real-estate reel competitors, HeyGen/HyperFrames capabilities, listing-source terms, Instagram output requirements, and voice-cloning constraints.\n- [x] Write an implementation-ready listing URL to Instagram reel plan.\n- [x] Add a canonical authorized listing manifest with source policy, path confinement, rights attestation, and photo integrity hashes.\n- [x] Add a single approval bundle covering facts, narration, caption, photo order, cover choice, and contact outro.\n- [x] Render a 9:16 photo reel with restrained pan/zoom motion, captions, narration, and a contact outro.\n- [x] Generate a designed property cover and include it in the manual Instagram handoff package.\n- [x] Require consent and audible output when cloned narration is requested.\n- [x] Run and inspect a local approval-resume end-to-end listing reel render with a real fixture (intentional silent provider; live cloned-voice validation still requires owner consent and credentials).\n\n## Testing\n\n- [x] Use TDD for deterministic business logic, config parsing, tenant scoping, approval gates, and media command construction.\n- [x] Use BDD-style scenarios for the video narration workflow.\n- [x] Mock paid/external APIs in the default test suite.\n- [x] Add opt-in live integration tests only after mocked contracts are stable.\n- [x] Add a short test video fixture for the end-to-end path.\n- [x] Verify local render execution against the committed short video fixture.\n\n## Provider Setup\n\n- [x] Document local `.env` setup.\n- [x] Document Neon database creation and migration steps.\n- [x] Document Vercel env vars and deployment steps for any later approval UI/API.\n- [x] Document Cloudflare DNS setup for the chosen domain/subdomain.\n- [x] Keep long-running video rendering out of Vercel request handlers.\n","numLines":70,"startLine":1,"totalLines":70}},"sourceToolAssistantUUID":"e09f5714-c3b2-4ff7-a328-2ac24646410e","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/extra/projects/stagehand","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
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{"parentUuid":"3b850cf5-70a0-4d2f-853b-70a7133d041c","isSidechain":false,"promptId":"5cf2b9aa-1e4c-4000-a379-b7377df30c86","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01SU7RKwTCq43vmoQxX9XTgD","type":"tool_result","content":"1\t---\n2\ttitle: Listing URL to Instagram Reel - Plan\n3\ttype: feat\n4\tdate: 2026-07-07\n5\tartifact_contract: ce-unified-plan/v1\n6\tartifact_readiness: implementation-ready\n7\tproduct_contract_source: ce-plan-bootstrap\n8\texecution: code\n9\tdeepened: 2026-07-07\n10\t---\n11\t\n12\t# Listing URL to Instagram Reel - Plan\n13\t\n14\t## Goal Capsule\n15\t\n16\t- **Objective:** Turn a property listing URL plus authorized listing media into a reviewable, narrated 9:16 reel and complete manual Instagram handoff package.\n17\t- **Authority:** Listing facts and photos supplied by the operator or a licensed provider are authoritative; generated copy must not add unsupported claims.\n18\t- **Execution profile:** Local CLI and background media worker, with deterministic offline tests and opt-in paid-provider tests.\n19\t- **Stop conditions:** Do not scrape sites that prohibit automated access, render unapproved listing content, or silently replace requested cloned narration with silence.\n20\t- **Tail ownership:** The operator reviews the listing bundle before render and manually posts the resulting package.\n21\t\n22\t---\n23\t\n24\t## Product Contract\n25\t\n26\t### Summary\n27\t\n28\tAdd a `listing_reel` workflow that treats the listing URL as the canonical property identity, ingests operator-authorized facts and photos through a provider-neutral snapshot, pauses for review, and produces a narrated vertical reel with captions, a designed cover, a contact outro, and Instagram caption metadata.\n29\t\n30\t### Problem Frame\n31\t\n32\tThe current workflow turns walkthrough footage into narrated video, but it cannot turn existing listing photography into a social post. Most listings already have approved photos, and tools such as AutoReel, Momenzo, AbodeVid, and HeyGen show that subtle photo motion, logical room ordering, consistent branding, and short vertical output are the useful baseline.\n33\t\n34\tThe user-provided Zillow URL cannot be treated as a scrape target. Zillow's current terms prohibit automated queries and republishing listing images or information without explicit permission. The workflow therefore needs a source boundary that accepts the URL while requiring an authorized manifest or licensed provider for the underlying data.\n35\t\n36\t### Requirements\n37\t\n38\t**Listing intake and truth**\n39\t\n40\t- R1. The CLI accepts a property listing URL and creates a canonical listing snapshot from an operator-provided manifest or an explicitly authorized provider.\n41\t- R2. The snapshot validates the source URL, listing facts, ordered local photo paths, cover choice, attribution, and explicit operator rights attestation before downstream work begins.\n42\t- R3. Zillow and other prohibited domains must never trigger generic automated page fetching; the CLI must return an actionable authorized-manifest or licensed-provider instruction instead.\n43\t- R4. Raw photos, client manifests, generated media, and contact details remain outside git unless they are synthetic test fixtures.\n44\t\n45\t**Human review and narration**\n46\t\n47\t- R5. One review bundle exposes the sourced facts, narration, Instagram caption, photo order, cover selection, and contact outro content before any paid voice synthesis or final rendering.\n48\t- R6. The workflow pauses at the existing approval gate and resumes only from a valid approved review bundle.\n49\t- R7. Richard Fowler narration is selected through tenant/provider configuration, requires recorded consent, and fails loudly if cloned narration was requested but no audible provider result is produced.\n50\t- R8. Narration and captions use only approved listing facts and avoid unsupported claims about schools, safety, demographics, financing, appreciation, or protected classes.\n51\t\n52\t**Reel and handoff artifacts**\n53\t\n54\t- R9. The renderer creates a 1080x1920, 30 fps, H.264/AAC MP4 from real listing photos using restrained pan/zoom motion and simple transitions in the approved order.\n55\t- R10. The reel includes timed captions and a final contact card with the configured agent name plus at least one contact method or destination.\n56\t- R11. The package includes a designed property cover image, the approved Instagram caption, canonical listing snapshot, final video, and metadata needed for manual posting.\n57\t- R12. The default target is a concise 20-45 second reel, with duration distributed across photos and a 4-5 second outro instead of hard-coded per-photo timing.\n58\t\n59\t**Verification**\n60\t\n61\t- R13. Deterministic parsing, validation, approval, command construction, and packaging are covered offline; paid and network provider tests remain opt-in.\n62\t- R14. A local end-to-end fixture render must prove visible photo motion, audible or intentionally synthetic narration, changing captions, a readable outro, a valid cover, muted source audio, and correct duration/dimensions.\n63\t\n64\t### Key Flow\n65\t\n66\t- F1. Operator starts a listing reel.\n67\t - **Trigger:** The operator supplies a listing URL, authorized manifest, and tenant/contact/voice settings.\n68\t - **Steps:** Normalize snapshot; draft review bundle; pause; operator edits and approves; synthesize narration; create captions and graphics; render reel; package for Instagram.\n69\t - **Outcome:** A reviewed `publish/` directory contains the reel, cover, caption, snapshot, and metadata.\n70\t\n71\t### Acceptance Examples\n72\t\n73\t- AE1. Given a valid Zillow URL and a local authorized manifest with six photos, when the operator starts the workflow, then the URL is retained as source identity and no request is made to Zillow.\n74\t- AE2. Given a review bundle awaiting approval, when no approval has been recorded, then voice synthesis, graphics, rendering, and packaging have not run.\n75\t- AE3. Given an approved bundle and silent offline narration, when rendering completes, then the MP4 is 1080x1920 at 30 fps, includes motion across multiple photos, timed captions, and the configured outro.\n76\t- AE4. Given `elevenlabs` with consent missing, an absent voice ID, or failed synthesis, when the workflow resumes, then it fails instead of producing a silent reel labeled as cloned narration.\n77\t- AE5. Given a cover photo index outside the approved list or a missing photo, when the snapshot is validated, then intake fails before approval.\n78\t\n79\t### Scope Boundaries\n80\t\n81\tIn scope: local CLI intake, manifest/provider boundary, approval bundle, deterministic photo motion, captions, cloned-voice integration, designed cover, branded contact outro, and manual Instagram packaging.\n82\t\n83\t#### Deferred to Follow-Up Work\n84\t\n85\t- Licensed Bridge/RESO ingestion after the pilot agent or brokerage obtains data access.\n86\t- A generic JSON-LD/OpenGraph adapter only for domains whose terms and operator authorization permit automated retrieval.\n87\t- A HeyGen provider spike for its Just Listed/Open House templates, image-to-video motion, agent avatar, and multilingual variants; the public material does not expose a stable real-estate-specific API contract suitable for the core workflow today.\n88\t- Personalized HeyGen follow-up videos, neighborhood/market updates, and a 24/7 interactive Richard avatar for lead qualification; these are separate engagement workflows with CRM, knowledge-base, disclosure, and escalation requirements.\n89\t- A HyperFrames renderer after the FFmpeg vertical slice is proven. HyperFrames offers deterministic HTML/GSAP motion, design systems, social overlays, and stronger reusable visual composition, but adding Node 22 and a second rendering stack before the first reel is validated would widen the pilot unnecessarily.\n90\t- Automatic social posting, web UI, billing, authentication, AI-generated property imagery, virtual staging, and autonomous caption optimization.\n91\t\n92\t### Dependencies and Preconditions\n93\t\n94\t- The operator must have rights to use the listing photos and facts.\n95\t- Richard must create/verify and share his provider voice or otherwise approve a provider-supported clone according to that provider's rules.\n96\t- At least one public contact destination must be supplied outside git.\n97\t- FFmpeg and ffprobe remain required for local render verification.\n98\t\n99\t---\n100\t\n101\t## Planning Contract\n102\t\n103\t### Key Technical Decisions\n104\t\n105\t- KTD1. **Use a provider-neutral listing snapshot and a separate agent profile.** URL parsing, manifest ingestion, and future licensed APIs terminate in one validated property model; tenant contact and voice settings remain separate so listing data cannot overwrite agent identity.\n106\t- KTD2. **Treat Zillow as identity-only in V1.** The URL is stored and displayed for review, while facts and photos come from the authorized manifest; prohibited domains are blocked from generic fetch behavior.\n107\t- KTD3. **Use a content-addressed JSON review bundle.** It contains narration, caption, photo order, photo hashes, cover selection, and outro content; one approval therefore covers the exact publish-visible material before expensive work starts, and render re-verifies hashes to prevent post-approval substitution.\n108\t- KTD4. **Extend the existing Python/FFmpeg worker for the first slice.** It preserves current job storage, approvals, TTS, captioning, offline tests, and local execution. HyperFrames remains the preferred later renderer if the pilot needs richer brand systems or reusable templates.\n109\t- KTD5. **Render motion deterministically.** FFmpeg zoom/pan parameters alternate by scene and remain within restrained bounds; no generative image-to-video model may alter room geometry or property features.\n110\t- KTD6. **Make cloned narration strict.** The voice module must support continuous ElevenLabs synthesis for photo reels and distinguish explicit silent fixtures from provider failure.\n111\t- KTD7. **Generate the cover independently from a video frame.** A selected property photo receives a readable, centered title/fact treatment and is exported at Instagram's recommended 1:1.55 cover ratio while the first reel scene remains full 9:16.\n112\t- KTD8. **Keep HeyGen optional, not foundational.** HeyGen has real-estate templates, photo animation, voice cloning, avatars, and multilingual output, but the core API documentation is avatar-oriented and provider output is paid and non-deterministic. It is best evaluated behind a provider seam after the local acceptance baseline exists.\n113\t- KTD9. **Expose a dedicated `listing-reel` command.** The existing `run` command requires a walkthrough-video input, so overloading it would create ambiguous flags and invalid states; status, approve, reject, and touch-time commands continue to operate on the resulting workflow job.\n114\t\n115\t### System-Wide Impact\n116\t\n117\t- The shared approval runner continues storing the approved artifact in `approved_script`; the listing workflow parses that value into distinct approved narration and caption outputs after approval, without changing existing workflow behavior.\n118\t- The voice module gains continuous provider synthesis and a strict-audio option. Existing walkthrough demo fallbacks remain unchanged unless strict mode is explicitly set by the listing workflow.\n119\t- Media probing expands to expose codec and frame-rate evidence used by the new renderer's tests and may be reused by existing render verification.\n120\t- Instagram packaging gains optional cover and snapshot inputs while retaining frame-extraction fallback for existing publish jobs.\n121\t- Tenant contact and provider credentials may enter through CLI/environment configuration but must not be copied into the canonical listing snapshot, logs, or committed fixtures.\n122\t\n123\t### Risks and Mitigations\n124\t\n125\t- **Unauthorized source use:** Require a rights attestation in the manifest, default every web domain to no-fetch, and permit automated providers only through an explicit allowlisted adapter with documented authorization.\n126\t- **Path traversal or local file disclosure:** Resolve manifest media against an operator-selected media root, reject escapes and symlink escapes, and accept only supported image types.\n127\t- **Post-approval media substitution:** Store SHA-256 and byte size for each approved photo and re-verify both immediately before render.\n128\t- **Stale or misleading listing facts:** Record snapshot creation time and source attribution, expose all facts in the approval bundle, and never refresh data after approval within the same job.\n129\t- **Synthetic property misrepresentation:** Limit V1 to deterministic 2D crops, pans, zooms, and transitions over approved photos; do not generate or alter rooms, views, fixtures, or geometry.\n130\t- **Voice impersonation or silent failure:** Require voice-owner consent metadata, use an owner-created/shared provider voice where required, keep credentials out of artifacts, and fail closed when strict cloned narration is unavailable or unprobeable.\n131\t- **Contact-data exposure:** Keep agent contact configuration local, include only approved public contact fields in the outro/package, and avoid printing those values in CLI status output.\n132\t- **Unusable crop or text placement:** Allow an approved cover focal point, use a neutral high-contrast fallback theme without unlicensed logos, and inspect the dedicated cover plus 9:16 safe zones on a real device before pilot delivery.\n133\t\n134\t### High-Level Technical Design\n135\t\n136\t```mermaid\n137\tflowchart TB\n138\t CLI[Listing reel CLI] --> Policy{Source policy}\n139\t Policy -->|Authorized manifest| Snapshot[Canonical listing snapshot]\n140\t Policy -->|Licensed provider later| Snapshot\n141\t Policy -->|Prohibited generic fetch| Stop[Actionable stop]\n142\t Snapshot --> Draft[Review bundle draft]\n143\t Draft --> Gate{Human approval}\n144\t Gate -->|Revise| Draft\n145\t Gate -->|Approve| Voice[Strict voice synthesis]\n146\t Voice --> Captions[Timed captions]\n147\t Captions --> Graphics[Cover and contact outro]\n148\t Graphics --> Render[Photo reel renderer]\n149\t Render --> Package[Instagram handoff package]\n150\t```\n151\t\n152\t```mermaid\n153\tstateDiagram-v2\n154\t [*] --> Intake\n155\t Intake --> WaitingForApproval: valid snapshot and review bundle\n156\t Intake --> Failed: source or media validation fails\n157\t WaitingForApproval --> Rendering: approved bundle parses and validates\n158\t WaitingForApproval --> Failed: rejected\n159\t Rendering --> Packaged: voice, graphics, and render succeed\n160\t Rendering --> Failed: required narration or artifact fails\n161\t Packaged --> [*]\n162\t```\n163\t\n164\t### Research That Shapes the Plan\n165\t\n166\t- AutoReel recommends 10-20 strong photos, exterior-to-interior sequencing, restrained pans/zooms, minimal text, and roughly 30-second output: https://www.autoreelapp.com/blog/how-to-make-real-estate-video-using-only-property-photos\n167\t- Momenzo emphasizes guided capture, automatic editing, AI captions, branding, and real-estate templates: https://www.momenzo.com/\n168\t- HeyGen offers a real-estate maker with Just Listed, Open House, and agent-intro templates; photo animation, voice cloning, avatars, captions, branding, and multilingual output are the relevant capabilities: https://www.heygen.com/en-gb/tool/real-estate-video-maker\n169\t- HeyGen also positions interactive avatars for round-the-clock FAQ, sales, and follow-up conversations, which confirms a later lead-engagement track but does not belong in the listing-reel render path: https://www.heygen.com/interactive-avatar/\n170\t- HyperFrames is an Apache-2.0 deterministic HTML/GSAP renderer with reusable social overlays and local FFmpeg output, but its installed workflows are general-purpose rather than real-estate-specific: https://github.com/heygen-com/hyperframes\n171\t- Zillow prohibits automated queries and republishing listing images or data without explicit permission: https://www.zillow.com/corporate/terms-of-use/\n172\t- Bridge provides licensed RESO Web API access after MLS approval: https://www.bridgeinteractive.com/developers/bridge-api/\n173\t- Meta recommends Reel aspect ratios up to 9:16, at least 30 fps and 720 px, and a 420x654 cover ratio: https://www.facebook.com/help/1038071743007909/\n174\t- ElevenLabs Professional Voice Clones must be created and verified by the voice owner, then privately shared: https://help.elevenlabs.io/hc/en-us/articles/36842751624209-Can-I-create-a-Professional-Voice-Clone-of-someone-else-s-voice\n175\t\n176\t---\n177\t\n178\t## Implementation Units\n179\t\n180\t### U1. Canonical listing snapshot and source policy\n181\t\n182\t- **Goal:** Validate listing identity, authorized facts, ordered local photos, cover selection, and source rights before workflow execution.\n183\t- **Requirements:** R1-R4, R13; AE1, AE5.\n184\t- **Dependencies:** None.\n185\t- **Files:** `core/listings/__init__.py`, `core/listings/models.py`, `core/listings/manifest.py`, `tests/test_listing_manifest.py`.\n186\t- **Approach:** Introduce typed immutable snapshot, photo, and agent-profile records; strict HTTPS URL normalization; media-root-confined path resolution; photo hashes; duplicate detection; rights attestation; and a source-policy check that rejects automated retrieval for prohibited domains.\n187\t- **Execution note:** Implement validation test-first because this contract protects every downstream claim and asset.\n188\t- **Patterns to follow:** Frozen dataclasses and explicit validation used in `core/workflows/config.py`; private media exclusions in `.gitignore` and `AGENTS.md`.\n189\t- **Test scenarios:**\n190\t 1. Load a valid manifest with relative photo paths and preserve approved order and source URL.\n191\t 2. Reject URL mismatch, unsupported scheme, missing photos, duplicates, empty facts, invalid cover index, missing rights attestation, or no contact method in the separate agent profile.\n192\t 3. Classify a Zillow URL as manifest/licensed-provider only and prove no fetch client is invoked.\n193\t 4. Reject absolute, parent-traversal, and symlink-escape photo paths outside the configured media root.\n194\t 5. Serialize the normalized snapshot with hashes and attribution without leaking contact fields or credentials.\n195\t- **Verification:** A snapshot round-trip is deterministic and invalid manifests stop before a job reaches approval.\n196\t\n197\t### U2. Review bundle and approval parsing\n198\t\n199\t- **Goal:** Put every publish-visible fact and choice into one operator-editable artifact.\n200\t- **Requirements:** R5, R6, R8, R13; F1, AE2.\n201\t- **Dependencies:** U1.\n202\t- **Files:** `core/listings/review.py`, `core/workflows/listing_reel_modules.py`, `tests/test_listing_review.py`, `tests/test_listing_reel_workflow.py`.\n203\t- **Approach:** Draft a versioned JSON bundle with snapshot digest, narration, caption, photo order, cover index, and outro content. After the shared approval gate, parse the approved JSON, require the digest and asset set to match intake, and expose distinct approved narration/caption values.\n204\t- **Execution note:** Start with the BDD scenario proving the workflow pauses before any paid or render step.\n205\t- **Patterns to follow:** `WorkflowRunner` approval resume semantics and the existing Instagram caption builder.\n206\t- **Test scenarios:**\n207\t 1. Draft content uses only snapshot facts and produces a concise warm narration and caption.\n208\t 2. Starting the workflow stops at approval with the review artifact and no voice/render/package outputs.\n209\t 3. Approval resumes from edited narration/caption and preserves the approved photo set.\n210\t 4. Reject malformed JSON, changed snapshot digest, injected photo paths, missing outro contact, and unsupported claims fields.\n211\t- **Verification:** The approved bundle is the only source for downstream narration, caption, order, cover, and outro.\n212\t\n213\t### U3. Designed cover and contact outro graphics\n214\t\n215\t- **Goal:** Produce a compelling property cover and readable final contact card from approved content.\n216\t- **Requirements:** R10, R11, R13; AE3.\n217\t- **Dependencies:** U2.\n218\t- **Files:** `core/media/listing_graphics.py`, `tests/test_listing_graphics.py`.\n219\t- **Approach:** Use Pillow to crop approved photos around an optional focal point without distortion, apply a neutral high-contrast editorial treatment, center critical cover text within crop-safe bounds, and render an outro with agent name, CTA, and one or more contact methods. Export a Reel cover at 1:1.55 and a 9:16 outro scene; use no brokerage logo unless an authorized asset is supplied.\n220\t- **Patterns to follow:** Pillow asset generation and font fallback in `core/media/caption_image.py`.\n221\t- **Test scenarios:**\n222\t 1. Render covers from landscape and portrait photos at exact dimensions with non-empty image data.\n223\t 2. Honor center and explicit focal points while keeping title and key facts within the central safe region and wrapping long text without clipping.\n224\t 3. Render a contact card with handle, phone, email, or website and reject a card with no contact destination.\n225\t 4. Avoid displaying absent or unapproved listing fields.\n226\t- **Verification:** Image inspection and pixel/dimension assertions confirm readable, non-blank outputs.\n227\t\n228\t### U4. Deterministic photo-reel renderer\n229\t\n230\t- **Goal:** Render approved photos, captions, narration, and outro into an Instagram-compatible moving reel.\n231\t- **Requirements:** R9, R10, R12-R14; AE3.\n232\t- **Dependencies:** U2, U3.\n233\t- **Files:** `core/media/photo_reel.py`, `core/media/ffmpeg_utils.py`, `core/models.py`, `core/workflows/listing_reel_modules.py`, `tests/test_photo_reel.py`, `tests/test_media.py`.\n234\t- **Approach:** Construct one FFmpeg filter graph with per-photo scale/crop and restrained zoom/pan, simple crossfades, caption overlays, a static outro scene, and narration audio. Calculate photo duration from total narration/outro duration and use fixed 30 fps output settings.\n235\t- **Execution note:** Build command construction test-first, then run a real local render because filter-graph validity cannot be proven by string assertions.\n236\t- **Patterns to follow:** Command builders and executable guard in `core/media/ffmpeg_utils.py`.\n237\t- **Test scenarios:**\n238\t 1. Build valid graphs for one photo, multiple photos, mixed orientations, captions, and outro.\n239\t 2. Alternate motion direction without exceeding configured zoom bounds.\n240\t 3. Distribute duration across the approved photo count and keep the outro within 4-5 seconds.\n241\t 4. Reject zero photos, non-positive duration, changed photo hashes, missing narration, or unsupported output settings.\n242\t 5. Render a real fixture and verify dimensions, frame rate, video/audio codecs, audio stream, duration, and changing frames.\n243\t- **Verification:** The committed command tests pass and an ffprobe/visual artifact check confirms a playable moving 9:16 MP4.\n244\t\n245\t### U5. Strict cloned narration and package integration\n246\t\n247\t- **Goal:** Make continuous photo-reel narration audible and deliver the designed cover instead of a random frame grab.\n248\t- **Requirements:** R7, R8, R11, R13; AE4.\n249\t- **Dependencies:** U2-U4.\n250\t- **Files:** `core/config.py`, `.env.example`, `cli/main.py`, `core/workflows/modules.py`, `core/publishing/instagram.py`, `tests/test_config_settings.py`, `tests/test_cli.py`, `tests/test_workflow_runner.py`, `tests/test_instagram_package.py`.\n251\t- **Approach:** Add consent and voice-owner settings, support continuous ElevenLabs synthesis when no transcript segments exist, add strict required-audio behavior for listing reels, prefer approved narration/caption keys, prevent credentials from entering job artifacts, and package the generated cover and snapshot.\n252\t- **Execution note:** Preserve current demo fallbacks for existing workflows; strict failure applies only when the listing workflow requests cloned narration.\n253\t- **Patterns to follow:** Lazy provider construction in `cli/main.py` and opt-in provider contracts in `tests/test_live_integrations.py`.\n254\t- **Test scenarios:**\n255\t 1. Build the configured voice client only when provider, voice ID, API key, and consent are present.\n256\t 2. Continuous ElevenLabs synthesis writes a probeable narration file for a listing script.\n257\t 3. Provider errors and empty/unprobeable output fail a strict listing job without silent fallback.\n258\t 4. Offline silent fixtures remain explicit and package metadata records the actual voice provider.\n259\t 5. Instagram packaging copies the designed cover, approved caption, and snapshot.\n260\t- **Verification:** Mocked provider tests prove contracts; an opt-in live test may validate Richard's privately shared voice without entering the default suite.\n261\t\n262\t### U6. End-to-end listing reel CLI and operator documentation\n263\t\n264\t- **Goal:** Expose and prove the complete concierge workflow through the local CLI.\n265\t- **Requirements:** R1-R14; F1; AE1-AE5.\n266\t- **Dependencies:** U1-U5.\n267\t- **Files:** `workflows/listing_reel/config.yaml`, `cli/main.py`, `tests/test_cli.py`, `tests/test_listing_reel_workflow.py`, `tests/fixtures/listing_reel/manifest.json`, `README.md`, `docs/setup.md`, `docs/punch-list.md`, `docs/listing-reel-operator-guide.md`.\n268\t- **Approach:** Add a dedicated `listing-reel` command with listing URL, manifest, media root, tenant, contact, TTS, and render flags; preserve status/approve/reject behavior; document source rights, voice consent, review, render, inspection, and manual posting.\n269\t- **Execution note:** Finish with an actual approval-resume render using locally extracted property frames or synthetic committed fixtures, then inspect the generated artifacts rather than relying on unit tests alone.\n270\t- **Patterns to follow:** Current `run`, `approve`, `status`, and manual Instagram handoff commands.\n271\t- **Test scenarios:**\n272\t 1. CLI forwards all listing, contact, voice, and render inputs without printing private content.\n273\t 2. Full start pauses for approval and approval resumes through package completion.\n274\t 3. Status and rejection work for the new workflow.\n275\t 4. Invalid source rights, missing consent, or missing media return actionable errors before paid calls.\n276\t 5. End-to-end output contains final video, cover, caption, snapshot, metadata, narration, captions, outro, and render command artifacts.\n277\t- **Verification:** The offline suite is green and the operator guide's local fixture flow produces and validates the expected package.\n278\t\n279\t---\n280\t\n281\t## Verification Contract\n282\t\n283\t| Gate | Applies to | Done signal |\n284\t|---|---|---|\n285\t| `python3 -m pytest -q` | U1-U6 | Default offline suite passes without network or paid APIs. |\n286\t| Focused listing workflow tests | U1-U6 | Validation, approval, strict voice, graphics, render commands, and packaging scenarios pass. |\n287\t| Local approval-resume render | U3-U6 | A real fixture produces a playable 1080x1920 MP4 and complete publish package. |\n288\t| ffprobe artifact inspection | U4-U6 | H.264 video, AAC audio, 30 fps, expected duration, and 9:16 dimensions are present. |\n289\t| Visual/audio inspection | U3-U6 | Photos visibly move, captions change, narration is audible or explicitly synthetic, outro is readable, cover is compelling, and no source audio leaks. |\n290\t| Opt-in live provider check | U5 | When explicitly enabled, the privately shared Richard voice produces audible speech and the artifact is not committed. |\n291\t\n292\t---\n293\t\n294\t## Definition of Done\n295\t\n296\t- A listing URL plus authorized local manifest can run from CLI intake through approval to a complete Instagram handoff package.\n297\t- The example Zillow URL is accepted as source identity without any automated Zillow request.\n298\t- Every publish-visible fact, script line, photo choice, cover, and contact method is approved before rendering.\n299\t- The final video has real photo motion, captions, configured narration, and a readable contact outro.\n300\t- The custom cover is designed from an approved property photo and included in the package.\n301\t- Strict cloned-voice failures never masquerade as successful silent narration.\n302\t- Offline and BDD tests pass, a real local render is inspected, and live provider calls remain guarded.\n303\t- Documentation and `docs/punch-list.md` reflect the implemented and still-deferred work.\n304\t- Raw media, client data, provider outputs, credentials, and abandoned implementation experiments are absent from git.\n305\t"}]},"uuid":"77566c0c-a4de-406f-9e1c-5aaaf58ade8f","timestamp":"2026-07-08T15:07:14.737Z","toolUseResult":{"type":"text","file":{"filePath":"/workspace/extra/projects/stagehand/docs/plans/2026-07-07-001-feat-listing-url-reel-plan.md","content":"---\ntitle: Listing URL to Instagram Reel - Plan\ntype: feat\ndate: 2026-07-07\nartifact_contract: ce-unified-plan/v1\nartifact_readiness: implementation-ready\nproduct_contract_source: ce-plan-bootstrap\nexecution: code\ndeepened: 2026-07-07\n---\n\n# Listing URL to Instagram Reel - Plan\n\n## Goal Capsule\n\n- **Objective:** Turn a property listing URL plus authorized listing media into a reviewable, narrated 9:16 reel and complete manual Instagram handoff package.\n- **Authority:** Listing facts and photos supplied by the operator or a licensed provider are authoritative; generated copy must not add unsupported claims.\n- **Execution profile:** Local CLI and background media worker, with deterministic offline tests and opt-in paid-provider tests.\n- **Stop conditions:** Do not scrape sites that prohibit automated access, render unapproved listing content, or silently replace requested cloned narration with silence.\n- **Tail ownership:** The operator reviews the listing bundle before render and manually posts the resulting package.\n\n---\n\n## Product Contract\n\n### Summary\n\nAdd a `listing_reel` workflow that treats the listing URL as the canonical property identity, ingests operator-authorized facts and photos through a provider-neutral snapshot, pauses for review, and produces a narrated vertical reel with captions, a designed cover, a contact outro, and Instagram caption metadata.\n\n### Problem Frame\n\nThe current workflow turns walkthrough footage into narrated video, but it cannot turn existing listing photography into a social post. Most listings already have approved photos, and tools such as AutoReel, Momenzo, AbodeVid, and HeyGen show that subtle photo motion, logical room ordering, consistent branding, and short vertical output are the useful baseline.\n\nThe user-provided Zillow URL cannot be treated as a scrape target. Zillow's current terms prohibit automated queries and republishing listing images or information without explicit permission. The workflow therefore needs a source boundary that accepts the URL while requiring an authorized manifest or licensed provider for the underlying data.\n\n### Requirements\n\n**Listing intake and truth**\n\n- R1. The CLI accepts a property listing URL and creates a canonical listing snapshot from an operator-provided manifest or an explicitly authorized provider.\n- R2. The snapshot validates the source URL, listing facts, ordered local photo paths, cover choice, attribution, and explicit operator rights attestation before downstream work begins.\n- R3. Zillow and other prohibited domains must never trigger generic automated page fetching; the CLI must return an actionable authorized-manifest or licensed-provider instruction instead.\n- R4. Raw photos, client manifests, generated media, and contact details remain outside git unless they are synthetic test fixtures.\n\n**Human review and narration**\n\n- R5. One review bundle exposes the sourced facts, narration, Instagram caption, photo order, cover selection, and contact outro content before any paid voice synthesis or final rendering.\n- R6. The workflow pauses at the existing approval gate and resumes only from a valid approved review bundle.\n- R7. Richard Fowler narration is selected through tenant/provider configuration, requires recorded consent, and fails loudly if cloned narration was requested but no audible provider result is produced.\n- R8. Narration and captions use only approved listing facts and avoid unsupported claims about schools, safety, demographics, financing, appreciation, or protected classes.\n\n**Reel and handoff artifacts**\n\n- R9. The renderer creates a 1080x1920, 30 fps, H.264/AAC MP4 from real listing photos using restrained pan/zoom motion and simple transitions in the approved order.\n- R10. The reel includes timed captions and a final contact card with the configured agent name plus at least one contact method or destination.\n- R11. The package includes a designed property cover image, the approved Instagram caption, canonical listing snapshot, final video, and metadata needed for manual posting.\n- R12. The default target is a concise 20-45 second reel, with duration distributed across photos and a 4-5 second outro instead of hard-coded per-photo timing.\n\n**Verification**\n\n- R13. Deterministic parsing, validation, approval, command construction, and packaging are covered offline; paid and network provider tests remain opt-in.\n- R14. A local end-to-end fixture render must prove visible photo motion, audible or intentionally synthetic narration, changing captions, a readable outro, a valid cover, muted source audio, and correct duration/dimensions.\n\n### Key Flow\n\n- F1. Operator starts a listing reel.\n - **Trigger:** The operator supplies a listing URL, authorized manifest, and tenant/contact/voice settings.\n - **Steps:** Normalize snapshot; draft review bundle; pause; operator edits and approves; synthesize narration; create captions and graphics; render reel; package for Instagram.\n - **Outcome:** A reviewed `publish/` directory contains the reel, cover, caption, snapshot, and metadata.\n\n### Acceptance Examples\n\n- AE1. Given a valid Zillow URL and a local authorized manifest with six photos, when the operator starts the workflow, then the URL is retained as source identity and no request is made to Zillow.\n- AE2. Given a review bundle awaiting approval, when no approval has been recorded, then voice synthesis, graphics, rendering, and packaging have not run.\n- AE3. Given an approved bundle and silent offline narration, when rendering completes, then the MP4 is 1080x1920 at 30 fps, includes motion across multiple photos, timed captions, and the configured outro.\n- AE4. Given `elevenlabs` with consent missing, an absent voice ID, or failed synthesis, when the workflow resumes, then it fails instead of producing a silent reel labeled as cloned narration.\n- AE5. Given a cover photo index outside the approved list or a missing photo, when the snapshot is validated, then intake fails before approval.\n\n### Scope Boundaries\n\nIn scope: local CLI intake, manifest/provider boundary, approval bundle, deterministic photo motion, captions, cloned-voice integration, designed cover, branded contact outro, and manual Instagram packaging.\n\n#### Deferred to Follow-Up Work\n\n- Licensed Bridge/RESO ingestion after the pilot agent or brokerage obtains data access.\n- A generic JSON-LD/OpenGraph adapter only for domains whose terms and operator authorization permit automated retrieval.\n- A HeyGen provider spike for its Just Listed/Open House templates, image-to-video motion, agent avatar, and multilingual variants; the public material does not expose a stable real-estate-specific API contract suitable for the core workflow today.\n- Personalized HeyGen follow-up videos, neighborhood/market updates, and a 24/7 interactive Richard avatar for lead qualification; these are separate engagement workflows with CRM, knowledge-base, disclosure, and escalation requirements.\n- A HyperFrames renderer after the FFmpeg vertical slice is proven. HyperFrames offers deterministic HTML/GSAP motion, design systems, social overlays, and stronger reusable visual composition, but adding Node 22 and a second rendering stack before the first reel is validated would widen the pilot unnecessarily.\n- Automatic social posting, web UI, billing, authentication, AI-generated property imagery, virtual staging, and autonomous caption optimization.\n\n### Dependencies and Preconditions\n\n- The operator must have rights to use the listing photos and facts.\n- Richard must create/verify and share his provider voice or otherwise approve a provider-supported clone according to that provider's rules.\n- At least one public contact destination must be supplied outside git.\n- FFmpeg and ffprobe remain required for local render verification.\n\n---\n\n## Planning Contract\n\n### Key Technical Decisions\n\n- KTD1. **Use a provider-neutral listing snapshot and a separate agent profile.** URL parsing, manifest ingestion, and future licensed APIs terminate in one validated property model; tenant contact and voice settings remain separate so listing data cannot overwrite agent identity.\n- KTD2. **Treat Zillow as identity-only in V1.** The URL is stored and displayed for review, while facts and photos come from the authorized manifest; prohibited domains are blocked from generic fetch behavior.\n- KTD3. **Use a content-addressed JSON review bundle.** It contains narration, caption, photo order, photo hashes, cover selection, and outro content; one approval therefore covers the exact publish-visible material before expensive work starts, and render re-verifies hashes to prevent post-approval substitution.\n- KTD4. **Extend the existing Python/FFmpeg worker for the first slice.** It preserves current job storage, approvals, TTS, captioning, offline tests, and local execution. HyperFrames remains the preferred later renderer if the pilot needs richer brand systems or reusable templates.\n- KTD5. **Render motion deterministically.** FFmpeg zoom/pan parameters alternate by scene and remain within restrained bounds; no generative image-to-video model may alter room geometry or property features.\n- KTD6. **Make cloned narration strict.** The voice module must support continuous ElevenLabs synthesis for photo reels and distinguish explicit silent fixtures from provider failure.\n- KTD7. **Generate the cover independently from a video frame.** A selected property photo receives a readable, centered title/fact treatment and is exported at Instagram's recommended 1:1.55 cover ratio while the first reel scene remains full 9:16.\n- KTD8. **Keep HeyGen optional, not foundational.** HeyGen has real-estate templates, photo animation, voice cloning, avatars, and multilingual output, but the core API documentation is avatar-oriented and provider output is paid and non-deterministic. It is best evaluated behind a provider seam after the local acceptance baseline exists.\n- KTD9. **Expose a dedicated `listing-reel` command.** The existing `run` command requires a walkthrough-video input, so overloading it would create ambiguous flags and invalid states; status, approve, reject, and touch-time commands continue to operate on the resulting workflow job.\n\n### System-Wide Impact\n\n- The shared approval runner continues storing the approved artifact in `approved_script`; the listing workflow parses that value into distinct approved narration and caption outputs after approval, without changing existing workflow behavior.\n- The voice module gains continuous provider synthesis and a strict-audio option. Existing walkthrough demo fallbacks remain unchanged unless strict mode is explicitly set by the listing workflow.\n- Media probing expands to expose codec and frame-rate evidence used by the new renderer's tests and may be reused by existing render verification.\n- Instagram packaging gains optional cover and snapshot inputs while retaining frame-extraction fallback for existing publish jobs.\n- Tenant contact and provider credentials may enter through CLI/environment configuration but must not be copied into the canonical listing snapshot, logs, or committed fixtures.\n\n### Risks and Mitigations\n\n- **Unauthorized source use:** Require a rights attestation in the manifest, default every web domain to no-fetch, and permit automated providers only through an explicit allowlisted adapter with documented authorization.\n- **Path traversal or local file disclosure:** Resolve manifest media against an operator-selected media root, reject escapes and symlink escapes, and accept only supported image types.\n- **Post-approval media substitution:** Store SHA-256 and byte size for each approved photo and re-verify both immediately before render.\n- **Stale or misleading listing facts:** Record snapshot creation time and source attribution, expose all facts in the approval bundle, and never refresh data after approval within the same job.\n- **Synthetic property misrepresentation:** Limit V1 to deterministic 2D crops, pans, zooms, and transitions over approved photos; do not generate or alter rooms, views, fixtures, or geometry.\n- **Voice impersonation or silent failure:** Require voice-owner consent metadata, use an owner-created/shared provider voice where required, keep credentials out of artifacts, and fail closed when strict cloned narration is unavailable or unprobeable.\n- **Contact-data exposure:** Keep agent contact configuration local, include only approved public contact fields in the outro/package, and avoid printing those values in CLI status output.\n- **Unusable crop or text placement:** Allow an approved cover focal point, use a neutral high-contrast fallback theme without unlicensed logos, and inspect the dedicated cover plus 9:16 safe zones on a real device before pilot delivery.\n\n### High-Level Technical Design\n\n```mermaid\nflowchart TB\n CLI[Listing reel CLI] --> Policy{Source policy}\n Policy -->|Authorized manifest| Snapshot[Canonical listing snapshot]\n Policy -->|Licensed provider later| Snapshot\n Policy -->|Prohibited generic fetch| Stop[Actionable stop]\n Snapshot --> Draft[Review bundle draft]\n Draft --> Gate{Human approval}\n Gate -->|Revise| Draft\n Gate -->|Approve| Voice[Strict voice synthesis]\n Voice --> Captions[Timed captions]\n Captions --> Graphics[Cover and contact outro]\n Graphics --> Render[Photo reel renderer]\n Render --> Package[Instagram handoff package]\n```\n\n```mermaid\nstateDiagram-v2\n [*] --> Intake\n Intake --> WaitingForApproval: valid snapshot and review bundle\n Intake --> Failed: source or media validation fails\n WaitingForApproval --> Rendering: approved bundle parses and validates\n WaitingForApproval --> Failed: rejected\n Rendering --> Packaged: voice, graphics, and render succeed\n Rendering --> Failed: required narration or artifact fails\n Packaged --> [*]\n```\n\n### Research That Shapes the Plan\n\n- AutoReel recommends 10-20 strong photos, exterior-to-interior sequencing, restrained pans/zooms, minimal text, and roughly 30-second output: https://www.autoreelapp.com/blog/how-to-make-real-estate-video-using-only-property-photos\n- Momenzo emphasizes guided capture, automatic editing, AI captions, branding, and real-estate templates: https://www.momenzo.com/\n- HeyGen offers a real-estate maker with Just Listed, Open House, and agent-intro templates; photo animation, voice cloning, avatars, captions, branding, and multilingual output are the relevant capabilities: https://www.heygen.com/en-gb/tool/real-estate-video-maker\n- HeyGen also positions interactive avatars for round-the-clock FAQ, sales, and follow-up conversations, which confirms a later lead-engagement track but does not belong in the listing-reel render path: https://www.heygen.com/interactive-avatar/\n- HyperFrames is an Apache-2.0 deterministic HTML/GSAP renderer with reusable social overlays and local FFmpeg output, but its installed workflows are general-purpose rather than real-estate-specific: https://github.com/heygen-com/hyperframes\n- Zillow prohibits automated queries and republishing listing images or data without explicit permission: https://www.zillow.com/corporate/terms-of-use/\n- Bridge provides licensed RESO Web API access after MLS approval: https://www.bridgeinteractive.com/developers/bridge-api/\n- Meta recommends Reel aspect ratios up to 9:16, at least 30 fps and 720 px, and a 420x654 cover ratio: https://www.facebook.com/help/1038071743007909/\n- ElevenLabs Professional Voice Clones must be created and verified by the voice owner, then privately shared: https://help.elevenlabs.io/hc/en-us/articles/36842751624209-Can-I-create-a-Professional-Voice-Clone-of-someone-else-s-voice\n\n---\n\n## Implementation Units\n\n### U1. Canonical listing snapshot and source policy\n\n- **Goal:** Validate listing identity, authorized facts, ordered local photos, cover selection, and source rights before workflow execution.\n- **Requirements:** R1-R4, R13; AE1, AE5.\n- **Dependencies:** None.\n- **Files:** `core/listings/__init__.py`, `core/listings/models.py`, `core/listings/manifest.py`, `tests/test_listing_manifest.py`.\n- **Approach:** Introduce typed immutable snapshot, photo, and agent-profile records; strict HTTPS URL normalization; media-root-confined path resolution; photo hashes; duplicate detection; rights attestation; and a source-policy check that rejects automated retrieval for prohibited domains.\n- **Execution note:** Implement validation test-first because this contract protects every downstream claim and asset.\n- **Patterns to follow:** Frozen dataclasses and explicit validation used in `core/workflows/config.py`; private media exclusions in `.gitignore` and `AGENTS.md`.\n- **Test scenarios:**\n 1. Load a valid manifest with relative photo paths and preserve approved order and source URL.\n 2. Reject URL mismatch, unsupported scheme, missing photos, duplicates, empty facts, invalid cover index, missing rights attestation, or no contact method in the separate agent profile.\n 3. Classify a Zillow URL as manifest/licensed-provider only and prove no fetch client is invoked.\n 4. Reject absolute, parent-traversal, and symlink-escape photo paths outside the configured media root.\n 5. Serialize the normalized snapshot with hashes and attribution without leaking contact fields or credentials.\n- **Verification:** A snapshot round-trip is deterministic and invalid manifests stop before a job reaches approval.\n\n### U2. Review bundle and approval parsing\n\n- **Goal:** Put every publish-visible fact and choice into one operator-editable artifact.\n- **Requirements:** R5, R6, R8, R13; F1, AE2.\n- **Dependencies:** U1.\n- **Files:** `core/listings/review.py`, `core/workflows/listing_reel_modules.py`, `tests/test_listing_review.py`, `tests/test_listing_reel_workflow.py`.\n- **Approach:** Draft a versioned JSON bundle with snapshot digest, narration, caption, photo order, cover index, and outro content. After the shared approval gate, parse the approved JSON, require the digest and asset set to match intake, and expose distinct approved narration/caption values.\n- **Execution note:** Start with the BDD scenario proving the workflow pauses before any paid or render step.\n- **Patterns to follow:** `WorkflowRunner` approval resume semantics and the existing Instagram caption builder.\n- **Test scenarios:**\n 1. Draft content uses only snapshot facts and produces a concise warm narration and caption.\n 2. Starting the workflow stops at approval with the review artifact and no voice/render/package outputs.\n 3. Approval resumes from edited narration/caption and preserves the approved photo set.\n 4. Reject malformed JSON, changed snapshot digest, injected photo paths, missing outro contact, and unsupported claims fields.\n- **Verification:** The approved bundle is the only source for downstream narration, caption, order, cover, and outro.\n\n### U3. Designed cover and contact outro graphics\n\n- **Goal:** Produce a compelling property cover and readable final contact card from approved content.\n- **Requirements:** R10, R11, R13; AE3.\n- **Dependencies:** U2.\n- **Files:** `core/media/listing_graphics.py`, `tests/test_listing_graphics.py`.\n- **Approach:** Use Pillow to crop approved photos around an optional focal point without distortion, apply a neutral high-contrast editorial treatment, center critical cover text within crop-safe bounds, and render an outro with agent name, CTA, and one or more contact methods. Export a Reel cover at 1:1.55 and a 9:16 outro scene; use no brokerage logo unless an authorized asset is supplied.\n- **Patterns to follow:** Pillow asset generation and font fallback in `core/media/caption_image.py`.\n- **Test scenarios:**\n 1. Render covers from landscape and portrait photos at exact dimensions with non-empty image data.\n 2. Honor center and explicit focal points while keeping title and key facts within the central safe region and wrapping long text without clipping.\n 3. Render a contact card with handle, phone, email, or website and reject a card with no contact destination.\n 4. Avoid displaying absent or unapproved listing fields.\n- **Verification:** Image inspection and pixel/dimension assertions confirm readable, non-blank outputs.\n\n### U4. Deterministic photo-reel renderer\n\n- **Goal:** Render approved photos, captions, narration, and outro into an Instagram-compatible moving reel.\n- **Requirements:** R9, R10, R12-R14; AE3.\n- **Dependencies:** U2, U3.\n- **Files:** `core/media/photo_reel.py`, `core/media/ffmpeg_utils.py`, `core/models.py`, `core/workflows/listing_reel_modules.py`, `tests/test_photo_reel.py`, `tests/test_media.py`.\n- **Approach:** Construct one FFmpeg filter graph with per-photo scale/crop and restrained zoom/pan, simple crossfades, caption overlays, a static outro scene, and narration audio. Calculate photo duration from total narration/outro duration and use fixed 30 fps output settings.\n- **Execution note:** Build command construction test-first, then run a real local render because filter-graph validity cannot be proven by string assertions.\n- **Patterns to follow:** Command builders and executable guard in `core/media/ffmpeg_utils.py`.\n- **Test scenarios:**\n 1. Build valid graphs for one photo, multiple photos, mixed orientations, captions, and outro.\n 2. Alternate motion direction without exceeding configured zoom bounds.\n 3. Distribute duration across the approved photo count and keep the outro within 4-5 seconds.\n 4. Reject zero photos, non-positive duration, changed photo hashes, missing narration, or unsupported output settings.\n 5. Render a real fixture and verify dimensions, frame rate, video/audio codecs, audio stream, duration, and changing frames.\n- **Verification:** The committed command tests pass and an ffprobe/visual artifact check confirms a playable moving 9:16 MP4.\n\n### U5. Strict cloned narration and package integration\n\n- **Goal:** Make continuous photo-reel narration audible and deliver the designed cover instead of a random frame grab.\n- **Requirements:** R7, R8, R11, R13; AE4.\n- **Dependencies:** U2-U4.\n- **Files:** `core/config.py`, `.env.example`, `cli/main.py`, `core/workflows/modules.py`, `core/publishing/instagram.py`, `tests/test_config_settings.py`, `tests/test_cli.py`, `tests/test_workflow_runner.py`, `tests/test_instagram_package.py`.\n- **Approach:** Add consent and voice-owner settings, support continuous ElevenLabs synthesis when no transcript segments exist, add strict required-audio behavior for listing reels, prefer approved narration/caption keys, prevent credentials from entering job artifacts, and package the generated cover and snapshot.\n- **Execution note:** Preserve current demo fallbacks for existing workflows; strict failure applies only when the listing workflow requests cloned narration.\n- **Patterns to follow:** Lazy provider construction in `cli/main.py` and opt-in provider contracts in `tests/test_live_integrations.py`.\n- **Test scenarios:**\n 1. Build the configured voice client only when provider, voice ID, API key, and consent are present.\n 2. Continuous ElevenLabs synthesis writes a probeable narration file for a listing script.\n 3. Provider errors and empty/unprobeable output fail a strict listing job without silent fallback.\n 4. Offline silent fixtures remain explicit and package metadata records the actual voice provider.\n 5. Instagram packaging copies the designed cover, approved caption, and snapshot.\n- **Verification:** Mocked provider tests prove contracts; an opt-in live test may validate Richard's privately shared voice without entering the default suite.\n\n### U6. End-to-end listing reel CLI and operator documentation\n\n- **Goal:** Expose and prove the complete concierge workflow through the local CLI.\n- **Requirements:** R1-R14; F1; AE1-AE5.\n- **Dependencies:** U1-U5.\n- **Files:** `workflows/listing_reel/config.yaml`, `cli/main.py`, `tests/test_cli.py`, `tests/test_listing_reel_workflow.py`, `tests/fixtures/listing_reel/manifest.json`, `README.md`, `docs/setup.md`, `docs/punch-list.md`, `docs/listing-reel-operator-guide.md`.\n- **Approach:** Add a dedicated `listing-reel` command with listing URL, manifest, media root, tenant, contact, TTS, and render flags; preserve status/approve/reject behavior; document source rights, voice consent, review, render, inspection, and manual posting.\n- **Execution note:** Finish with an actual approval-resume render using locally extracted property frames or synthetic committed fixtures, then inspect the generated artifacts rather than relying on unit tests alone.\n- **Patterns to follow:** Current `run`, `approve`, `status`, and manual Instagram handoff commands.\n- **Test scenarios:**\n 1. CLI forwards all listing, contact, voice, and render inputs without printing private content.\n 2. Full start pauses for approval and approval resumes through package completion.\n 3. Status and rejection work for the new workflow.\n 4. Invalid source rights, missing consent, or missing media return actionable errors before paid calls.\n 5. End-to-end output contains final video, cover, caption, snapshot, metadata, narration, captions, outro, and render command artifacts.\n- **Verification:** The offline suite is green and the operator guide's local fixture flow produces and validates the expected package.\n\n---\n\n## Verification Contract\n\n| Gate | Applies to | Done signal |\n|---|---|---|\n| `python3 -m pytest -q` | U1-U6 | Default offline suite passes without network or paid APIs. |\n| Focused listing workflow tests | U1-U6 | Validation, approval, strict voice, graphics, render commands, and packaging scenarios pass. |\n| Local approval-resume render | U3-U6 | A real fixture produces a playable 1080x1920 MP4 and complete publish package. |\n| ffprobe artifact inspection | U4-U6 | H.264 video, AAC audio, 30 fps, expected duration, and 9:16 dimensions are present. |\n| Visual/audio inspection | U3-U6 | Photos visibly move, captions change, narration is audible or explicitly synthetic, outro is readable, cover is compelling, and no source audio leaks. |\n| Opt-in live provider check | U5 | When explicitly enabled, the privately shared Richard voice produces audible speech and the artifact is not committed. |\n\n---\n\n## Definition of Done\n\n- A listing URL plus authorized local manifest can run from CLI intake through approval to a complete Instagram handoff package.\n- The example Zillow URL is accepted as source identity without any automated Zillow request.\n- Every publish-visible fact, script line, photo choice, cover, and contact method is approved before rendering.\n- The final video has real photo motion, captions, configured narration, and a readable contact outro.\n- The custom cover is designed from an approved property photo and included in the package.\n- Strict cloned-voice failures never masquerade as successful silent narration.\n- Offline and BDD tests pass, a real local render is inspected, and live provider calls remain guarded.\n- Documentation and `docs/punch-list.md` reflect the implemented and still-deferred work.\n- Raw media, client data, provider outputs, credentials, and abandoned implementation experiments are absent from git.\n","numLines":305,"startLine":1,"totalLines":305}},"sourceToolAssistantUUID":"3b850cf5-70a0-4d2f-853b-70a7133d041c","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/extra/projects/stagehand","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
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{"parentUuid":"2a3915bb-e2f6-4b4f-9bc5-69c84f59b99a","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcpoJwioM2gNv3fm1nq93","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Now I have a clear picture. Let me summarize what I found:\n\n1. The competitor research was done and is referenced in the plan (section \"Research That Shapes the Plan\") - it names AutoReel, Momenzo, HeyGen, HyperFrames as competitors, with their Instagram-relevant capabilities documented.\n\n2. The research was baked INTO the plan (2026-07-07-001-feat-listing-url-reel-plan.md) rather than as a separate competitor analysis doc. The key section is \"Research That Shapes the Plan\" starting at line 164.\n3. The entire listing-reel workflow was fully implemented—all the punch list items for that feature are checked off. The Discovery section still has open work though: gathering walkthrough videos from the first real estate agent, collecting publishable post examples, confirming pricing and turnaround times, documenting compliance preferences, and establishing acceptance criteria.\n\nSo the competitor links James shared became research sources that fed directly into the plan document, and the feature itself is already built out.\n\nThe remaining blocker is finding that initial real estate agent to pilot with. I should send James a clear summary of where things stand.","signature":"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"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":7391,"cache_read_input_tokens":37640,"output_tokens":769,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":7391,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":769,"cache_read_input_tokens":37640,"cache_creation_input_tokens":7391,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":7391},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcpoJvdp124FCb8vUrnk1","type":"assistant","uuid":"23e300b3-ef5f-4664-976d-eb70f65a136c","timestamp":"2026-07-08T15:07:33.653Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/extra/projects/stagehand","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"23e300b3-ef5f-4664-976d-eb70f65a136c","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcpoJwioM2gNv3fm1nq93","type":"message","role":"assistant","content":[{"type":"text","text":"\nFound it. The competitor research was completed — the coding agent folded it directly into the implementation plan rather than a standalone competitive analysis doc. Here's what happened and where things stand:\n\n**What the agent built from those links:**\n`docs/plans/2026-07-07-001-feat-listing-url-reel-plan.md` — a full implementation-ready plan. The \"Research That Shapes the Plan\" section (line 164) is where your Instagram competitor links landed:\n- **AutoReel** → 10-20 photos, exterior-to-interior sequencing, ~30s output\n- **Momenzo** → guided capture, AI captions, real-estate templates\n- **HeyGen** → Just Listed/Open House templates, voice cloning, avatars (deferred as optional, not foundational)\n- **HyperFrames** → deterministic HTML/GSAP renderer (deferred until FFmpeg slice is proven)\n\n**What's already done:**\nAll Listing URL Reel punch list items are checked. The workflow was fully built: CLI intake → listing snapshot → approval gate → narration → captions → photo reel renderer → Instagram handoff package.\n\n**What's still open (the actual next actions):**\nThe Discovery section of the punch list is where you're blocked:\n- [ ] Collect 5–8 raw walkthrough videos from the first real estate agent\n- [ ] Collect examples of posts the agent considers publishable\n- [ ] Confirm turnaround time, revision expectations, pricing signal\n- [ ] Capture compliance/brokerage disclaimer preferences\n- [ ] Define acceptance criteria from the discovery conversation\n\nSo the follow-up on the competitor links is done — the real blocker is finding and onboarding your first pilot real estate agent. That's the step that unlocks everything.\n"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":7391,"cache_read_input_tokens":37640,"output_tokens":769,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":7391,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":769,"cache_read_input_tokens":37640,"cache_creation_input_tokens":7391,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":7391},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcpoJvdp124FCb8vUrnk1","type":"assistant","uuid":"c72e31ba-db85-484f-8659-0e5365c0612b","timestamp":"2026-07-08T15:07:36.196Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/extra/projects/stagehand","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"type":"queue-operation","operation":"enqueue","timestamp":"2026-07-08T15:24:47.593Z","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","content":"\nWe already have a agent to work with, Richard Fowler, I would like to have something to show him that can be:the walk through video I did that uses his cloned voice and good thumbnail and outro slide contact cardsome demo content built from pictures of different listings using techniques that we've seen other solutions offer. So if these other tools have 3 or so different templates maybe we make 3 different instagram ready videos for 3 different houses on the market now or recently, maybe better yet some of his actual listings, using each of these templates. @U0BFL0HCL20"}
{"type":"queue-operation","operation":"dequeue","timestamp":"2026-07-08T15:24:47.593Z","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}
{"parentUuid":"c72e31ba-db85-484f-8659-0e5365c0612b","isSidechain":false,"promptId":"674253e9-f943-40e3-b94f-99e2ed034599","type":"user","message":{"role":"user","content":"\nWe already have a agent to work with, Richard Fowler, I would like to have something to show him that can be:the walk through video I did that uses his cloned voice and good thumbnail and outro slide contact cardsome demo content built from pictures of different listings using techniques that we've seen other solutions offer. So if these other tools have 3 or so different templates maybe we make 3 different instagram ready videos for 3 different houses on the market now or recently, maybe better yet some of his actual listings, using each of these templates. @U0BFL0HCL20"},"uuid":"3802e13c-6470-47bb-a8e4-c725c30d192c","timestamp":"2026-07-08T15:24:47.610Z","permissionMode":"bypassPermissions","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"3802e13c-6470-47bb-a8e4-c725c30d192c","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcppebXYC2BCXRoQwwyMA","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"James wants to prepare a demo package to show Richard Fowler. There are two parts:\n\n1. **The walkthrough video** - using his cloned voice, good thumbnail, outro slide/contact card\n2. **Demo content** - 3 different Instagram-ready videos from 3 different listings (ideally Richard's actual listings), each using a different template style (inspired by the competitors: AutoReel, Momenzo, HeyGen-style)\n\nLet me think about what I need to know to help plan this:\n\n1. For Richard's cloned voice - the voice cloning setup (ElevenLabs, consent already established?)\n2. For Richard's actual listings - I need to find his listings since he's a realtor\n3. For the templates - I need to define 3 distinct template styles based on competitor research\n\nI should check the existing codebase to understand what's already built, specifically the listing reel workflow, current template styles, voice cloning setup, and Instagram publishing requirements. I'll also look at what we know about Richard from the people directory.\n\nBefore diving into implementation, I should either ask James some clarifying questions about key details like whether Richard's voice is already configured in ElevenLabs and where his listing photos are stored, or I can map out a clear plan and identify what information I'm missing.","signature":"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"}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":950,"cache_read_input_tokens":45031,"output_tokens":616,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":950,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":616,"cache_read_input_tokens":45031,"cache_creation_input_tokens":950,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":950},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcppeYtHvXK34LQLJL8RX","type":"assistant","uuid":"a8d8ad5e-a85e-4084-a39f-4a97a74fe061","timestamp":"2026-07-08T15:25:02.656Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"a8d8ad5e-a85e-4084-a39f-4a97a74fe061","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcppebXYC2BCXRoQwwyMA","type":"message","role":"assistant","content":[{"type":"text","text":"Let me read the relevant StageHand docs to understand the current state before mapping out a demo plan."}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":950,"cache_read_input_tokens":45031,"output_tokens":616,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":950,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":616,"cache_read_input_tokens":45031,"cache_creation_input_tokens":950,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":950},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcppeYtHvXK34LQLJL8RX","type":"assistant","uuid":"edf59476-ef0a-4a3d-87ef-eee0a59acce2","timestamp":"2026-07-08T15:25:02.706Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"edf59476-ef0a-4a3d-87ef-eee0a59acce2","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcppebXYC2BCXRoQwwyMA","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_011E8X4K51htJAXME5yAmd2A","name":"Bash","input":{"command":"cat /workspace/extra/projects/stagehand/docs/voice-cloning-guide.md && echo \"===\" && cat /workspace/extra/projects/stagehand/docs/listing-reel-operator-guide.md"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":950,"cache_read_input_tokens":45031,"output_tokens":616,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":950,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":616,"cache_read_input_tokens":45031,"cache_creation_input_tokens":950,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":950},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcppeYtHvXK34LQLJL8RX","type":"assistant","uuid":"40f76516-258a-4ca7-ad6f-b83a5b7c5331","timestamp":"2026-07-08T15:25:02.772Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"40f76516-258a-4ca7-ad6f-b83a5b7c5331","isSidechain":false,"promptId":"674253e9-f943-40e3-b94f-99e2ed034599","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_011E8X4K51htJAXME5yAmd2A","type":"tool_result","content":"# Voice Cloning Guide\n\nHow to capture and clone a voice for use in the narration pipeline. Covers both self-cloning and cloning an agent's voice from existing source material.\n\n---\n\n## Options Overview\n\n| Tool | Type | Min Audio | Quality | Apple Silicon | Cost |\n|------|------|-----------|---------|---------------|------|\n| **ElevenLabs Instant** | Cloud API | 1–2 min | Good | N/A | Paid (per character) |\n| **ElevenLabs Professional** | Cloud API | 30 min–3 hrs | Best | N/A | Paid (training + usage) |\n| **Coqui XTTS-v2** | Local / self-hosted | 6–30 sec | Good | MPS (4× faster than CPU) | Free (CPML license) |\n| **F5-TTS** | Local / self-hosted | ~6 sec | Good for long-form | CPU-only, slow | Free (MIT) |\n| **OpenVoice V2** | Local / self-hosted | Pre-registered | Fast inference | CPU viable (3–5× RT) | Free (MIT) |\n\n**Recommendation for this pipeline**: For another person's production voice, use an ElevenLabs Professional Voice Clone created and verified by the voice owner, then privately shared with the operator account. Instant cloning is appropriate only when the operator is cloning their own voice under the provider's rules. If you want a fully local/private research path, use Coqui XTTS-v2 only with explicit recorded consent.\n\n---\n\n## Part 1: Cloning Your Own Voice\n\n### Step 1 — Record reference audio\n\n**ElevenLabs (quickest):**\n- Record 1–2 minutes of clean, natural speech. Avoid going over 3 minutes — it yields little improvement and can hurt the clone.\n- Speak in a conversational tone at your normal pace, including some variety (statements, questions, pauses).\n- Record in a quiet room with no background music, AC hum, or echo. A closet full of clothes is a surprisingly good impromptu booth.\n- Use a decent USB mic or even a modern iPhone held 6–8 inches away. Avoid speakerphone or laptop mics.\n- Export as MP3 at 192kbps+ or WAV 44.1kHz/16-bit.\n\n**For higher quality (ElevenLabs Professional or XTTS-v2):**\n- 30+ minutes of varied speech content gives noticeably more natural results.\n- Good sources to record from: read a few pages of a book aloud, narrate a property walkthrough as if showing a real listing, describe your neighborhood, tell a personal story.\n- Avoid reading in a stiff \"reading voice\" — the clone will sound robotic if the source material does.\n\n### Step 2 — Clean the audio\n\nRun through Audacity or ffmpeg before uploading:\n- Remove silence at the start/end\n- Normalize to -1 dBFS peak\n- No need for heavy noise reduction if it was recorded cleanly; over-processing hurts the clone\n\n```bash\nffmpeg -i raw_voice.wav -af \"silenceremove=start_periods=1:start_silence=0.5:start_threshold=-50dB,loudnorm=I=-16:TP=-1:LRA=11\" voice_clean.wav\n```\n\n### Step 3 — Create the clone\n\n**ElevenLabs (cloud):**\n1. Go to elevenlabs.io → Voices → Add Voice → Instant Voice Clone\n2. Upload your cleaned audio file(s)\n3. Name the voice (e.g., \"James - Natural\")\n4. Test with a short sample before saving\n5. Copy the Voice ID — you'll use this in the pipeline\n\n**Coqui XTTS-v2 (local):**\n\nRun the local Docker smoke test:\n\n```bash\nCOQUI_ACCEPT_CPML=1 ./scripts/coqui_clone_test.sh\n```\n\nThis uses `input/voice_samples/richard_fowler_voice_45s_75s.wav` by default and writes `output/voice-clone-local/xtts_clone_test.wav`. The script mounts `output/voice-clone-local/coqui-cache` as the Coqui model cache so the XTTS-v2 download and license acceptance persist across runs.\n\nOverride inputs without editing the script:\n\n```bash\nCOQUI_ACCEPT_CPML=1 \\\nCOQUI_REFERENCE_WAV=input/voice_samples/richard_fowler_voice_45s_75s.wav \\\nCOQUI_CLONE_TEXT=\"Welcome inside this Cedar Park walkthrough.\" \\\nCOQUI_CLONE_OUTPUT=output/voice-clone-local/custom_test.wav \\\n./scripts/coqui_clone_test.sh\n```\n\n```bash\npip install coqui-tts # requires Python 3.9 or 3.10\n```\n\n```python\nfrom TTS.api import TTS\n\n# Load model (downloads ~1.8GB on first run)\ntts = TTS(\"tts_models/multilingual/multi-dataset/xtts_v2\")\n\n# On Apple Silicon, use MPS for ~4× speedup vs CPU\ntts = tts.to(\"mps\") # or \"cuda\" on Nvidia, \"cpu\" as fallback\n\n# Generate speech in the cloned voice\ntts.tts_to_file(\n text=\"Welcome inside. This four-bedroom home sits on a quiet cul-de-sac.\",\n speaker_wav=\"voice_clean.wav\", # your reference audio\n language=\"en\",\n file_path=\"output.wav\",\n)\n```\n\n### Step 4 — Wire into the stagehand pipeline (ElevenLabs)\n\nElevenLabs is fully wired in. Add your credentials to `.env`:\n\n```bash\nELEVENLABS_API_KEY=sk_...\nDEFAULT_VOICE_ID=\nVOICE_CLONE_CONSENT_CONFIRMED=true\nVOICE_CLONE_OWNER=\"Voice Owner Name\"\n```\n\nThen run any job with `--tts-provider elevenlabs`:\n\n```bash\npython -m cli.main run video_narration \\\n --input input/IMG_2157.MOV \\\n --transcription-provider local-whisper \\\n --tts-provider elevenlabs \\\n --render\n```\n\nOverride the voice for a specific run (useful when comparing clones):\n\n```bash\npython -m cli.main run video_narration \\\n --input input/walkthrough.mov \\\n --transcription-provider local-whisper \\\n --tts-provider elevenlabs \\\n --voice-id \\\n --render\n```\n\nThe pipeline generates one ElevenLabs API call per sentence group (matching original video timestamps), assembles the clips with ffmpeg, and renders the final video identically to the `say` path. Model defaults to `eleven_turbo_v2_5` for fast turnaround; change it by modifying `ElevenLabsVoiceClient(model_id=...)` in `core/integrations/elevenlabs_voice.py` if you want `eleven_multilingual_v2` for higher quality.\n\n**Integration surface** (for adding other providers):\n- `core/integrations/elevenlabs_voice.py` — the client; implement `synthesize_to_file(text, path)`\n- `core/workflows/modules.py:_resolve_tts_fn()` — dispatch by provider name\n- `cli/main.py:_build_elevenlabs_client()` — CLI construction pattern to follow\n\n---\n\n## Part 2: Richard Fowler's Voice — Consent and Provider Setup\n\n**Richard Fowler** is the target agent — a fifth-generation Texan, Cedar Park-based REALTOR® with Compass, principal of the ARK Property Team with partner Donna Ciccarelli.\n\n### Source material — status\n\nA local research sample exists under ignored `input/` storage. It must not be uploaded to create an ElevenLabs clone on Richard's behalf. ElevenLabs requires a Professional Voice Clone to be created and verified by the voice owner; Richard must complete that process and privately share the resulting voice with the operator account.\n\nLocal sample paths, if retained for an explicitly consented local evaluation, are:\n\n```\ninput/voice_samples/richard_fowler_voice.wav\n```\n\nExtracted from YouTube (8:30–11:20 segment of continuous speech), converted to mono WAV 44.1kHz, normalized to -16 LUFS. Ready for immediate upload to ElevenLabs or use as XTTS-v2 reference audio.\n\nThe full 2m50s file includes another speaker. For local XTTS-v2 voice cloning, prefer the single-speaker Richard-only section from 45s to 1:15:\n\n```\ninput/voice_samples/richard_fowler_voice_45s_75s.wav\n```\n\nThat clip is 30 seconds, mono WAV 44.1kHz, lightly silence-trimmed and normalized. It produced the current cleaner local clone test:\n\n```\noutput/voice-clone-local/xtts_clone_test_45s_75s.wav\n```\n\n**To use Richard's voice with ElevenLabs:**\n\n1. Obtain and record Richard's consent for this workflow and intended publishing use.\n2. Richard creates and verifies his Professional Voice Clone in his ElevenLabs account.\n3. Richard privately shares that verified voice with the operator's ElevenLabs account.\n4. Copy the shared Voice ID to `DEFAULT_VOICE_ID` and set the consent/owner environment fields shown above.\n5. Run an opt-in test and have Richard approve the output before production publishing.\n\n**Digital presence found:**\n\n| Platform | Handle / URL | Content |\n|----------|-------------|---------|\n| Website | richardfowlerrealtor.com | Bio, listings |\n| Facebook | facebook.com/RichardFowlerRealtor | Page exists |\n| Instagram | instagram.com/richardfowlerrealtor | Profile exists |\n| LinkedIn | linkedin.com/in/richardfowler | Professional profile |\n| YouTube | Not found | No channel |\n| Podcast | Not found | No show |\n\n**If you want a higher-quality clone (30+ minutes):**\n- Ask Richard to record directly — Voice Memo in a quiet room, 5–10 minutes of natural conversation about Cedar Park or a recent listing is enough.\n- Check Facebook/Instagram manually for video reels — even 60-second clips in good conditions add up.\n\n### Voice and tone profile (from client reviews)\n\nSince no audio/video was found, this profile is constructed from 20 five-star Google reviews and his professional bio. Use it to inform how a cloned voice should be directed or prompted:\n\n**Communication style:**\n- Warm and conversational, not salesy — clients specifically note he doesn't pressure them\n- Patient and thorough — walks through every step of a transaction in plain language\n- Genuine empathy — his son's autism diagnosis is part of his public story, and clients describe him as someone who \"really cares about people\"\n- Direct and confident when negotiating — holds the Seller Representative Specialist and Master Certified Negotiation Expert certifications\n\n**Delivery characteristics (inferred):**\n- Texas accent, likely mild Central Texas — not a strong drawl, Austin-area speech tends to be flatter\n- Measured pace — detail-oriented people who explain every step tend to speak at a comfortable mid-pace, not rapid-fire\n- Warm tone in walkthroughs — the input video (IMG_2157.MOV) confirms a relaxed, natural delivery with natural pauses\n\n**Phrases and vocabulary from the walkthrough transcript (actual voice data):**\n- \"here today we have\" — natural opener, not scripted-sounding\n- Uses \"we\" a lot rather than \"you\" — inclusive phrasing\n- Specific and factual: \"four bedroom, two and a half bath,\" \"half bath and a closet,\" \"two car garage\"\n- Casual connectives: \"and so,\" \"right along,\" \"you don't really\"\n- Closes warmly: \"Thank you\" (genuinely, not performatively)\n\n**TTS direction notes** (if manually recording reference material or directing a session):\n- Aim for a calm, conversational read — imagine showing a close friend's family the home, not pitching to a stranger\n- Vary sentence length: mix short punchy observations (\"Pool, tree house for the kids.\") with longer descriptive ones\n- Don't over-enunciate — the natural mouth sounds and Texas vowels are part of the voice signature\n\n---\n\n## Quality Checklist Before Cloning\n\n- [ ] Audio is single-speaker only (no background voices, TV, music)\n- [ ] No reverb or room echo\n- [ ] No clipping (peaks below -1 dBFS)\n- [ ] Minimum 6 seconds (XTTS-v2) or 60 seconds (ElevenLabs Instant)\n- [ ] Normalized and trimmed silence\n- [ ] Sample rate: 22050 Hz (acceptable) or 44100 Hz (preferred)\n- [ ] Format: WAV 16-bit or MP3 192kbps+\n\n---\n\n## Sources\n\n- [ElevenLabs Voice Cloning overview](https://elevenlabs.io/docs/creative-platform/voices/voice-cloning)\n- [ElevenLabs Instant Voice Clone requirements](https://elevenlabs.io/docs/creative-platform/voices/voice-cloning/instant-voice-cloning)\n- [ElevenLabs Professional Voice Clone requirements](https://elevenlabs.io/docs/eleven-creative/voices/voice-cloning/professional-voice-cloning)\n- [Coqui XTTS-v2 tutorial — Local AI Master](https://localaimaster.com/models/coqui-tts)\n- [Self-host XTTS-2, F5-TTS, OpenVoice V2 — Spheron](https://www.spheron.network/blog/self-host-voice-cloning-gpu-cloud-xtts-f5-tts-openvoice-v2/)\n- [Richard Fowler — richardfowlerrealtor.com](https://richardfowlerrealtor.com/)\n- [Richard Fowler — client reviews](https://www.experience.com/reviews/richard-6457194)\n- [ARK Property Team — Compass](https://www.compass.com/agents/ark-property-team/)\n===\n# Listing Reel Operator Guide\n\nThe listing reel workflow turns an authorized local listing manifest and photos into a reviewed vertical video package. The public URL identifies the property; the workflow does not scrape Zillow, Realtor.com, Redfin, or other listing sites.\n\n## 1. Prepare authorized inputs\n\nKeep real manifests and photos under `input/` or another ignored local directory. Confirm that the listing agent, broker, photographer, or licensed feed permits the intended social-media use.\n\nCreate a JSON manifest:\n\n```json\n{\n \"version\": 1,\n \"source_url\": \"https://www.zillow.com/homedetails/example/1_zpid/\",\n \"rights_confirmed\": true,\n \"attribution\": \"Listing agent supplied media for social promotion.\",\n \"address\": \"123 Example Street\",\n \"city\": \"Austin\",\n \"state\": \"TX\",\n \"postal_code\": \"78701\",\n \"price\": 625000,\n \"beds\": 4,\n \"baths\": 3,\n \"square_feet\": 2410,\n \"description\": \"Approved factual listing description.\",\n \"photos\": [\n {\"path\": \"photos/front.jpg\", \"label\": \"Exterior\", \"focal_point\": [0.5, 0.5]},\n {\"path\": \"photos/living.jpg\", \"label\": \"Living room\", \"focal_point\": [0.55, 0.45]}\n ],\n \"cover_photo_index\": 0\n}\n```\n\nPhoto paths must be relative to `--media-root`, cannot escape it through `..` or symlinks, and must point to JPEG, PNG, WebP, or PPM files. The intake step records each file's size and SHA-256 hash; the renderer checks those values again after approval.\n\n## 2. Configure the agent and voice\n\nSet public contact fields and provider configuration in `.env`:\n\n```bash\nAGENT_NAME=\"Agent Name\"\nAGENT_INSTAGRAM_HANDLE=\"@agenthandle\"\nAGENT_WEBSITE=\"https://example.com\"\n\nELEVENLABS_API_KEY=\"...\"\nDEFAULT_VOICE_ID=\"...\"\nVOICE_CLONE_CONSENT_CONFIRMED=true\nVOICE_CLONE_OWNER=\"Agent Name\"\n```\n\nFor a person-specific ElevenLabs voice, the voice owner must create and verify the Professional Voice Clone and privately share it with the account running this workflow. Do not upload third-party recordings to create a clone on the person's behalf.\n\n## 3. Start and review\n\n```bash\npython3 -m cli.main listing-reel \\\n --url \"https://www.zillow.com/homedetails/example/1_zpid/\" \\\n --manifest input/listing/listing.json \\\n --media-root input/listing \\\n --tenant agent-name\n```\n\nThe command stops at one JSON approval artifact before voice synthesis or rendering. Review and edit:\n\n- sourced facts and attribution;\n- narration and Instagram caption;\n- photo order and cover choice;\n- public contact outro;\n- target duration.\n\nDo not add claims that the manifest does not support, especially claims about schools, safety, demographics, financing, appreciation, or protected classes.\n\nResume with the same artifact:\n\n```bash\npython3 -m cli.main approve JOB_ID \\\n --script output/JOB_ID/approved_listing_reel.json \\\n --approved-by operator-name\n```\n\nThe resume command reloads the original provider and voice settings. Requested ElevenLabs narration fails closed if credentials, voice ownership/consent, synthesis, or audible output validation fails.\n\nIf a provider or render step fails after approval, the job is saved as failed. Correct the provider/configuration issue and retry the failed step without repeating approval:\n\n```bash\npython3 -m cli.main resume JOB_ID\n```\n\n## 4. Inspect the handoff\n\nThe completed job contains `output/JOB_ID/publish/` with:\n\n- `final_video.mp4` — 1080x1920 H.264/AAC reel at 30 fps;\n- `cover.jpg` or `cover.png` — dedicated 1:1.55 Instagram cover;\n- `caption.txt` — approved caption;\n- `listing_snapshot.json` — the source and media-integrity record;\n- `metadata.json` — tenant, handle, dimensions, duration, and package filenames.\n\nBefore delivery, watch the entire MP4 and verify visible photo motion, accurate changing captions, audible correct narration, readable safe-zone text, the final contact card, and no unauthorized or substituted media. Posting remains manual.\n\nFor an offline renderer check, pass `--tts-provider say` on macOS or `--tts-provider silent` only when silence is intentional test data. Silent mode is not acceptable for a production deliverable.","is_error":false}]},"uuid":"291c1b09-5c70-4eeb-91fe-e0d02efcf571","timestamp":"2026-07-08T15:25:02.805Z","toolUseResult":{"stdout":"# Voice Cloning Guide\n\nHow to capture and clone a voice for use in the narration pipeline. Covers both self-cloning and cloning an agent's voice from existing source material.\n\n---\n\n## Options Overview\n\n| Tool | Type | Min Audio | Quality | Apple Silicon | Cost |\n|------|------|-----------|---------|---------------|------|\n| **ElevenLabs Instant** | Cloud API | 1–2 min | Good | N/A | Paid (per character) |\n| **ElevenLabs Professional** | Cloud API | 30 min–3 hrs | Best | N/A | Paid (training + usage) |\n| **Coqui XTTS-v2** | Local / self-hosted | 6–30 sec | Good | MPS (4× faster than CPU) | Free (CPML license) |\n| **F5-TTS** | Local / self-hosted | ~6 sec | Good for long-form | CPU-only, slow | Free (MIT) |\n| **OpenVoice V2** | Local / self-hosted | Pre-registered | Fast inference | CPU viable (3–5× RT) | Free (MIT) |\n\n**Recommendation for this pipeline**: For another person's production voice, use an ElevenLabs Professional Voice Clone created and verified by the voice owner, then privately shared with the operator account. Instant cloning is appropriate only when the operator is cloning their own voice under the provider's rules. If you want a fully local/private research path, use Coqui XTTS-v2 only with explicit recorded consent.\n\n---\n\n## Part 1: Cloning Your Own Voice\n\n### Step 1 — Record reference audio\n\n**ElevenLabs (quickest):**\n- Record 1–2 minutes of clean, natural speech. Avoid going over 3 minutes — it yields little improvement and can hurt the clone.\n- Speak in a conversational tone at your normal pace, including some variety (statements, questions, pauses).\n- Record in a quiet room with no background music, AC hum, or echo. A closet full of clothes is a surprisingly good impromptu booth.\n- Use a decent USB mic or even a modern iPhone held 6–8 inches away. Avoid speakerphone or laptop mics.\n- Export as MP3 at 192kbps+ or WAV 44.1kHz/16-bit.\n\n**For higher quality (ElevenLabs Professional or XTTS-v2):**\n- 30+ minutes of varied speech content gives noticeably more natural results.\n- Good sources to record from: read a few pages of a book aloud, narrate a property walkthrough as if showing a real listing, describe your neighborhood, tell a personal story.\n- Avoid reading in a stiff \"reading voice\" — the clone will sound robotic if the source material does.\n\n### Step 2 — Clean the audio\n\nRun through Audacity or ffmpeg before uploading:\n- Remove silence at the start/end\n- Normalize to -1 dBFS peak\n- No need for heavy noise reduction if it was recorded cleanly; over-processing hurts the clone\n\n```bash\nffmpeg -i raw_voice.wav -af \"silenceremove=start_periods=1:start_silence=0.5:start_threshold=-50dB,loudnorm=I=-16:TP=-1:LRA=11\" voice_clean.wav\n```\n\n### Step 3 — Create the clone\n\n**ElevenLabs (cloud):**\n1. Go to elevenlabs.io → Voices → Add Voice → Instant Voice Clone\n2. Upload your cleaned audio file(s)\n3. Name the voice (e.g., \"James - Natural\")\n4. Test with a short sample before saving\n5. Copy the Voice ID — you'll use this in the pipeline\n\n**Coqui XTTS-v2 (local):**\n\nRun the local Docker smoke test:\n\n```bash\nCOQUI_ACCEPT_CPML=1 ./scripts/coqui_clone_test.sh\n```\n\nThis uses `input/voice_samples/richard_fowler_voice_45s_75s.wav` by default and writes `output/voice-clone-local/xtts_clone_test.wav`. The script mounts `output/voice-clone-local/coqui-cache` as the Coqui model cache so the XTTS-v2 download and license acceptance persist across runs.\n\nOverride inputs without editing the script:\n\n```bash\nCOQUI_ACCEPT_CPML=1 \\\nCOQUI_REFERENCE_WAV=input/voice_samples/richard_fowler_voice_45s_75s.wav \\\nCOQUI_CLONE_TEXT=\"Welcome inside this Cedar Park walkthrough.\" \\\nCOQUI_CLONE_OUTPUT=output/voice-clone-local/custom_test.wav \\\n./scripts/coqui_clone_test.sh\n```\n\n```bash\npip install coqui-tts # requires Python 3.9 or 3.10\n```\n\n```python\nfrom TTS.api import TTS\n\n# Load model (downloads ~1.8GB on first run)\ntts = TTS(\"tts_models/multilingual/multi-dataset/xtts_v2\")\n\n# On Apple Silicon, use MPS for ~4× speedup vs CPU\ntts = tts.to(\"mps\") # or \"cuda\" on Nvidia, \"cpu\" as fallback\n\n# Generate speech in the cloned voice\ntts.tts_to_file(\n text=\"Welcome inside. This four-bedroom home sits on a quiet cul-de-sac.\",\n speaker_wav=\"voice_clean.wav\", # your reference audio\n language=\"en\",\n file_path=\"output.wav\",\n)\n```\n\n### Step 4 — Wire into the stagehand pipeline (ElevenLabs)\n\nElevenLabs is fully wired in. Add your credentials to `.env`:\n\n```bash\nELEVENLABS_API_KEY=sk_...\nDEFAULT_VOICE_ID=\nVOICE_CLONE_CONSENT_CONFIRMED=true\nVOICE_CLONE_OWNER=\"Voice Owner Name\"\n```\n\nThen run any job with `--tts-provider elevenlabs`:\n\n```bash\npython -m cli.main run video_narration \\\n --input input/IMG_2157.MOV \\\n --transcription-provider local-whisper \\\n --tts-provider elevenlabs \\\n --render\n```\n\nOverride the voice for a specific run (useful when comparing clones):\n\n```bash\npython -m cli.main run video_narration \\\n --input input/walkthrough.mov \\\n --transcription-provider local-whisper \\\n --tts-provider elevenlabs \\\n --voice-id \\\n --render\n```\n\nThe pipeline generates one ElevenLabs API call per sentence group (matching original video timestamps), assembles the clips with ffmpeg, and renders the final video identically to the `say` path. Model defaults to `eleven_turbo_v2_5` for fast turnaround; change it by modifying `ElevenLabsVoiceClient(model_id=...)` in `core/integrations/elevenlabs_voice.py` if you want `eleven_multilingual_v2` for higher quality.\n\n**Integration surface** (for adding other providers):\n- `core/integrations/elevenlabs_voice.py` — the client; implement `synthesize_to_file(text, path)`\n- `core/workflows/modules.py:_resolve_tts_fn()` — dispatch by provider name\n- `cli/main.py:_build_elevenlabs_client()` — CLI construction pattern to follow\n\n---\n\n## Part 2: Richard Fowler's Voice — Consent and Provider Setup\n\n**Richard Fowler** is the target agent — a fifth-generation Texan, Cedar Park-based REALTOR® with Compass, principal of the ARK Property Team with partner Donna Ciccarelli.\n\n### Source material — status\n\nA local research sample exists under ignored `input/` storage. It must not be uploaded to create an ElevenLabs clone on Richard's behalf. ElevenLabs requires a Professional Voice Clone to be created and verified by the voice owner; Richard must complete that process and privately share the resulting voice with the operator account.\n\nLocal sample paths, if retained for an explicitly consented local evaluation, are:\n\n```\ninput/voice_samples/richard_fowler_voice.wav\n```\n\nExtracted from YouTube (8:30–11:20 segment of continuous speech), converted to mono WAV 44.1kHz, normalized to -16 LUFS. Ready for immediate upload to ElevenLabs or use as XTTS-v2 reference audio.\n\nThe full 2m50s file includes another speaker. For local XTTS-v2 voice cloning, prefer the single-speaker Richard-only section from 45s to 1:15:\n\n```\ninput/voice_samples/richard_fowler_voice_45s_75s.wav\n```\n\nThat clip is 30 seconds, mono WAV 44.1kHz, lightly silence-trimmed and normalized. It produced the current cleaner local clone test:\n\n```\noutput/voice-clone-local/xtts_clone_test_45s_75s.wav\n```\n\n**To use Richard's voice with ElevenLabs:**\n\n1. Obtain and record Richard's consent for this workflow and intended publishing use.\n2. Richard creates and verifies his Professional Voice Clone in his ElevenLabs account.\n3. Richard privately shares that verified voice with the operator's ElevenLabs account.\n4. Copy the shared Voice ID to `DEFAULT_VOICE_ID` and set the consent/owner environment fields shown above.\n5. Run an opt-in test and have Richard approve the output before production publishing.\n\n**Digital presence found:**\n\n| Platform | Handle / URL | Content |\n|----------|-------------|---------|\n| Website | richardfowlerrealtor.com | Bio, listings |\n| Facebook | facebook.com/RichardFowlerRealtor | Page exists |\n| Instagram | instagram.com/richardfowlerrealtor | Profile exists |\n| LinkedIn | linkedin.com/in/richardfowler | Professional profile |\n| YouTube | Not found | No channel |\n| Podcast | Not found | No show |\n\n**If you want a higher-quality clone (30+ minutes):**\n- Ask Richard to record directly — Voice Memo in a quiet room, 5–10 minutes of natural conversation about Cedar Park or a recent listing is enough.\n- Check Facebook/Instagram manually for video reels — even 60-second clips in good conditions add up.\n\n### Voice and tone profile (from client reviews)\n\nSince no audio/video was found, this profile is constructed from 20 five-star Google reviews and his professional bio. Use it to inform how a cloned voice should be directed or prompted:\n\n**Communication style:**\n- Warm and conversational, not salesy — clients specifically note he doesn't pressure them\n- Patient and thorough — walks through every step of a transaction in plain language\n- Genuine empathy — his son's autism diagnosis is part of his public story, and clients describe him as someone who \"really cares about people\"\n- Direct and confident when negotiating — holds the Seller Representative Specialist and Master Certified Negotiation Expert certifications\n\n**Delivery characteristics (inferred):**\n- Texas accent, likely mild Central Texas — not a strong drawl, Austin-area speech tends to be flatter\n- Measured pace — detail-oriented people who explain every step tend to speak at a comfortable mid-pace, not rapid-fire\n- Warm tone in walkthroughs — the input video (IMG_2157.MOV) confirms a relaxed, natural delivery with natural pauses\n\n**Phrases and vocabulary from the walkthrough transcript (actual voice data):**\n- \"here today we have\" — natural opener, not scripted-sounding\n- Uses \"we\" a lot rather than \"you\" — inclusive phrasing\n- Specific and factual: \"four bedroom, two and a half bath,\" \"half bath and a closet,\" \"two car garage\"\n- Casual connectives: \"and so,\" \"right along,\" \"you don't really\"\n- Closes warmly: \"Thank you\" (genuinely, not performatively)\n\n**TTS direction notes** (if manually recording reference material or directing a session):\n- Aim for a calm, conversational read — imagine showing a close friend's family the home, not pitching to a stranger\n- Vary sentence length: mix short punchy observations (\"Pool, tree house for the kids.\") with longer descriptive ones\n- Don't over-enunciate — the natural mouth sounds and Texas vowels are part of the voice signature\n\n---\n\n## Quality Checklist Before Cloning\n\n- [ ] Audio is single-speaker only (no background voices, TV, music)\n- [ ] No reverb or room echo\n- [ ] No clipping (peaks below -1 dBFS)\n- [ ] Minimum 6 seconds (XTTS-v2) or 60 seconds (ElevenLabs Instant)\n- [ ] Normalized and trimmed silence\n- [ ] Sample rate: 22050 Hz (acceptable) or 44100 Hz (preferred)\n- [ ] Format: WAV 16-bit or MP3 192kbps+\n\n---\n\n## Sources\n\n- [ElevenLabs Voice Cloning overview](https://elevenlabs.io/docs/creative-platform/voices/voice-cloning)\n- [ElevenLabs Instant Voice Clone requirements](https://elevenlabs.io/docs/creative-platform/voices/voice-cloning/instant-voice-cloning)\n- [ElevenLabs Professional Voice Clone requirements](https://elevenlabs.io/docs/eleven-creative/voices/voice-cloning/professional-voice-cloning)\n- [Coqui XTTS-v2 tutorial — Local AI Master](https://localaimaster.com/models/coqui-tts)\n- [Self-host XTTS-2, F5-TTS, OpenVoice V2 — Spheron](https://www.spheron.network/blog/self-host-voice-cloning-gpu-cloud-xtts-f5-tts-openvoice-v2/)\n- [Richard Fowler — richardfowlerrealtor.com](https://richardfowlerrealtor.com/)\n- [Richard Fowler — client reviews](https://www.experience.com/reviews/richard-6457194)\n- [ARK Property Team — Compass](https://www.compass.com/agents/ark-property-team/)\n===\n# Listing Reel Operator Guide\n\nThe listing reel workflow turns an authorized local listing manifest and photos into a reviewed vertical video package. The public URL identifies the property; the workflow does not scrape Zillow, Realtor.com, Redfin, or other listing sites.\n\n## 1. Prepare authorized inputs\n\nKeep real manifests and photos under `input/` or another ignored local directory. Confirm that the listing agent, broker, photographer, or licensed feed permits the intended social-media use.\n\nCreate a JSON manifest:\n\n```json\n{\n \"version\": 1,\n \"source_url\": \"https://www.zillow.com/homedetails/example/1_zpid/\",\n \"rights_confirmed\": true,\n \"attribution\": \"Listing agent supplied media for social promotion.\",\n \"address\": \"123 Example Street\",\n \"city\": \"Austin\",\n \"state\": \"TX\",\n \"postal_code\": \"78701\",\n \"price\": 625000,\n \"beds\": 4,\n \"baths\": 3,\n \"square_feet\": 2410,\n \"description\": \"Approved factual listing description.\",\n \"photos\": [\n {\"path\": \"photos/front.jpg\", \"label\": \"Exterior\", \"focal_point\": [0.5, 0.5]},\n {\"path\": \"photos/living.jpg\", \"label\": \"Living room\", \"focal_point\": [0.55, 0.45]}\n ],\n \"cover_photo_index\": 0\n}\n```\n\nPhoto paths must be relative to `--media-root`, cannot escape it through `..` or symlinks, and must point to JPEG, PNG, WebP, or PPM files. The intake step records each file's size and SHA-256 hash; the renderer checks those values again after approval.\n\n## 2. Configure the agent and voice\n\nSet public contact fields and provider configuration in `.env`:\n\n```bash\nAGENT_NAME=\"Agent Name\"\nAGENT_INSTAGRAM_HANDLE=\"@agenthandle\"\nAGENT_WEBSITE=\"https://example.com\"\n\nELEVENLABS_API_KEY=\"...\"\nDEFAULT_VOICE_ID=\"...\"\nVOICE_CLONE_CONSENT_CONFIRMED=true\nVOICE_CLONE_OWNER=\"Agent Name\"\n```\n\nFor a person-specific ElevenLabs voice, the voice owner must create and verify the Professional Voice Clone and privately share it with the account running this workflow. Do not upload third-party recordings to create a clone on the person's behalf.\n\n## 3. Start and review\n\n```bash\npython3 -m cli.main listing-reel \\\n --url \"https://www.zillow.com/homedetails/example/1_zpid/\" \\\n --manifest input/listing/listing.json \\\n --media-root input/listing \\\n --tenant agent-name\n```\n\nThe command stops at one JSON approval artifact before voice synthesis or rendering. Review and edit:\n\n- sourced facts and attribution;\n- narration and Instagram caption;\n- photo order and cover choice;\n- public contact outro;\n- target duration.\n\nDo not add claims that the manifest does not support, especially claims about schools, safety, demographics, financing, appreciation, or protected classes.\n\nResume with the same artifact:\n\n```bash\npython3 -m cli.main approve JOB_ID \\\n --script output/JOB_ID/approved_listing_reel.json \\\n --approved-by operator-name\n```\n\nThe resume command reloads the original provider and voice settings. Requested ElevenLabs narration fails closed if credentials, voice ownership/consent, synthesis, or audible output validation fails.\n\nIf a provider or render step fails after approval, the job is saved as failed. Correct the provider/configuration issue and retry the failed step without repeating approval:\n\n```bash\npython3 -m cli.main resume JOB_ID\n```\n\n## 4. Inspect the handoff\n\nThe completed job contains `output/JOB_ID/publish/` with:\n\n- `final_video.mp4` — 1080x1920 H.264/AAC reel at 30 fps;\n- `cover.jpg` or `cover.png` — dedicated 1:1.55 Instagram cover;\n- `caption.txt` — approved caption;\n- `listing_snapshot.json` — the source and media-integrity record;\n- `metadata.json` — tenant, handle, dimensions, duration, and package filenames.\n\nBefore delivery, watch the entire MP4 and verify visible photo motion, accurate changing captions, audible correct narration, readable safe-zone text, the final contact card, and no unauthorized or substituted media. Posting remains manual.\n\nFor an offline renderer check, pass `--tts-provider say` on macOS or `--tts-provider silent` only when silence is intentional test data. Silent mode is not acceptable for a production deliverable.","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"40f76516-258a-4ca7-ad6f-b83a5b7c5331","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
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{"parentUuid":"291c1b09-5c70-4eeb-91fe-e0d02efcf571","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Ccppfgxjx1Q9MshsDvWPv","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Now I have a clear picture. Let me understand what James wants to put together for a Richard Fowler demo:\n\n1. **The walkthrough video** - James already has a walkthrough video (IMG_2157.MOV) processed through the system. He wants to present it with Richard's cloned voice and a good thumbnail/outro contact card.\n\n2. **3 demo listing reels** - 3 different Instagram-ready videos using 3 different template styles, ideally from Richard's actual listings.\n\nThe key gaps I need to identify:\n1. **Voice** - Richard's ElevenLabs Professional Voice Clone isn't set up yet (he needs to create it himself and share it). \n\nThere's a local XTTS-v2 clone sample we could use for demonstration purposes, but ideally Richard creates his own professional version.\n\n2. **Listing photos** - We need authorized photos from Richard's actual listings. His website at richardfowlerrealtor.com would be a good source for current properties.\n\n3. **Templates** - We need to define 3 distinct template styles. Looking at competitor approaches, I'm thinking about an AutoReel-style template with an exterior-to-interior flow, minimal text overlays, and restrained camera movements.\n\nThe AutoReel template would run about 30 seconds, while a Momenzo-style approach would feature room-by-room progression with AI-generated captions highlighting key features, and a HeyGen-style would be more branded with agent intro and outro cards.\n\nSo here's what I need to communicate to James about what's ready versus what we still need. The pipeline itself is functional and can generate listing reels from photos and a manifest file. We have that local voice clone for demo purposes, though it's not production quality. The workflow and rendering system are already built out.\n\nFor the actual demo, we need Richard's listing photos—James would need to either get authorized images directly from Richard or pull them from his website with permission. For the voice component, we could use the local XTTS-v2 clone to show the concept, but we'd want Richard's actual voice for anything production-ready.\n\nI'm thinking about three distinct template approaches that would showcase different styles. The first would be a clean, minimal editorial look with white overlays and subtle motion, moving through exterior to main rooms to kitchen to primary to backyard. The second would emphasize individual features with prominent labels on each photo, faster transitions, and more dynamic movement. The third would be agent-branded with Richard's name and colors prominently featured, room labels with icons, and a more prominent contact outro.\n\nTo actually produce these three different styles, I'd need to either parameterize the renderer to support different visual approaches or define configuration options that create meaningfully different outputs. Right now the code only produces one style.\n\nI'm identifying what James needs to handle versus what I can help build. James needs to get Richard's buy-in for a meeting, secure authorized listing photos, and decide on the voice approach—whether to use a local voice clone for the demo or wait for Richard to set up ElevenLabs. On my end, I can help define the template styles more precisely, prepare listing manifests once photos are available, and look up Richard's current listings to see what we're working with.\n\nI should also check on the walkthrough video status—whether IMG_2157.MOV has already been processed through the pipeline with a cloned voice, since the recent commits have focused on the listing reel feature rather than the narrated video 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{"parentUuid":"79906b65-ce14-4b9e-a4cf-d45575afa5f6","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Ccppi8gcnGqR87CZC9vJZ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01WHdZvPnnBaCCR63b4NNKLL","name":"Bash","input":{"command":"# Find the most recent completed job with a publish/ directory\nfor dir in /workspace/extra/projects/stagehand/output/*/; do\n if [ -d \"${dir}publish\" ]; then\n echo \"=== $dir ===\"\n ls \"${dir}publish/\"\n fi\ndone | head -50"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":223,"cache_read_input_tokens":52901,"output_tokens":124,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":223,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":124,"cache_read_input_tokens":52901,"cache_creation_input_tokens":223,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":223},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Ccppi7Aq91RVy6VREJCCX","type":"assistant","uuid":"23c0b8a7-3bf2-4af1-9ca9-c30fd35e15ad","timestamp":"2026-07-08T15:25:40.497Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"23c0b8a7-3bf2-4af1-9ca9-c30fd35e15ad","isSidechain":false,"promptId":"674253e9-f943-40e3-b94f-99e2ed034599","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01WHdZvPnnBaCCR63b4NNKLL","type":"tool_result","content":"=== /workspace/extra/projects/stagehand/output/647d7b9b-2a2d-4bc5-9434-2a1fde35819a/ ===\ncaption.txt\ncover.jpg\nfinal_video.mp4\nlisting_snapshot.json\nmetadata.json\n=== /workspace/extra/projects/stagehand/output/c4c74f62-c5e8-4144-855c-1477f97297b8/ ===\ncaption.txt\ncover.jpg\nfinal_video.mp4\nlisting_snapshot.json\nmetadata.json\n=== /workspace/extra/projects/stagehand/output/d4d67dc5-53fa-4de9-af9d-8072e96f969e/ ===\ncaption.txt\ncover.jpg\nfinal_video.mp4\nlisting_snapshot.json\nmetadata.json\n=== /workspace/extra/projects/stagehand/output/e2954c52-ed24-45d3-8d45-dec6bdc89304/ ===\ncaption.txt\ncover.jpg\nfinal_video.mp4\nlisting_snapshot.json\nmetadata.json","is_error":false}]},"uuid":"7481a098-6c11-4e8e-8e63-4a612c835f08","timestamp":"2026-07-08T15:25:40.530Z","toolUseResult":{"stdout":"=== /workspace/extra/projects/stagehand/output/647d7b9b-2a2d-4bc5-9434-2a1fde35819a/ ===\ncaption.txt\ncover.jpg\nfinal_video.mp4\nlisting_snapshot.json\nmetadata.json\n=== /workspace/extra/projects/stagehand/output/c4c74f62-c5e8-4144-855c-1477f97297b8/ ===\ncaption.txt\ncover.jpg\nfinal_video.mp4\nlisting_snapshot.json\nmetadata.json\n=== /workspace/extra/projects/stagehand/output/d4d67dc5-53fa-4de9-af9d-8072e96f969e/ ===\ncaption.txt\ncover.jpg\nfinal_video.mp4\nlisting_snapshot.json\nmetadata.json\n=== /workspace/extra/projects/stagehand/output/e2954c52-ed24-45d3-8d45-dec6bdc89304/ ===\ncaption.txt\ncover.jpg\nfinal_video.mp4\nlisting_snapshot.json\nmetadata.json","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"23c0b8a7-3bf2-4af1-9ca9-c30fd35e15ad","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"7481a098-6c11-4e8e-8e63-4a612c835f08","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcppiTB7DuSkLShmaWjW4","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_0111zXNxjGm9pMWF9EHcmFC1","name":"Bash","input":{"command":"# Check what's in the most recent publish packages\nfor dir in /workspace/extra/projects/stagehand/output/*/; do\n if [ -d \"${dir}publish\" ]; then\n modtime=$(stat -c %Y \"${dir}publish/final_video.mp4\" 2>/dev/null || echo 0)\n echo \"$modtime $dir\"\n fi\ndone | sort -rn | head -5"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":410,"cache_read_input_tokens":53124,"output_tokens":151,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":410,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":151,"cache_read_input_tokens":53124,"cache_creation_input_tokens":410,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":410},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcppiSSx3M4AFutaPBkc6","type":"assistant","uuid":"16bc4802-9c66-4d5b-b409-fd0abfa1a3df","timestamp":"2026-07-08T15:25:44.507Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"16bc4802-9c66-4d5b-b409-fd0abfa1a3df","isSidechain":false,"promptId":"674253e9-f943-40e3-b94f-99e2ed034599","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0111zXNxjGm9pMWF9EHcmFC1","type":"tool_result","content":"1783452234 /workspace/extra/projects/stagehand/output/e2954c52-ed24-45d3-8d45-dec6bdc89304/\n1783452154 /workspace/extra/projects/stagehand/output/647d7b9b-2a2d-4bc5-9434-2a1fde35819a/\n1783452049 /workspace/extra/projects/stagehand/output/d4d67dc5-53fa-4de9-af9d-8072e96f969e/\n1783451933 /workspace/extra/projects/stagehand/output/c4c74f62-c5e8-4144-855c-1477f97297b8/","is_error":false}]},"uuid":"0df933a3-b5d5-4df2-b182-796a6aa9981c","timestamp":"2026-07-08T15:25:44.539Z","toolUseResult":{"stdout":"1783452234 /workspace/extra/projects/stagehand/output/e2954c52-ed24-45d3-8d45-dec6bdc89304/\n1783452154 /workspace/extra/projects/stagehand/output/647d7b9b-2a2d-4bc5-9434-2a1fde35819a/\n1783452049 /workspace/extra/projects/stagehand/output/d4d67dc5-53fa-4de9-af9d-8072e96f969e/\n1783451933 /workspace/extra/projects/stagehand/output/c4c74f62-c5e8-4144-855c-1477f97297b8/","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"16bc4802-9c66-4d5b-b409-fd0abfa1a3df","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"0df933a3-b5d5-4df2-b182-796a6aa9981c","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcppikZ86dGKfZoTZfcSF","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_014g5A5QbkNT37sUGJrFDqRu","name":"Bash","input":{"command":"cat /workspace/extra/projects/stagehand/output/e2954c52-ed24-45d3-8d45-dec6bdc89304/publish/caption.txt && echo \"===\" && cat /workspace/extra/projects/stagehand/output/e2954c52-ed24-45d3-8d45-dec6bdc89304/publish/metadata.json"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":342,"cache_read_input_tokens":53534,"output_tokens":143,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":342,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":143,"cache_read_input_tokens":53534,"cache_creation_input_tokens":342,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":342},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Ccppija63H3qS4RVBeCxn","type":"assistant","uuid":"714e52ba-a5ae-49ff-bbe8-2ac73633199b","timestamp":"2026-07-08T15:25:48.491Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"714e52ba-a5ae-49ff-bbe8-2ac73633199b","isSidechain":false,"promptId":"674253e9-f943-40e3-b94f-99e2ed034599","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_014g5A5QbkNT37sUGJrFDqRu","type":"tool_result","content":"Austin, TX — Local workflow fixture for render verification only.\n\nContact Richard D Fowler for details or a private tour.\n\n@richardfowlerrealtor===\n{\n \"tenant_id\": \"render-audit\",\n \"handle\": \"@richardfowlerrealtor\",\n \"aspect_ratio\": \"9:16\",\n \"duration_seconds\": 20.0,\n \"caption\": \"Austin, TX \\u2014 Local workflow fixture for render verification only.\\n\\nContact Richard D Fowler for details or a private tour.\\n\\n@richardfowlerrealtor\",\n \"hashtags\": [\n \"#realestate\",\n \"#austinrealestate\"\n ],\n \"video_filename\": \"final_video.mp4\",\n \"cover_filename\": \"cover.jpg\",\n \"listing_snapshot_filename\": \"listing_snapshot.json\",\n \"suggested_post_time\": null,\n \"publish_method\": \"manual_handoff\"\n}","is_error":false}]},"uuid":"994ccf49-2706-4fed-b708-ee0edb856364","timestamp":"2026-07-08T15:25:48.512Z","toolUseResult":{"stdout":"Austin, TX — Local workflow fixture for render verification only.\n\nContact Richard D Fowler for details or a private tour.\n\n@richardfowlerrealtor===\n{\n \"tenant_id\": \"render-audit\",\n \"handle\": \"@richardfowlerrealtor\",\n \"aspect_ratio\": \"9:16\",\n \"duration_seconds\": 20.0,\n \"caption\": \"Austin, TX \\u2014 Local workflow fixture for render verification only.\\n\\nContact Richard D Fowler for details or a private tour.\\n\\n@richardfowlerrealtor\",\n \"hashtags\": [\n \"#realestate\",\n \"#austinrealestate\"\n ],\n \"video_filename\": \"final_video.mp4\",\n \"cover_filename\": \"cover.jpg\",\n \"listing_snapshot_filename\": \"listing_snapshot.json\",\n \"suggested_post_time\": null,\n \"publish_method\": \"manual_handoff\"\n}","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"714e52ba-a5ae-49ff-bbe8-2ac73633199b","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"994ccf49-2706-4fed-b708-ee0edb856364","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Ccppj4HELYA3ajKfcnnxf","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Now I have a good picture of the state. Let me understand what's been built:\n\n1. The listing reel workflow is fully built and produces publish packages with `final_video.mp4`, `cover.jpg`, `caption.txt`, `listing_snapshot.json`, `metadata.json`.\n\n2. The recent jobs were likely run with synthetic/fixture data for testing.\n\n3. The walkthrough video (IMG_2157.MOV) exists as input but I need to check if there's a recent job that used it with Richard's voice.\n\n4. The XTTS-v2 clone exists locally for Richard's voice.\n\nNow for the demo James wants:\nFor the walkthrough video, I can run it through the narration workflow using either ElevenLabs with Richard's voice (if he consents) or the local XTTS-v2 clone that's already set up, plus I'll need a good thumbnail and outro card. For the three listing reels, I need Richard's actual authorized listing photos and need to define three distinct template styles to showcase variety.\n\nThe main constraint is that the current renderer only supports one visual style, so I'd need to either add template parameterization or differentiate through configuration like motion styles, caption treatments, and color themes for the contact card. What I should tell James is that the pipeline is built and working with completed reel packages already in output, and the walkthrough is ready as input with the local voice clone available. The two blockers are getting Richard's listing photos and deciding on the voice approach for the demo.\n\nFor the demo itself, I'm thinking we run the walkthrough video through the narration pipeline with the local XTTS-v2 voice to produce the narrated walkthrough with contact card, then create three listing reels using Richard's actual listings with style variations. I need to present James with a concrete plan that identifies these two blocking questions clearly.\n\nActually, let me first check what the coqui-demo outputs look like to see if there's already a completed walkthrough with Richard's voice that we can 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{"parentUuid":"b04a1350-afaa-41a1-9a2c-7a9bab97f345","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Ccppm3Ufh6mCqiaSadYuk","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Good. So we have completed walkthrough demo videos with Richard's XTTS-v2 cloned voice. The coqui-demo outputs contain final_video.mp4 files from the walkthrough workflow.\n\nNow let me give James a clear, concise summary of what we have and what the path forward looks like for the demo package.\n\nKey facts:\n1. **Walkthrough with Richard's voice**: Already done via XTTS-v2 local clone - `coqui-demo`, `coqui-demo-2`, `coqui-demo-3` each have final_video.mp4\n2. **Listing reels**: 4 completed jobs with full publish packages including video, cover image, and captions\n3. **What's still missing**: Real listing photos from Richard's properties, the three template style variations (we're currently locked into one renderer style), and I need to verify whether the walkthrough has a proper contact card outro\n\nThe core question for the demo is how to handle template differentiation—we'd need to add configurable parameters to the renderer to produce meaningfully different visual styles rather than just one fixed approach.\n\nI'm thinking three distinct templates: a minimal \"Essential\" style with subtle motion and clean overlays, a \"Feature Focus\" version with prominent room labels and faster pacing, and a \"Branded Showcase\" option that incorporates Richard's branding, agent headshot, and stronger calls-to-action. The walkthrough videos from the coqui demo are already done, so James just needs to review them for quality.\n\nI should ask James two things: whether he wants me to build out all three template styles now, and whether he has access to Richard's actual listing photos or if we need to pull them from his website. I should also flag that the XTTS-v2 voice clone is demo-quality at best—for the real pitch, Richard will want to set up his own ElevenLabs account for a professional voice.","signature":"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"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":250,"cache_read_input_tokens":55576,"output_tokens":1236,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":250,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":1236,"cache_read_input_tokens":55576,"cache_creation_input_tokens":250,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":250},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Ccppm2VdPLpkT6tXzQya7","type":"assistant","uuid":"da74bf37-dd55-4410-8f24-3de0ee04e033","timestamp":"2026-07-08T15:26:32.746Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"da74bf37-dd55-4410-8f24-3de0ee04e033","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Ccppm3Ufh6mCqiaSadYuk","type":"message","role":"assistant","content":[{"type":"text","text":"Good picture now. Let me lay out exactly where things stand and what's needed.\n\n\nHere's the state of play and a concrete plan for the Richard demo package.\n\n**What already exists:**\n- Walkthrough videos with Richard's XTTS-v2 cloned voice are already rendered — `output/coqui-demo/`, `coqui-demo-2/`, `coqui-demo-3/` each have a `final_video.mp4`. These are from IMG_2157.MOV with the local voice clone baked in. Worth watching them to pick the best one.\n- The listing reel pipeline is fully built and has produced 4 complete publish packages (video + designed cover + caption) — those were test fixtures, not real listings.\n\n**What's needed for the 3-template listing demo:**\n\n*1. Richard's actual listing photos* — The pipeline won't scrape Zillow. We need authorized photos for 3 of his listings. Options:\n- Ask Richard directly once you're in contact (cleanest path)\n- His website richardfowlerrealtor.com has listings — I can research what's active or recent right now so we can plan which 3 to target and have the manifests ready to go the moment he shares photos\n\n*2. Three visual template styles* — The renderer currently produces one look. To show 3 distinct styles like competitors offer, we need to parameterize it. My proposed 3:\n- **Essential** (AutoReel-style): neutral palette, subtle Ken Burns pans, minimal text, facts as brief bottom overlays, ~25s\n- **Feature Spotlight** (Momenzo-style): each photo gets a bold room label + key stat mid-screen, tighter pacing, more kinetic feel\n- **Branded** (HeyGen-inspired): Richard's name/handle prominent on every slide, color-accented outro card, stronger CTA\n\nBuilding those variants is a 1-session coding task once we confirm the 3 looks. Want me to get started on the template parameterization now, or look up his current listings first?\n\n**Voice for the demo:**\nThe XTTS-v2 clone is demo-quality — good enough to show the concept. For the final pitch to Richard, he'd need to create his ElevenLabs Professional Voice Clone himself and share it. Worth having that conversation with him as part of the meeting.\n"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":250,"cache_read_input_tokens":55576,"output_tokens":1236,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":250,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":1236,"cache_read_input_tokens":55576,"cache_creation_input_tokens":250,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":250},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Ccppm2VdPLpkT6tXzQya7","type":"assistant","uuid":"c96677c3-0b50-4bd4-a934-ae3a57e571ef","timestamp":"2026-07-08T15:26:43.593Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"type":"queue-operation","operation":"enqueue","timestamp":"2026-07-08T15:35:51.786Z","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","content":"\nYes let's grab images from his siteYes let's go with your recommendations\nDemo quality voice is fine for now @U0BFL0HCL20"}
{"type":"queue-operation","operation":"dequeue","timestamp":"2026-07-08T15:35:51.787Z","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}
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{"parentUuid":"82358725-5fc2-409b-b70e-cc75e3b53d33","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcpqWB2nLYTpvpWPpRE57","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Let me send an acknowledgment and then start working on both tasks in parallel:\n1. Browse Richard's website to find listings and photos\n2. Plan the template parameterization for the renderer\n\nI'll send an ack via send_message, then spawn an agent to browse his website.","signature":"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"}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":1076,"cache_read_input_tokens":57150,"output_tokens":159,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1076,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":159,"cache_read_input_tokens":57150,"cache_creation_input_tokens":1076,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":1076},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcpqW8VEjgV2EXaP6YATT","type":"assistant","uuid":"1c4dd0a3-be3a-4088-ba5c-e00cc2ed1a02","timestamp":"2026-07-08T15:36:05.400Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"1c4dd0a3-be3a-4088-ba5c-e00cc2ed1a02","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcpqWB2nLYTpvpWPpRE57","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Xpzzdq6ZYLpj1UU6Ch7kKD","name":"ToolSearch","input":{"query":"select:mcp__nanoclaw__send_message","max_results":1},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":1076,"cache_read_input_tokens":57150,"output_tokens":159,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1076,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":159,"cache_read_input_tokens":57150,"cache_creation_input_tokens":1076,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":1076},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcpqW8VEjgV2EXaP6YATT","type":"assistant","uuid":"ef423718-fcdc-4bc6-b6ce-fa09eac9a3fa","timestamp":"2026-07-08T15:36:05.904Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"ef423718-fcdc-4bc6-b6ce-fa09eac9a3fa","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"type":"tool_result","tool_use_id":"toolu_01Xpzzdq6ZYLpj1UU6Ch7kKD","content":[{"type":"tool_reference","tool_name":"mcp__nanoclaw__send_message"}]}]},"uuid":"99725d2d-a681-49a8-a399-0723357d7b56","timestamp":"2026-07-08T15:36:05.922Z","toolUseResult":{"matches":["mcp__nanoclaw__send_message"],"query":"select:mcp__nanoclaw__send_message","total_deferred_tools":88},"sourceToolAssistantUUID":"ef423718-fcdc-4bc6-b6ce-fa09eac9a3fa","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"99725d2d-a681-49a8-a399-0723357d7b56","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcpqWb6dyuedKg4WdNkg9","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Let me send an ack and then start working. I'll:\n1. Send an ack message\n2. Spawn an agent-browser to browse Richard's website for listings/photos\n3. Look at the current renderer code to plan the 3 template styles\n\nLet me do the ack first, then parallelize the browsing and code reading.","signature":"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"}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":312,"cache_read_input_tokens":58226,"output_tokens":190,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":312,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":190,"cache_read_input_tokens":58226,"cache_creation_input_tokens":312,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":312},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcpqWYba892egiWG2xcxn","type":"assistant","uuid":"4da1a1c1-36ea-4eaa-a560-6bb33592738b","timestamp":"2026-07-08T15:36:10.575Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"4da1a1c1-36ea-4eaa-a560-6bb33592738b","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcpqWb6dyuedKg4WdNkg9","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01KHGGshSWqRtbdQUhm6Q8vz","name":"mcp__nanoclaw__send_message","input":{"to":"slack-mg-17835-5","text":"On it — grabbing his listings now and starting on the template code in parallel."},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":312,"cache_read_input_tokens":58226,"output_tokens":190,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":312,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":190,"cache_read_input_tokens":58226,"cache_creation_input_tokens":312,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":312},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcpqWYba892egiWG2xcxn","type":"assistant","uuid":"a89f402e-1de5-43f4-a402-00792b58d376","timestamp":"2026-07-08T15:36:11.630Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"a89f402e-1de5-43f4-a402-00792b58d376","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01KHGGshSWqRtbdQUhm6Q8vz","type":"tool_result","content":[{"type":"text","text":"Message sent to slack-mg-17835-5 (id: 7)"}]}]},"uuid":"ffd1715e-c659-49f1-9566-31aec6051332","timestamp":"2026-07-08T15:36:11.665Z","toolUseResult":[{"type":"text","text":"Message sent to slack-mg-17835-5 (id: 7)"}],"sourceToolAssistantUUID":"a89f402e-1de5-43f4-a402-00792b58d376","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"ffd1715e-c659-49f1-9566-31aec6051332","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcpqWyrMnconn4ZXxipSb","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01LKDuDVp9s8sgtLKrZ4rnoR","name":"Agent","input":{"description":"Browse Richard Fowler's realtor website for active listings with photos","subagent_type":"general-purpose","prompt":"Browse richardfowlerrealtor.com to find Richard Fowler's current or recent property listings. I need:\n\n1. A list of 3 active or recently sold listings with their addresses, prices, beds/baths, and brief descriptions\n2. For each listing, find the listing photos/images — get the direct image URLs if possible so we can download them\n3. Any listing detail pages with property facts (sq ft, features, etc.)\n\nHis site is for a Cedar Park, TX REALTOR (Compass). Focus on residential listings with good photo sets (ideally 6+ photos per listing). \n\nReturn a structured list of the 3 best listings with: address, price, beds, baths, sq ft, description summary, and all the photo URLs you can find for each."},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":221,"cache_read_input_tokens":58538,"output_tokens":332,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":221,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":332,"cache_read_input_tokens":58538,"cache_creation_input_tokens":221,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":221},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcpqWy2kTq6u2fGDk2STp","type":"assistant","uuid":"b82db34b-b390-4a8d-b9a7-f5633cfc170a","timestamp":"2026-07-08T15:36:21.599Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"b82db34b-b390-4a8d-b9a7-f5633cfc170a","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcpqWyrMnconn4ZXxipSb","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01CoanNgsVc73jccqnYzwoBH","name":"Bash","input":{"command":"cat /workspace/extra/projects/stagehand/core/media/photo_reel.py"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":221,"cache_read_input_tokens":58538,"output_tokens":332,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":221,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":332,"cache_read_input_tokens":58538,"cache_creation_input_tokens":221,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":221},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcpqWy2kTq6u2fGDk2STp","type":"assistant","uuid":"03733395-7d89-49f5-9f75-d7b8b63cb14c","timestamp":"2026-07-08T15:36:22.089Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"03733395-7d89-49f5-9f75-d7b8b63cb14c","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CoanNgsVc73jccqnYzwoBH","type":"tool_result","content":"from __future__ import annotations\n\nimport subprocess\nfrom collections.abc import Sequence\nfrom pathlib import Path\n\n\nclass PhotoReelError(ValueError):\n pass\n\n\ndef build_photo_reel_command(\n *,\n photo_paths: Sequence[str | Path],\n narration_audio: str | Path,\n outro_image: str | Path,\n caption_overlays: Sequence[dict],\n output_video: str | Path,\n total_duration_seconds: float,\n outro_duration_seconds: float = 4.5,\n width: int = 1080,\n height: int = 1920,\n fps: int = 30,\n) -> list[str]:\n photos = [Path(path) for path in photo_paths]\n total_duration = float(total_duration_seconds)\n outro_duration = float(outro_duration_seconds)\n if not photos:\n raise PhotoReelError(\"Photo reel requires at least one photo\")\n if total_duration <= 0:\n raise PhotoReelError(\"Photo reel duration must be positive\")\n if outro_duration <= 0 or outro_duration >= total_duration:\n raise PhotoReelError(\"Photo reel outro duration must be positive and shorter than total duration\")\n if width <= 0 or height <= 0 or fps <= 0:\n raise PhotoReelError(\"Photo reel output settings must be positive\")\n\n main_duration = total_duration - outro_duration\n transition = min(0.45, main_duration / max(4, len(photos) * 4)) if len(photos) > 1 else 0.0\n scene_duration = (main_duration + (len(photos) - 1) * transition) / len(photos)\n scene_frames = max(1, round(scene_duration * fps))\n frame_denominator = max(1, scene_frames - 1)\n zoom_increment = 0.06 / frame_denominator\n\n command = [\"ffmpeg\", \"-y\"]\n for photo in photos:\n command.extend([\"-loop\", \"1\", \"-framerate\", str(fps), \"-i\", str(photo)])\n outro_index = len(photos)\n command.extend([\"-loop\", \"1\", \"-framerate\", str(fps), \"-i\", str(outro_image)])\n audio_index = outro_index + 1\n command.extend([\"-i\", str(narration_audio)])\n caption_start_index = audio_index + 1\n for overlay in caption_overlays:\n command.extend([\"-loop\", \"1\", \"-framerate\", str(fps), \"-i\", str(overlay[\"path\"])])\n\n filters: list[str] = []\n for index in range(len(photos)):\n if index % 2 == 0:\n x_expression = f\"(iw-iw/zoom)*on/{frame_denominator}\"\n else:\n x_expression = f\"(iw-iw/zoom)*(1-on/{frame_denominator})\"\n filters.append(\n f\"[{index}:v]scale={width}:{height}:force_original_aspect_ratio=increase,\"\n f\"crop={width}:{height},setsar=1,\"\n f\"zoompan=z='min(zoom+{zoom_increment:.8f},1.06)':\"\n f\"x='{x_expression}':y='(ih-ih/zoom)/2':\"\n f\"d={scene_frames}:s={width}x{height}:fps={fps},\"\n f\"trim=duration={scene_duration:.6f},setpts=PTS-STARTPTS,format=yuv420p[p{index}]\"\n )\n\n photo_label = \"p0\"\n if len(photos) > 1:\n current_duration = scene_duration\n for index in range(1, len(photos)):\n output_label = f\"px{index}\"\n offset = current_duration - transition\n filters.append(\n f\"[{photo_label}][p{index}]xfade=transition=fade:duration={transition:.6f}:\"\n f\"offset={offset:.6f}[{output_label}]\"\n )\n photo_label = output_label\n current_duration += scene_duration - transition\n\n filters.append(\n f\"[{outro_index}:v]scale={width}:{height}:force_original_aspect_ratio=increase,\"\n f\"crop={width}:{height},setsar=1,trim=duration={outro_duration:.6f},\"\n f\"setpts=PTS-STARTPTS,format=yuv420p[outro]\"\n )\n filters.append(f\"[{photo_label}][outro]concat=n=2:v=1:a=0[base]\")\n\n video_label = \"base\"\n for index, overlay in enumerate(caption_overlays):\n input_index = caption_start_index + index\n output_label = f\"captioned{index}\"\n start = float(overlay[\"start\"])\n end = float(overlay[\"end\"])\n if end <= start:\n raise PhotoReelError(f\"Caption overlay {index} must end after it starts\")\n filters.append(\n f\"[{video_label}][{input_index}:v]overlay=(W-w)/2:H-h-160:\"\n f\"enable='between(t,{start:.3f},{end:.3f})':eof_action=pass:format=auto[{output_label}]\"\n )\n video_label = output_label\n\n filters.append(f\"[{video_label}]setparams=range=tv,format=yuv420p[final]\")\n video_label = \"final\"\n\n command.extend(\n [\n \"-filter_complex\",\n \";\".join(filters),\n \"-map\",\n f\"[{video_label}]\",\n \"-map\",\n f\"{audio_index}:a:0\",\n \"-t\",\n f\"{total_duration:.3f}\",\n \"-r\",\n str(fps),\n \"-c:v\",\n \"libx264\",\n \"-pix_fmt\",\n \"yuv420p\",\n \"-c:a\",\n \"aac\",\n \"-movflags\",\n \"+faststart\",\n str(output_video),\n ]\n )\n return command\n\n\ndef run_photo_reel(command: Sequence[str]) -> subprocess.CompletedProcess[str]:\n if not command or command[0] != \"ffmpeg\":\n raise PhotoReelError(\"Photo reel command must start with ffmpeg\")\n return subprocess.run(list(command), check=True, capture_output=True, text=True)","is_error":false}]},"uuid":"2c0db4b5-8476-4375-8d6b-c7524bdc4b5a","timestamp":"2026-07-08T15:36:22.116Z","toolUseResult":{"stdout":"from __future__ import annotations\n\nimport subprocess\nfrom collections.abc import Sequence\nfrom pathlib import Path\n\n\nclass PhotoReelError(ValueError):\n pass\n\n\ndef build_photo_reel_command(\n *,\n photo_paths: Sequence[str | Path],\n narration_audio: str | Path,\n outro_image: str | Path,\n caption_overlays: Sequence[dict],\n output_video: str | Path,\n total_duration_seconds: float,\n outro_duration_seconds: float = 4.5,\n width: int = 1080,\n height: int = 1920,\n fps: int = 30,\n) -> list[str]:\n photos = [Path(path) for path in photo_paths]\n total_duration = float(total_duration_seconds)\n outro_duration = float(outro_duration_seconds)\n if not photos:\n raise PhotoReelError(\"Photo reel requires at least one photo\")\n if total_duration <= 0:\n raise PhotoReelError(\"Photo reel duration must be positive\")\n if outro_duration <= 0 or outro_duration >= total_duration:\n raise PhotoReelError(\"Photo reel outro duration must be positive and shorter than total duration\")\n if width <= 0 or height <= 0 or fps <= 0:\n raise PhotoReelError(\"Photo reel output settings must be positive\")\n\n main_duration = total_duration - outro_duration\n transition = min(0.45, main_duration / max(4, len(photos) * 4)) if len(photos) > 1 else 0.0\n scene_duration = (main_duration + (len(photos) - 1) * transition) / len(photos)\n scene_frames = max(1, round(scene_duration * fps))\n frame_denominator = max(1, scene_frames - 1)\n zoom_increment = 0.06 / frame_denominator\n\n command = [\"ffmpeg\", \"-y\"]\n for photo in photos:\n command.extend([\"-loop\", \"1\", \"-framerate\", str(fps), \"-i\", str(photo)])\n outro_index = len(photos)\n command.extend([\"-loop\", \"1\", \"-framerate\", str(fps), \"-i\", str(outro_image)])\n audio_index = outro_index + 1\n command.extend([\"-i\", str(narration_audio)])\n caption_start_index = audio_index + 1\n for overlay in caption_overlays:\n command.extend([\"-loop\", \"1\", \"-framerate\", str(fps), \"-i\", str(overlay[\"path\"])])\n\n filters: list[str] = []\n for index in range(len(photos)):\n if index % 2 == 0:\n x_expression = f\"(iw-iw/zoom)*on/{frame_denominator}\"\n else:\n x_expression = f\"(iw-iw/zoom)*(1-on/{frame_denominator})\"\n filters.append(\n f\"[{index}:v]scale={width}:{height}:force_original_aspect_ratio=increase,\"\n f\"crop={width}:{height},setsar=1,\"\n f\"zoompan=z='min(zoom+{zoom_increment:.8f},1.06)':\"\n f\"x='{x_expression}':y='(ih-ih/zoom)/2':\"\n f\"d={scene_frames}:s={width}x{height}:fps={fps},\"\n f\"trim=duration={scene_duration:.6f},setpts=PTS-STARTPTS,format=yuv420p[p{index}]\"\n )\n\n photo_label = \"p0\"\n if len(photos) > 1:\n current_duration = scene_duration\n for index in range(1, len(photos)):\n output_label = f\"px{index}\"\n offset = current_duration - transition\n filters.append(\n f\"[{photo_label}][p{index}]xfade=transition=fade:duration={transition:.6f}:\"\n f\"offset={offset:.6f}[{output_label}]\"\n )\n photo_label = output_label\n current_duration += scene_duration - transition\n\n filters.append(\n f\"[{outro_index}:v]scale={width}:{height}:force_original_aspect_ratio=increase,\"\n f\"crop={width}:{height},setsar=1,trim=duration={outro_duration:.6f},\"\n f\"setpts=PTS-STARTPTS,format=yuv420p[outro]\"\n )\n filters.append(f\"[{photo_label}][outro]concat=n=2:v=1:a=0[base]\")\n\n video_label = \"base\"\n for index, overlay in enumerate(caption_overlays):\n input_index = caption_start_index + index\n output_label = f\"captioned{index}\"\n start = float(overlay[\"start\"])\n end = float(overlay[\"end\"])\n if end <= start:\n raise PhotoReelError(f\"Caption overlay {index} must end after it starts\")\n filters.append(\n f\"[{video_label}][{input_index}:v]overlay=(W-w)/2:H-h-160:\"\n f\"enable='between(t,{start:.3f},{end:.3f})':eof_action=pass:format=auto[{output_label}]\"\n )\n video_label = output_label\n\n filters.append(f\"[{video_label}]setparams=range=tv,format=yuv420p[final]\")\n video_label = \"final\"\n\n command.extend(\n [\n \"-filter_complex\",\n \";\".join(filters),\n \"-map\",\n f\"[{video_label}]\",\n \"-map\",\n f\"{audio_index}:a:0\",\n \"-t\",\n f\"{total_duration:.3f}\",\n \"-r\",\n str(fps),\n \"-c:v\",\n \"libx264\",\n \"-pix_fmt\",\n \"yuv420p\",\n \"-c:a\",\n \"aac\",\n \"-movflags\",\n \"+faststart\",\n str(output_video),\n ]\n )\n return command\n\n\ndef run_photo_reel(command: Sequence[str]) -> subprocess.CompletedProcess[str]:\n if not command or command[0] != \"ffmpeg\":\n raise PhotoReelError(\"Photo reel command must start with ffmpeg\")\n return subprocess.run(list(command), check=True, capture_output=True, text=True)","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"03733395-7d89-49f5-9f75-d7b8b63cb14c","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"type":"last-prompt","leafUuid":"2c0db4b5-8476-4375-8d6b-c7524bdc4b5a","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}
{"type":"ai-title","aiTitle":"Review competitive analysis documentation","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}
{"parentUuid":"b82db34b-b390-4a8d-b9a7-f5633cfc170a","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01LKDuDVp9s8sgtLKrZ4rnoR","type":"tool_result","content":[{"type":"text","text":"The `big4` path gives ~950KB full-res JPEGs — significantly larger than the 1200x630 version (~344KB). Now I have everything needed. Here is the fully structured result:\n\n---\n\n## Richard Fowler (Compass, Cedar Park TX) — 3 Best Residential Listings\n\n---\n\n### Listing 1: 2605 Orsobello Pl, Cedar Park, TX 78613\n\n**Status:** Sold (11/24/2021)\n**Price:** $899,900\n**Beds/Baths:** 4 bed / 3.5 bath\n**Square Footage:** 3,243 sq ft\n**Lot Size:** 0.24 acres (10,585 sq ft)\n**Year Built:** 2004\n**Price/sq ft:** $277\n**Compass Listing:** https://www.compass.com/homedetails/2605-Orsobello-Pl-Cedar-Park-TX-78613/892704791158671745_lid/\n**Virtual Tour:** https://www.tourfactory.com/2924979\n\n**Description:** Contemporary Rustic Texan home in Bella Vista community with over $100K in upgrades. Features stone masonry, open-concept living, remodeled kitchen with quartz countertops, vaulted ceilings, gas fireplace, luxury owner's suite with garden soaking tub, game room, 3-car garage, multi-level Trex deck with hot tub, and greenbelt/creek views. Walking distance to Bella Vista Park, minutes from Lakeline Mall.\n\n**Photo URLs (43 photos, full-res JPEGs ~950KB each):**\n\nBase URL pattern: `https://www.tourfactory.com/media/scene/big4/[ID].jpg`\n\n```\nhttps://www.tourfactory.com/media/scene/big4/75341186.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341187.jpg ← hero/cover photo\nhttps://www.tourfactory.com/media/scene/big4/75341188.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341189.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341190.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341191.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341192.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341193.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341194.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341195.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341196.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341197.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341198.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341199.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341200.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341201.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341202.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341203.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341204.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341205.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341206.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341207.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341208.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341209.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341210.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341211.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341212.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341213.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341214.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341215.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338561.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338562.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338563.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338564.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338565.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338566.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338570.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338571.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338572.jpg\nhttps://www.tourfactory.com/media/scene/big4/75361795.jpg\nhttps://www.tourfactory.com/media/scene/big4/75361796.jpg\nhttps://www.tourfactory.com/media/scene/big4/75361797.jpg\nhttps://www.tourfactory.com/media/scene/big4/75361798.jpg\n```\n\nAlso available via Compass (cover photo only):\n- `https://www.compass.com/m/3b3fe93ca7e476478b56809e7f2ad23268f45ba12fabd96e28681a98d13f3c08/origin.jpg`\n\n---\n\n### Listing 2: 8 Hightrail Way, The Hills, TX 78738\n\n**Status:** Sold (3/21/2022)\n**Price:** $1,150,000\n**Beds/Baths:** 3 bed / 3 bath (2.5 full)\n**Square Footage:** 3,275 sq ft\n**Lot Size:** 0.16 acres (6,969 sq ft)\n**Year Built:** 2001\n**Stories:** 2\n**Price/sq ft:** $351\n**Compass Listing:** https://www.compass.com/homedetails/8-Hightrail-Way-The-Hills-TX-78738/984131746132131137_lid/\n**Virtual Tour:** https://www.tourfactory.com/2954124\n\n**Description:** Updated luxury home in The Hills of Lakeway (gated community). Over $150K in designer upgrades including whitewash oak hardwoods, bamboo and high-end tile flooring, LED recessed lighting, vaulted ceilings, granite-counter gourmet kitchen with island, wood-burning fireplace, updated primary suite with marble bath, upstairs family room with built-ins, home office, and 2-car garage. Near Hills Country Club, golf courses, and tennis facilities.\n\n**Photo URLs (37 photos, full-res JPEGs ~950KB each):**\n\nBase URL pattern: `https://www.tourfactory.com/media/scene/big4/[ID].jpg`\n\n```\nhttps://www.tourfactory.com/media/scene/big4/76228804.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228805.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228806.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228807.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228808.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228809.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228810.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228811.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228814.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228815.jpg ← hero/cover photo\nhttps://www.tourfactory.com/media/scene/big4/76228816.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228817.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228818.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228819.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228820.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228821.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228822.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228823.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228824.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228825.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228826.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228827.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228828.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228829.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228830.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228831.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228832.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228833.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238053.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238054.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238055.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238056.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238057.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238058.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238059.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238060.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238061.jpg\n```\n\nAlso available via Compass (cover photo only):\n- `https://www.compass.com/m/cf3d20d8381b6a84679cf9fb6b543244e3aade7789dd0462add18d4c96003e27/origin.webp`\n\n---\n\n### Listing 3: 3213 Herradura Dr, Leander, TX 78641\n\n**Status:** Sold (12/28/2023)\n**Price:** $895,000\n**Beds/Baths:** 4 bed / 3 bath\n**Square Footage:** 3,504 sq ft\n**Lot Size:** 0.22 acres (9,626 sq ft)\n**Year Built:** 2011\n**Price/sq ft:** $255\n**MLS #:** 2966211\n**Subdivision:** Caballo Ranch Sec 02\n**Compass Listing:** https://www.compass.com/homedetails/3213-Herradura-Dr-Leander-TX-78641/1364037881138127177_lid/\n**Virtual Tour:** http://www.3213herradura.com (site appears down/unreachable as of Jul 2026)\n\n**Description:** Captivating single-story home on a private lot in Caballo Ranch with Brushy Creek views. Over $100K in improvements: fresh paint, no carpet, wood-finished patio with outdoor kitchen, outdoor fireplace, gas log fireplace, floor-to-ceiling windows, soaring ceilings, curbless primary shower with quartz dual vanities, two walk-in closets, double ovens, kitchen island, 2-car garage, and wired for sound. 3-minute walk to community pool.\n\n**Photo URLs:**\n\nCompass cover photo (only one recoverable from static HTML — gallery is JS-rendered):\n```\nhttps://www.compass.com/m/5ce703f71f9f24742c747724c4234a7bc0d2853ef625cdddbf44c0022b206cfa/origin.jpg\nhttps://www.compass.com/m/5ce703f71f9f24742c747724c4234a7bc0d2853ef625cdddbf44c0022b206cfa/1500x1000.jpg\n```\n\nThe virtual tour domain (`3213herradura.com`) is currently unreachable, and Compass renders its full gallery via JavaScript which isn't accessible to static fetching. To get the complete photo set, the Compass listing detail page needs to be opened in a browser and the \"View All\" photos gallery loaded.\n\n---\n\n**Notes on photo access:**\n- Listings 1 and 2 have full photo sets (43 and 37 photos respectively) confirmed live at `https://www.tourfactory.com/media/scene/big4/[ID].jpg`. Each image is a full-resolution JPEG (~950KB).\n- The TourFactory `big4` path is the largest available size. A smaller 1200x630 version is also available at `https://media.tourfactory.com/Scene/[ID]_1200_630.jpg` (~344KB).\n- Listing 3's full photo set requires a live browser session on the Compass listing page; the virtual tour site is down."},{"type":"text","text":"agentId: acda02602c79918dd (use SendMessage with to: 'acda02602c79918dd' to continue this agent)\ntotal_tokens: 62945\ntool_uses: 69\nduration_ms: 467162"}]}]},"uuid":"15478bd6-88fe-496f-bfc7-fa5a3486ee87","timestamp":"2026-07-08T15:44:08.778Z","toolUseResult":{"status":"completed","prompt":"Browse richardfowlerrealtor.com to find Richard Fowler's current or recent property listings. I need:\n\n1. A list of 3 active or recently sold listings with their addresses, prices, beds/baths, and brief descriptions\n2. For each listing, find the listing photos/images — get the direct image URLs if possible so we can download them\n3. Any listing detail pages with property facts (sq ft, features, etc.)\n\nHis site is for a Cedar Park, TX REALTOR (Compass). Focus on residential listings with good photo sets (ideally 6+ photos per listing). \n\nReturn a structured list of the 3 best listings with: address, price, beds, baths, sq ft, description summary, and all the photo URLs you can find for each.","agentId":"acda02602c79918dd","agentType":"general-purpose","content":[{"type":"text","text":"The `big4` path gives ~950KB full-res JPEGs — significantly larger than the 1200x630 version (~344KB). Now I have everything needed. Here is the fully structured result:\n\n---\n\n## Richard Fowler (Compass, Cedar Park TX) — 3 Best Residential Listings\n\n---\n\n### Listing 1: 2605 Orsobello Pl, Cedar Park, TX 78613\n\n**Status:** Sold (11/24/2021)\n**Price:** $899,900\n**Beds/Baths:** 4 bed / 3.5 bath\n**Square Footage:** 3,243 sq ft\n**Lot Size:** 0.24 acres (10,585 sq ft)\n**Year Built:** 2004\n**Price/sq ft:** $277\n**Compass Listing:** https://www.compass.com/homedetails/2605-Orsobello-Pl-Cedar-Park-TX-78613/892704791158671745_lid/\n**Virtual Tour:** https://www.tourfactory.com/2924979\n\n**Description:** Contemporary Rustic Texan home in Bella Vista community with over $100K in upgrades. Features stone masonry, open-concept living, remodeled kitchen with quartz countertops, vaulted ceilings, gas fireplace, luxury owner's suite with garden soaking tub, game room, 3-car garage, multi-level Trex deck with hot tub, and greenbelt/creek views. Walking distance to Bella Vista Park, minutes from Lakeline Mall.\n\n**Photo URLs (43 photos, full-res JPEGs ~950KB each):**\n\nBase URL pattern: `https://www.tourfactory.com/media/scene/big4/[ID].jpg`\n\n```\nhttps://www.tourfactory.com/media/scene/big4/75341186.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341187.jpg ← hero/cover photo\nhttps://www.tourfactory.com/media/scene/big4/75341188.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341189.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341190.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341191.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341192.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341193.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341194.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341195.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341196.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341197.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341198.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341199.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341200.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341201.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341202.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341203.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341204.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341205.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341206.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341207.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341208.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341209.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341210.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341211.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341212.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341213.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341214.jpg\nhttps://www.tourfactory.com/media/scene/big4/75341215.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338561.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338562.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338563.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338564.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338565.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338566.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338570.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338571.jpg\nhttps://www.tourfactory.com/media/scene/big4/75338572.jpg\nhttps://www.tourfactory.com/media/scene/big4/75361795.jpg\nhttps://www.tourfactory.com/media/scene/big4/75361796.jpg\nhttps://www.tourfactory.com/media/scene/big4/75361797.jpg\nhttps://www.tourfactory.com/media/scene/big4/75361798.jpg\n```\n\nAlso available via Compass (cover photo only):\n- `https://www.compass.com/m/3b3fe93ca7e476478b56809e7f2ad23268f45ba12fabd96e28681a98d13f3c08/origin.jpg`\n\n---\n\n### Listing 2: 8 Hightrail Way, The Hills, TX 78738\n\n**Status:** Sold (3/21/2022)\n**Price:** $1,150,000\n**Beds/Baths:** 3 bed / 3 bath (2.5 full)\n**Square Footage:** 3,275 sq ft\n**Lot Size:** 0.16 acres (6,969 sq ft)\n**Year Built:** 2001\n**Stories:** 2\n**Price/sq ft:** $351\n**Compass Listing:** https://www.compass.com/homedetails/8-Hightrail-Way-The-Hills-TX-78738/984131746132131137_lid/\n**Virtual Tour:** https://www.tourfactory.com/2954124\n\n**Description:** Updated luxury home in The Hills of Lakeway (gated community). Over $150K in designer upgrades including whitewash oak hardwoods, bamboo and high-end tile flooring, LED recessed lighting, vaulted ceilings, granite-counter gourmet kitchen with island, wood-burning fireplace, updated primary suite with marble bath, upstairs family room with built-ins, home office, and 2-car garage. Near Hills Country Club, golf courses, and tennis facilities.\n\n**Photo URLs (37 photos, full-res JPEGs ~950KB each):**\n\nBase URL pattern: `https://www.tourfactory.com/media/scene/big4/[ID].jpg`\n\n```\nhttps://www.tourfactory.com/media/scene/big4/76228804.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228805.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228806.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228807.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228808.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228809.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228810.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228811.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228814.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228815.jpg ← hero/cover photo\nhttps://www.tourfactory.com/media/scene/big4/76228816.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228817.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228818.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228819.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228820.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228821.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228822.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228823.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228824.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228825.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228826.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228827.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228828.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228829.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228830.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228831.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228832.jpg\nhttps://www.tourfactory.com/media/scene/big4/76228833.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238053.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238054.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238055.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238056.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238057.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238058.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238059.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238060.jpg\nhttps://www.tourfactory.com/media/scene/big4/76238061.jpg\n```\n\nAlso available via Compass (cover photo only):\n- `https://www.compass.com/m/cf3d20d8381b6a84679cf9fb6b543244e3aade7789dd0462add18d4c96003e27/origin.webp`\n\n---\n\n### Listing 3: 3213 Herradura Dr, Leander, TX 78641\n\n**Status:** Sold (12/28/2023)\n**Price:** $895,000\n**Beds/Baths:** 4 bed / 3 bath\n**Square Footage:** 3,504 sq ft\n**Lot Size:** 0.22 acres (9,626 sq ft)\n**Year Built:** 2011\n**Price/sq ft:** $255\n**MLS #:** 2966211\n**Subdivision:** Caballo Ranch Sec 02\n**Compass Listing:** https://www.compass.com/homedetails/3213-Herradura-Dr-Leander-TX-78641/1364037881138127177_lid/\n**Virtual Tour:** http://www.3213herradura.com (site appears down/unreachable as of Jul 2026)\n\n**Description:** Captivating single-story home on a private lot in Caballo Ranch with Brushy Creek views. Over $100K in improvements: fresh paint, no carpet, wood-finished patio with outdoor kitchen, outdoor fireplace, gas log fireplace, floor-to-ceiling windows, soaring ceilings, curbless primary shower with quartz dual vanities, two walk-in closets, double ovens, kitchen island, 2-car garage, and wired for sound. 3-minute walk to community pool.\n\n**Photo URLs:**\n\nCompass cover photo (only one recoverable from static HTML — gallery is JS-rendered):\n```\nhttps://www.compass.com/m/5ce703f71f9f24742c747724c4234a7bc0d2853ef625cdddbf44c0022b206cfa/origin.jpg\nhttps://www.compass.com/m/5ce703f71f9f24742c747724c4234a7bc0d2853ef625cdddbf44c0022b206cfa/1500x1000.jpg\n```\n\nThe virtual tour domain (`3213herradura.com`) is currently unreachable, and Compass renders its full gallery via JavaScript which isn't accessible to static fetching. To get the complete photo set, the Compass listing detail page needs to be opened in a browser and the \"View All\" photos gallery loaded.\n\n---\n\n**Notes on photo access:**\n- Listings 1 and 2 have full photo sets (43 and 37 photos respectively) confirmed live at `https://www.tourfactory.com/media/scene/big4/[ID].jpg`. Each image is a full-resolution JPEG (~950KB).\n- The TourFactory `big4` path is the largest available size. A smaller 1200x630 version is also available at `https://media.tourfactory.com/Scene/[ID]_1200_630.jpg` (~344KB).\n- Listing 3's full photo set requires a live browser session on the Compass listing page; the virtual tour site is down."}],"totalDurationMs":467162,"totalTokens":62945,"totalToolUseCount":69,"usage":{"input_tokens":1,"cache_creation_input_tokens":455,"cache_read_input_tokens":59019,"output_tokens":3470,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":455},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":3470,"cache_read_input_tokens":59019,"cache_creation_input_tokens":455,"cache_creation":{"ephemeral_5m_input_tokens":455,"ephemeral_1h_input_tokens":0},"type":"message"}],"speed":"standard"},"toolStats":{"readCount":0,"searchCount":0,"bashCount":39,"editFileCount":0,"linesAdded":0,"linesRemoved":0,"otherToolCount":30}},"sourceToolAssistantUUID":"b82db34b-b390-4a8d-b9a7-f5633cfc170a","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"15478bd6-88fe-496f-bfc7-fa5a3486ee87","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Ccpr8A6jX8fUL2N1YEjds","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Excellent! I have everything I need. Let me now:\n\n1. The agent found 3 listings with photos:\n - **Listing 1**: 2605 Orsobello Pl, Cedar Park, TX — 4bd/3.5ba, 3243 sqft, $899,900 — 43 photos from TourFactory\n - **Listing 2**: 8 Hightrail Way, The Hills, TX — 3bd/3ba, 3275 sqft, $1,150,000 — 37 photos from TourFactory\n - **Listing 3**: 3213 Herradura Dr, Leander, TX — 4bd/3ba, 3504 sqft, $895,000 — only 1-2 photos recoverable (virtual tour down)\n\n2. I have the renderer code and need to understand what changes support 3 template styles. The key parameterizable elements I can adjust are the motion style (zoom increment and directional expressions) and transition effects (fade and other transition types).\n\nFor the three templates, I'm thinking: Essential keeps the current subtle approach with slow zooms and bottom captions, Feature Spotlight ramps up the motion intensity with faster zooms and center captions, and Branded goes slower with wider pans and branded elements. The main levers I'll pull are motion intensity through zoom and direction variants, plus different transition types like fade, wipeleft, or slideleft.\n\nNow I need to map out the actual implementation: download the photos for the first two listings, build out the manifests for all three, add template parameters to the workflow, create the three outro variants, and run everything through. I'll start by examining how `listing_graphics.py` generates the outro and cover images, then write a photo downloader, and finally wire up the template parameterization. For listing 3, I should try a different approach to get the photos since the Compass gallery needs JavaScript to load. Let me see if I can extract the cover photo URLs directly or find an alternative source, otherwise I'll use fewer photos for that listing or swap it out for another property with more accessible images. to get more photos for listing 3 through a browser session, then start building out the template code. First, I'll check the listing_graphics.py file to understand the 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"}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1669,"cache_creation_input_tokens":3898,"cache_read_input_tokens":58759,"output_tokens":1815,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3898,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1669,"output_tokens":1815,"cache_read_input_tokens":58759,"cache_creation_input_tokens":3898,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3898},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Ccpr88p6F6HVvZF7bmKXy","type":"assistant","uuid":"77de3b8a-2fea-4ea1-b434-e397a0177e38","timestamp":"2026-07-08T15:44:39.875Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"77de3b8a-2fea-4ea1-b434-e397a0177e38","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Ccpr8A6jX8fUL2N1YEjds","type":"message","role":"assistant","content":[{"type":"text","text":"Got the listings — two with full photo sets (43 and 37 photos each), plus a third to chase down. Let me read the graphics code and then start both tasks in parallel."}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1669,"cache_creation_input_tokens":3898,"cache_read_input_tokens":58759,"output_tokens":1815,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3898,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1669,"output_tokens":1815,"cache_read_input_tokens":58759,"cache_creation_input_tokens":3898,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3898},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Ccpr88p6F6HVvZF7bmKXy","type":"assistant","uuid":"dcc39dd3-3876-4994-b162-f53dc66542f0","timestamp":"2026-07-08T15:44:40.229Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"dcc39dd3-3876-4994-b162-f53dc66542f0","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Ccpr8A6jX8fUL2N1YEjds","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01GDCJkVCAJSKouvLdsY6VK7","name":"Bash","input":{"command":"cat /workspace/extra/projects/stagehand/core/media/listing_graphics.py"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1669,"cache_creation_input_tokens":3898,"cache_read_input_tokens":58759,"output_tokens":1815,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3898,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1669,"output_tokens":1815,"cache_read_input_tokens":58759,"cache_creation_input_tokens":3898,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3898},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Ccpr88p6F6HVvZF7bmKXy","type":"assistant","uuid":"3a2de1ab-0981-4765-b166-a56c14e08aea","timestamp":"2026-07-08T15:44:40.626Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"3a2de1ab-0981-4765-b166-a56c14e08aea","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01GDCJkVCAJSKouvLdsY6VK7","type":"tool_result","content":"from __future__ import annotations\n\nfrom pathlib import Path\nfrom typing import Iterable\n\nfrom PIL import Image, ImageDraw, ImageEnhance, ImageFilter, ImageFont\n\n\nclass ListingGraphicError(ValueError):\n pass\n\n\ndef create_listing_cover(\n source_photo: str | Path,\n output_path: str | Path,\n *,\n title: str,\n subtitle: str = \"\",\n price: str = \"\",\n focal_point: tuple[float, float] = (0.5, 0.5),\n width: int = 1080,\n height: int = 1681,\n) -> Path:\n if not title.strip():\n raise ListingGraphicError(\"Listing cover requires a title\")\n path = Path(output_path)\n path.parent.mkdir(parents=True, exist_ok=True)\n with Image.open(source_photo) as opened:\n background = _cover_crop(opened.convert(\"RGB\"), (width, height), focal_point)\n background = ImageEnhance.Contrast(background).enhance(1.05)\n background = ImageEnhance.Color(background).enhance(0.92)\n canvas = background.convert(\"RGBA\")\n shade = Image.new(\"RGBA\", canvas.size, (0, 0, 0, 0))\n shade_pixels = shade.load()\n start = int(height * 0.37)\n for y in range(start, height):\n alpha = int(28 + 185 * ((y - start) / max(1, height - start)))\n for x in range(width):\n shade_pixels[x, y] = (10, 18, 25, alpha)\n canvas = Image.alpha_composite(canvas, shade)\n draw = ImageDraw.Draw(canvas)\n\n margin = 88\n max_text_width = width - (margin * 2)\n title_font, title_lines = _fit_lines(draw, title, max_text_width, max_lines=3, start_size=84, min_size=44, bold=True)\n subtitle_font = _font(38, bold=False)\n price_font = _font(54, bold=True)\n y = int(height * 0.57)\n if price.strip():\n _draw_centered(draw, price.strip(), y, price_font, width, fill=(244, 204, 112, 255))\n y += 82\n for line in title_lines:\n _draw_centered(draw, line, y, title_font, width, fill=(255, 251, 242, 255), stroke=3)\n y += _line_height(draw, line, title_font) + 16\n if subtitle.strip():\n subtitle_lines = _wrap_by_width(draw, subtitle.strip(), subtitle_font, max_text_width, max_lines=3)\n y += 18\n for line in subtitle_lines:\n _draw_centered(draw, line, y, subtitle_font, width, fill=(235, 236, 232, 255), stroke=2)\n y += _line_height(draw, line, subtitle_font) + 12\n\n _save(canvas, path)\n return path\n\n\ndef create_contact_outro(\n output_path: str | Path,\n *,\n agent_name: str,\n cta: str,\n instagram_handle: str = \"\",\n phone: str = \"\",\n email: str = \"\",\n website: str = \"\",\n width: int = 1080,\n height: int = 1920,\n) -> Path:\n contacts = [value.strip() for value in (instagram_handle, phone, email, website) if value.strip()]\n if not contacts:\n raise ListingGraphicError(\"Contact outro requires at least one contact method\")\n if not agent_name.strip():\n raise ListingGraphicError(\"Contact outro requires an agent name\")\n path = Path(output_path)\n path.parent.mkdir(parents=True, exist_ok=True)\n\n canvas = Image.new(\"RGBA\", (width, height), (14, 26, 36, 255))\n glow = Image.new(\"RGBA\", canvas.size, (0, 0, 0, 0))\n glow_draw = ImageDraw.Draw(glow)\n glow_draw.ellipse((-320, -180, 760, 900), fill=(44, 92, 104, 115))\n glow_draw.ellipse((520, 1150, 1370, 2100), fill=(138, 94, 51, 70))\n canvas = Image.alpha_composite(canvas, glow.filter(ImageFilter.GaussianBlur(120)))\n draw = ImageDraw.Draw(canvas)\n\n accent = (235, 187, 89, 255)\n cream = (255, 249, 238, 255)\n muted = (207, 216, 216, 255)\n draw.rounded_rectangle((90, 170, 990, 1750), radius=52, outline=(255, 255, 255, 38), width=2, fill=(8, 17, 25, 105))\n draw.rectangle((150, 300, 270, 312), fill=accent)\n\n label_font = _font(32, bold=True)\n name_font, name_lines = _fit_lines(draw, agent_name, 770, max_lines=2, start_size=78, min_size=46, bold=True)\n cta_font, cta_lines = _fit_lines(draw, cta or \"Schedule a private tour\", 770, max_lines=3, start_size=52, min_size=36, bold=False)\n contact_font = _font(34, bold=False)\n\n draw.text((150, 350), \"YOUR LOCAL REAL ESTATE CONTACT\", font=label_font, fill=accent)\n y = 465\n for line in name_lines:\n draw.text((150, y), line, font=name_font, fill=cream)\n y += _line_height(draw, line, name_font) + 16\n y += 80\n for line in cta_lines:\n draw.text((150, y), line, font=cta_font, fill=cream)\n y += _line_height(draw, line, cta_font) + 14\n y += 100\n draw.rectangle((150, y, 930, y + 2), fill=(255, 255, 255, 45))\n y += 62\n for contact in contacts:\n for line in _wrap_by_width(draw, contact, contact_font, 760, max_lines=2):\n draw.text((150, y), line, font=contact_font, fill=muted)\n y += _line_height(draw, line, contact_font) + 18\n y += 12\n\n _save(canvas, path)\n return path\n\n\ndef _cover_crop(image: Image.Image, size: tuple[int, int], focal_point: tuple[float, float]) -> Image.Image:\n width, height = size\n fx, fy = focal_point\n if not 0 <= fx <= 1 or not 0 <= fy <= 1:\n raise ListingGraphicError(\"Focal point values must be between 0 and 1\")\n scale = max(width / image.width, height / image.height)\n resized_size = (max(width, round(image.width * scale)), max(height, round(image.height * scale)))\n resized = image.resize(resized_size, Image.Resampling.LANCZOS)\n left = min(max(0, round((resized.width * fx) - (width / 2))), resized.width - width)\n top = min(max(0, round((resized.height * fy) - (height / 2))), resized.height - height)\n return resized.crop((left, top, left + width, top + height))\n\n\ndef _font(size: int, *, bold: bool) -> ImageFont.ImageFont:\n candidates: Iterable[str] = (\n \"/System/Library/Fonts/Supplemental/Arial Bold.ttf\" if bold else \"/System/Library/Fonts/Supplemental/Arial.ttf\",\n \"/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf\" if bold else \"/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf\",\n )\n for candidate in candidates:\n if Path(candidate).exists():\n return ImageFont.truetype(candidate, size)\n return ImageFont.load_default(size=size)\n\n\ndef _fit_lines(\n draw: ImageDraw.ImageDraw,\n text: str,\n max_width: int,\n *,\n max_lines: int,\n start_size: int,\n min_size: int,\n bold: bool,\n) -> tuple[ImageFont.ImageFont, list[str]]:\n for size in range(start_size, min_size - 1, -2):\n font = _font(size, bold=bold)\n lines = _wrap_by_width(draw, text, font, max_width, max_lines=max_lines)\n if len(lines) <= max_lines and all(_text_width(draw, line, font) <= max_width for line in lines):\n return font, lines\n font = _font(min_size, bold=bold)\n return font, _wrap_by_width(draw, text, font, max_width, max_lines=max_lines)\n\n\ndef _wrap_by_width(\n draw: ImageDraw.ImageDraw,\n text: str,\n font: ImageFont.ImageFont,\n max_width: int,\n *,\n max_lines: int,\n) -> list[str]:\n words = \" \".join(text.split()).split()\n lines: list[str] = []\n current = \"\"\n for word in words:\n candidate = f\"{current} {word}\".strip()\n if current and _text_width(draw, candidate, font) > max_width:\n lines.append(current)\n current = word\n else:\n current = candidate\n if current:\n lines.append(current)\n if len(lines) > max_lines:\n lines = lines[:max_lines]\n lines[-1] = lines[-1].rstrip(\". \") + \"…\"\n while _text_width(draw, lines[-1], font) > max_width and len(lines[-1]) > 2:\n lines[-1] = lines[-1][:-2].rstrip() + \"…\"\n return lines or [\"\"]\n\n\ndef _draw_centered(\n draw: ImageDraw.ImageDraw,\n text: str,\n y: int,\n font: ImageFont.ImageFont,\n width: int,\n *,\n fill: tuple[int, int, int, int],\n stroke: int = 0,\n) -> None:\n bbox = draw.textbbox((0, 0), text, font=font, stroke_width=stroke)\n x = (width - (bbox[2] - bbox[0])) // 2\n draw.text((x, y), text, font=font, fill=fill, stroke_width=stroke, stroke_fill=(0, 0, 0, 150))\n\n\ndef _text_width(draw: ImageDraw.ImageDraw, text: str, font: ImageFont.ImageFont) -> int:\n bbox = draw.textbbox((0, 0), text, font=font)\n return bbox[2] - bbox[0]\n\n\ndef _line_height(draw: ImageDraw.ImageDraw, text: str, font: ImageFont.ImageFont) -> int:\n bbox = draw.textbbox((0, 0), text or \"Ag\", font=font)\n return bbox[3] - bbox[1]\n\n\ndef _save(image: Image.Image, path: Path) -> None:\n if path.suffix.lower() in {\".jpg\", \".jpeg\"}:\n image.convert(\"RGB\").save(path, quality=92, optimize=True)\n else:\n image.save(path)","is_error":false}]},"uuid":"6277271a-9589-4a55-bdb0-994c73324db2","timestamp":"2026-07-08T15:44:40.655Z","toolUseResult":{"stdout":"from __future__ import annotations\n\nfrom pathlib import Path\nfrom typing import Iterable\n\nfrom PIL import Image, ImageDraw, ImageEnhance, ImageFilter, ImageFont\n\n\nclass ListingGraphicError(ValueError):\n pass\n\n\ndef create_listing_cover(\n source_photo: str | Path,\n output_path: str | Path,\n *,\n title: str,\n subtitle: str = \"\",\n price: str = \"\",\n focal_point: tuple[float, float] = (0.5, 0.5),\n width: int = 1080,\n height: int = 1681,\n) -> Path:\n if not title.strip():\n raise ListingGraphicError(\"Listing cover requires a title\")\n path = Path(output_path)\n path.parent.mkdir(parents=True, exist_ok=True)\n with Image.open(source_photo) as opened:\n background = _cover_crop(opened.convert(\"RGB\"), (width, height), focal_point)\n background = ImageEnhance.Contrast(background).enhance(1.05)\n background = ImageEnhance.Color(background).enhance(0.92)\n canvas = background.convert(\"RGBA\")\n shade = Image.new(\"RGBA\", canvas.size, (0, 0, 0, 0))\n shade_pixels = shade.load()\n start = int(height * 0.37)\n for y in range(start, height):\n alpha = int(28 + 185 * ((y - start) / max(1, height - start)))\n for x in range(width):\n shade_pixels[x, y] = (10, 18, 25, alpha)\n canvas = Image.alpha_composite(canvas, shade)\n draw = ImageDraw.Draw(canvas)\n\n margin = 88\n max_text_width = width - (margin * 2)\n title_font, title_lines = _fit_lines(draw, title, max_text_width, max_lines=3, start_size=84, min_size=44, bold=True)\n subtitle_font = _font(38, bold=False)\n price_font = _font(54, bold=True)\n y = int(height * 0.57)\n if price.strip():\n _draw_centered(draw, price.strip(), y, price_font, width, fill=(244, 204, 112, 255))\n y += 82\n for line in title_lines:\n _draw_centered(draw, line, y, title_font, width, fill=(255, 251, 242, 255), stroke=3)\n y += _line_height(draw, line, title_font) + 16\n if subtitle.strip():\n subtitle_lines = _wrap_by_width(draw, subtitle.strip(), subtitle_font, max_text_width, max_lines=3)\n y += 18\n for line in subtitle_lines:\n _draw_centered(draw, line, y, subtitle_font, width, fill=(235, 236, 232, 255), stroke=2)\n y += _line_height(draw, line, subtitle_font) + 12\n\n _save(canvas, path)\n return path\n\n\ndef create_contact_outro(\n output_path: str | Path,\n *,\n agent_name: str,\n cta: str,\n instagram_handle: str = \"\",\n phone: str = \"\",\n email: str = \"\",\n website: str = \"\",\n width: int = 1080,\n height: int = 1920,\n) -> Path:\n contacts = [value.strip() for value in (instagram_handle, phone, email, website) if value.strip()]\n if not contacts:\n raise ListingGraphicError(\"Contact outro requires at least one contact method\")\n if not agent_name.strip():\n raise ListingGraphicError(\"Contact outro requires an agent name\")\n path = Path(output_path)\n path.parent.mkdir(parents=True, exist_ok=True)\n\n canvas = Image.new(\"RGBA\", (width, height), (14, 26, 36, 255))\n glow = Image.new(\"RGBA\", canvas.size, (0, 0, 0, 0))\n glow_draw = ImageDraw.Draw(glow)\n glow_draw.ellipse((-320, -180, 760, 900), fill=(44, 92, 104, 115))\n glow_draw.ellipse((520, 1150, 1370, 2100), fill=(138, 94, 51, 70))\n canvas = Image.alpha_composite(canvas, glow.filter(ImageFilter.GaussianBlur(120)))\n draw = ImageDraw.Draw(canvas)\n\n accent = (235, 187, 89, 255)\n cream = (255, 249, 238, 255)\n muted = (207, 216, 216, 255)\n draw.rounded_rectangle((90, 170, 990, 1750), radius=52, outline=(255, 255, 255, 38), width=2, fill=(8, 17, 25, 105))\n draw.rectangle((150, 300, 270, 312), fill=accent)\n\n label_font = _font(32, bold=True)\n name_font, name_lines = _fit_lines(draw, agent_name, 770, max_lines=2, start_size=78, min_size=46, bold=True)\n cta_font, cta_lines = _fit_lines(draw, cta or \"Schedule a private tour\", 770, max_lines=3, start_size=52, min_size=36, bold=False)\n contact_font = _font(34, bold=False)\n\n draw.text((150, 350), \"YOUR LOCAL REAL ESTATE CONTACT\", font=label_font, fill=accent)\n y = 465\n for line in name_lines:\n draw.text((150, y), line, font=name_font, fill=cream)\n y += _line_height(draw, line, name_font) + 16\n y += 80\n for line in cta_lines:\n draw.text((150, y), line, font=cta_font, fill=cream)\n y += _line_height(draw, line, cta_font) + 14\n y += 100\n draw.rectangle((150, y, 930, y + 2), fill=(255, 255, 255, 45))\n y += 62\n for contact in contacts:\n for line in _wrap_by_width(draw, contact, contact_font, 760, max_lines=2):\n draw.text((150, y), line, font=contact_font, fill=muted)\n y += _line_height(draw, line, contact_font) + 18\n y += 12\n\n _save(canvas, path)\n return path\n\n\ndef _cover_crop(image: Image.Image, size: tuple[int, int], focal_point: tuple[float, float]) -> Image.Image:\n width, height = size\n fx, fy = focal_point\n if not 0 <= fx <= 1 or not 0 <= fy <= 1:\n raise ListingGraphicError(\"Focal point values must be between 0 and 1\")\n scale = max(width / image.width, height / image.height)\n resized_size = (max(width, round(image.width * scale)), max(height, round(image.height * scale)))\n resized = image.resize(resized_size, Image.Resampling.LANCZOS)\n left = min(max(0, round((resized.width * fx) - (width / 2))), resized.width - width)\n top = min(max(0, round((resized.height * fy) - (height / 2))), resized.height - height)\n return resized.crop((left, top, left + width, top + height))\n\n\ndef _font(size: int, *, bold: bool) -> ImageFont.ImageFont:\n candidates: Iterable[str] = (\n \"/System/Library/Fonts/Supplemental/Arial Bold.ttf\" if bold else \"/System/Library/Fonts/Supplemental/Arial.ttf\",\n \"/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf\" if bold else \"/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf\",\n )\n for candidate in candidates:\n if Path(candidate).exists():\n return ImageFont.truetype(candidate, size)\n return ImageFont.load_default(size=size)\n\n\ndef _fit_lines(\n draw: ImageDraw.ImageDraw,\n text: str,\n max_width: int,\n *,\n max_lines: int,\n start_size: int,\n min_size: int,\n bold: bool,\n) -> tuple[ImageFont.ImageFont, list[str]]:\n for size in range(start_size, min_size - 1, -2):\n font = _font(size, bold=bold)\n lines = _wrap_by_width(draw, text, font, max_width, max_lines=max_lines)\n if len(lines) <= max_lines and all(_text_width(draw, line, font) <= max_width for line in lines):\n return font, lines\n font = _font(min_size, bold=bold)\n return font, _wrap_by_width(draw, text, font, max_width, max_lines=max_lines)\n\n\ndef _wrap_by_width(\n draw: ImageDraw.ImageDraw,\n text: str,\n font: ImageFont.ImageFont,\n max_width: int,\n *,\n max_lines: int,\n) -> list[str]:\n words = \" \".join(text.split()).split()\n lines: list[str] = []\n current = \"\"\n for word in words:\n candidate = f\"{current} {word}\".strip()\n if current and _text_width(draw, candidate, font) > max_width:\n lines.append(current)\n current = word\n else:\n current = candidate\n if current:\n lines.append(current)\n if len(lines) > max_lines:\n lines = lines[:max_lines]\n lines[-1] = lines[-1].rstrip(\". \") + \"…\"\n while _text_width(draw, lines[-1], font) > max_width and len(lines[-1]) > 2:\n lines[-1] = lines[-1][:-2].rstrip() + \"…\"\n return lines or [\"\"]\n\n\ndef _draw_centered(\n draw: ImageDraw.ImageDraw,\n text: str,\n y: int,\n font: ImageFont.ImageFont,\n width: int,\n *,\n fill: tuple[int, int, int, int],\n stroke: int = 0,\n) -> None:\n bbox = draw.textbbox((0, 0), text, font=font, stroke_width=stroke)\n x = (width - (bbox[2] - bbox[0])) // 2\n draw.text((x, y), text, font=font, fill=fill, stroke_width=stroke, stroke_fill=(0, 0, 0, 150))\n\n\ndef _text_width(draw: ImageDraw.ImageDraw, text: str, font: ImageFont.ImageFont) -> int:\n bbox = draw.textbbox((0, 0), text, font=font)\n return bbox[2] - bbox[0]\n\n\ndef _line_height(draw: ImageDraw.ImageDraw, text: str, font: ImageFont.ImageFont) -> int:\n bbox = draw.textbbox((0, 0), text or \"Ag\", font=font)\n return bbox[3] - bbox[1]\n\n\ndef _save(image: Image.Image, path: Path) -> None:\n if path.suffix.lower() in {\".jpg\", \".jpeg\"}:\n image.convert(\"RGB\").save(path, quality=92, optimize=True)\n else:\n image.save(path)","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"3a2de1ab-0981-4765-b166-a56c14e08aea","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"6277271a-9589-4a55-bdb0-994c73324db2","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011Ccpr8A6jX8fUL2N1YEjds","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01JDxVgHrQ2PVYTPsqgwmLbZ","name":"Agent","input":{"description":"Get photos for 3213 Herradura Dr listing via browser","subagent_type":"general-purpose","prompt":"I need photos from a specific real estate listing. Please browse to this Compass listing page and extract all the listing photo URLs:\n\nhttps://www.compass.com/homedetails/3213-Herradura-Dr-Leander-TX-78641/1364037881138127177_lid/\n\nOpen the page fully, click to view all photos if needed, and collect all the image URLs shown in the gallery. I need at least 6 high-resolution photo URLs. \n\nIf Compass doesn't work well, also try searching for \"3213 Herradura Dr Leander TX 78641 listing photos\" to find the photos on Zillow, Redfin, or any other real estate site.\n\nThe property is a 4 bed/3 bath, 3504 sqft home sold in December 2023 for $895,000 in Leander TX (Caballo Ranch subdivision).\n\nReturn all the photo URLs you find, as many as possible (ideally 8+)."},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1669,"cache_creation_input_tokens":3898,"cache_read_input_tokens":58759,"output_tokens":1815,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":3898,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1669,"output_tokens":1815,"cache_read_input_tokens":58759,"cache_creation_input_tokens":3898,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3898},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Ccpr88p6F6HVvZF7bmKXy","type":"assistant","uuid":"7a6ed186-a363-40ca-ac41-34f601b2a345","timestamp":"2026-07-08T15:44:46.701Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"type":"last-prompt","leafUuid":"7a6ed186-a363-40ca-ac41-34f601b2a345","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}
{"type":"ai-title","aiTitle":"Review competitive analysis documentation","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}
{"parentUuid":"7a6ed186-a363-40ca-ac41-34f601b2a345","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JDxVgHrQ2PVYTPsqgwmLbZ","type":"tool_result","content":[{"type":"text","text":"All URLs are live and returning 200 OK JPEGs. Here are all 18 listing photo URLs for 3213 Herradura Dr, Leander TX 78641:\n\n---\n\n**All 18 listing photos found** — extracted from Compass's CDN via the listing agent's profile page. All URLs return 200 OK, full-resolution JPEGs (1.3MB+).\n\n**Photo URLs (all high-res, origin.jpg format):**\n\n1. `https://www.compass.com/m/5ce703f71f9f24742c747724c4234a7bc0d2853ef625cdddbf44c0022b206cfa/origin.jpg`\n — Sprawling, single-story home on private, shaded lot\n\n2. `https://www.compass.com/m/bb94219b52555b9a54c7abaaee0cdb32f4b8df3b992aad4f5cefd0bf671c860d/origin.jpg`\n — Custom wood front door with rain glass is welcoming and timeless\n\n3. `https://www.compass.com/m/addbd1b4c5dcf9c1af1978d9fd431ebe8ea0896fd652cb543e08f5758f460dbb/origin.jpg`\n — Oversized living area with lovely views into a private backyard\n\n4. `https://www.compass.com/m/b3b5d30e315540709838ad319eb3d421d9d32837ba5520c21031a4903423f64a/origin.jpg`\n\n5. `https://www.compass.com/m/85dcc6101fe5477245654690ea77fa3d351517af834ee86924624b67111efec6/origin.jpg`\n — The solid, center island provides excellent, 360° prep space\n\n6. `https://www.compass.com/m/bf2f42d2d9ad022dc730c2ec60a31403af83e1b824ba3ba04a847dcd53056e6f/origin.jpg`\n — Tray ceilings in dining room and updated chandelier\n\n7. `https://www.compass.com/m/24f0152a82aa2391c13dfef5e54acf45de9143f44ac7fd2622199433bb890887/origin.jpg`\n — Primary bedroom has direct access to the fabulous outdoor patio\n\n8. `https://www.compass.com/m/5da380092871bfa93f31d7c7f3d218247a231e6666a1681a05f737f2f458125e/origin.jpg`\n — Meticulously remodeled with new vanities, tile, and shiplap\n\n9. `https://www.compass.com/m/14a1f5f81f8d20fc8855d3813696a2e04bc4c9d58a857c3016db095c238a39e4/origin.jpg`\n — One of two walk-in closets in the primary bath\n\n10. `https://www.compass.com/m/8f8075bd754e42aff2bfc89210bdfe2298a9c23abc344f7a479b03fc549c6e0e/origin.jpg`\n\n11. `https://www.compass.com/m/cc2a4df6977c4acca5cba801e0477076150c63512198b564e9e7216a443116d2/origin.jpg`\n — Second bedroom with walk-in closet\n\n12. `https://www.compass.com/m/019e34cb7aaba8d7c3a9e6abb78c03e36ef3d455679f83d6ca56cdd9f37ac017/origin.jpg`\n — A very spacious fourth bedroom\n\n13. `https://www.compass.com/m/698f8198262e234518ba1911a7011ec45bb800c3ecd21f9d6c01c87ba6ba3222/origin.jpg`\n — Convenient half bath\n\n14. `https://www.compass.com/m/9b98d935b874a11329b648f10bf5c3afd4fc599114ee9a9b9337497368ef5667/origin.jpg`\n — Dedicated office space for modern living\n\n15. `https://www.compass.com/m/5b49430fe052d1beda6cb5c53d020b2447d8be17172df01faf0bbf1736396181/origin.jpg`\n — An expansive patio with gas fireplace and outdoor kitchen offers year-round enjoyment\n\n16. `https://www.compass.com/m/efd039866e99090d936abf9db929ac7bd3c6e8f3d2c4ff41f791a93980e561fa/origin.jpg`\n — Enjoy lovely views of nature with no neighbors to the back\n\n17. `https://www.compass.com/m/27b8214cdaa1bfbd2f39d3d1f48168e6c613ce10d9eae0a92009c7b533a7ef80/origin.jpg`\n\n18. `https://www.compass.com/m/1aca5f4a9ada5eaf79f39419a38cb712bca8597706519837bfbe2df569f46385/origin.jpg`\n — Caballo Ranch community playground\n\n**How these were found:** Compass's listing detail page only SSRs one photo. The full media array was discovered in the listing agent (Richard Fowler) profile page at compass.com, which embeds the full listing JSON including all 18 `originalUrl` fields. Each URL is a full-resolution JPEG (~640KB–1.3MB) served directly from Compass's CDN with no auth required."},{"type":"text","text":"agentId: ae435fdd5817785d3 (use SendMessage with to: 'ae435fdd5817785d3' to continue this agent)\ntotal_tokens: 99464\ntool_uses: 74\nduration_ms: 498340"}]}]},"uuid":"ba6f80a9-0dd1-4137-be66-4f279c0a92b4","timestamp":"2026-07-08T15:53:05.061Z","toolUseResult":{"status":"completed","prompt":"I need photos from a specific real estate listing. Please browse to this Compass listing page and extract all the listing photo URLs:\n\nhttps://www.compass.com/homedetails/3213-Herradura-Dr-Leander-TX-78641/1364037881138127177_lid/\n\nOpen the page fully, click to view all photos if needed, and collect all the image URLs shown in the gallery. I need at least 6 high-resolution photo URLs. \n\nIf Compass doesn't work well, also try searching for \"3213 Herradura Dr Leander TX 78641 listing photos\" to find the photos on Zillow, Redfin, or any other real estate site.\n\nThe property is a 4 bed/3 bath, 3504 sqft home sold in December 2023 for $895,000 in Leander TX (Caballo Ranch subdivision).\n\nReturn all the photo URLs you find, as many as possible (ideally 8+).","agentId":"ae435fdd5817785d3","agentType":"general-purpose","content":[{"type":"text","text":"All URLs are live and returning 200 OK JPEGs. Here are all 18 listing photo URLs for 3213 Herradura Dr, Leander TX 78641:\n\n---\n\n**All 18 listing photos found** — extracted from Compass's CDN via the listing agent's profile page. All URLs return 200 OK, full-resolution JPEGs (1.3MB+).\n\n**Photo URLs (all high-res, origin.jpg format):**\n\n1. `https://www.compass.com/m/5ce703f71f9f24742c747724c4234a7bc0d2853ef625cdddbf44c0022b206cfa/origin.jpg`\n — Sprawling, single-story home on private, shaded lot\n\n2. `https://www.compass.com/m/bb94219b52555b9a54c7abaaee0cdb32f4b8df3b992aad4f5cefd0bf671c860d/origin.jpg`\n — Custom wood front door with rain glass is welcoming and timeless\n\n3. `https://www.compass.com/m/addbd1b4c5dcf9c1af1978d9fd431ebe8ea0896fd652cb543e08f5758f460dbb/origin.jpg`\n — Oversized living area with lovely views into a private backyard\n\n4. `https://www.compass.com/m/b3b5d30e315540709838ad319eb3d421d9d32837ba5520c21031a4903423f64a/origin.jpg`\n\n5. `https://www.compass.com/m/85dcc6101fe5477245654690ea77fa3d351517af834ee86924624b67111efec6/origin.jpg`\n — The solid, center island provides excellent, 360° prep space\n\n6. `https://www.compass.com/m/bf2f42d2d9ad022dc730c2ec60a31403af83e1b824ba3ba04a847dcd53056e6f/origin.jpg`\n — Tray ceilings in dining room and updated chandelier\n\n7. `https://www.compass.com/m/24f0152a82aa2391c13dfef5e54acf45de9143f44ac7fd2622199433bb890887/origin.jpg`\n — Primary bedroom has direct access to the fabulous outdoor patio\n\n8. `https://www.compass.com/m/5da380092871bfa93f31d7c7f3d218247a231e6666a1681a05f737f2f458125e/origin.jpg`\n — Meticulously remodeled with new vanities, tile, and shiplap\n\n9. `https://www.compass.com/m/14a1f5f81f8d20fc8855d3813696a2e04bc4c9d58a857c3016db095c238a39e4/origin.jpg`\n — One of two walk-in closets in the primary bath\n\n10. `https://www.compass.com/m/8f8075bd754e42aff2bfc89210bdfe2298a9c23abc344f7a479b03fc549c6e0e/origin.jpg`\n\n11. `https://www.compass.com/m/cc2a4df6977c4acca5cba801e0477076150c63512198b564e9e7216a443116d2/origin.jpg`\n — Second bedroom with walk-in closet\n\n12. `https://www.compass.com/m/019e34cb7aaba8d7c3a9e6abb78c03e36ef3d455679f83d6ca56cdd9f37ac017/origin.jpg`\n — A very spacious fourth bedroom\n\n13. `https://www.compass.com/m/698f8198262e234518ba1911a7011ec45bb800c3ecd21f9d6c01c87ba6ba3222/origin.jpg`\n — Convenient half bath\n\n14. `https://www.compass.com/m/9b98d935b874a11329b648f10bf5c3afd4fc599114ee9a9b9337497368ef5667/origin.jpg`\n — Dedicated office space for modern living\n\n15. `https://www.compass.com/m/5b49430fe052d1beda6cb5c53d020b2447d8be17172df01faf0bbf1736396181/origin.jpg`\n — An expansive patio with gas fireplace and outdoor kitchen offers year-round enjoyment\n\n16. `https://www.compass.com/m/efd039866e99090d936abf9db929ac7bd3c6e8f3d2c4ff41f791a93980e561fa/origin.jpg`\n — Enjoy lovely views of nature with no neighbors to the back\n\n17. `https://www.compass.com/m/27b8214cdaa1bfbd2f39d3d1f48168e6c613ce10d9eae0a92009c7b533a7ef80/origin.jpg`\n\n18. `https://www.compass.com/m/1aca5f4a9ada5eaf79f39419a38cb712bca8597706519837bfbe2df569f46385/origin.jpg`\n — Caballo Ranch community playground\n\n**How these were found:** Compass's listing detail page only SSRs one photo. The full media array was discovered in the listing agent (Richard Fowler) profile page at compass.com, which embeds the full listing JSON including all 18 `originalUrl` fields. Each URL is a full-resolution JPEG (~640KB–1.3MB) served directly from Compass's CDN with no auth required."}],"totalDurationMs":498340,"totalTokens":99464,"totalToolUseCount":74,"usage":{"input_tokens":1,"cache_creation_input_tokens":598,"cache_read_input_tokens":97439,"output_tokens":1426,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":598},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":1426,"cache_read_input_tokens":97439,"cache_creation_input_tokens":598,"cache_creation":{"ephemeral_5m_input_tokens":598,"ephemeral_1h_input_tokens":0},"type":"message"}],"speed":"standard"},"toolStats":{"readCount":0,"searchCount":0,"bashCount":62,"editFileCount":0,"linesAdded":0,"linesRemoved":0,"otherToolCount":12}},"sourceToolAssistantUUID":"7a6ed186-a363-40ca-ac41-34f601b2a345","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
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{"parentUuid":"92c75fe1-eeba-443f-a2bc-988bee4f83a7","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcprojqLURr5TM8GBa27L","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Excellent! Now I have all 3 listings with photos:\n- Listing 1: 2605 Orsobello Pl, Cedar Park — 43 photos from TourFactory\n- Listing 2: 8 Hightrail Way, The Hills — 37 photos from TourFactory \n- Listing 3: 3213 Herradura Dr, Leander — 18 photos from Compass CDN\n\nNow I need to:\n1. Download photos for all 3 listings (select best 8-10 each)\n2. Add template parameterization to the renderer\n3. Create 3 manifests and run the listing reels\n\nI'm planning three distinct template styles. The first will be \"Essential\" with subtle pans and slow zooms, natural pacing around 5 seconds per photo, crossfade transitions, and bottom captions—keeping it understated and around 30 seconds with 6 photos. The second template, \"Feature Spotlight,\" will be more dynamic with faster zoom effects and kinetic movement to really showcase the property details.\n\nThe third template, \"Branded Showcase,\" takes a cinematic approach with slower, more deliberate motion, longer scene durations, fade transitions, and branded accent colors in the captions and outro to match the compass branding aesthetic.\n\nNow I need to modify the code to accept a template parameter in the build function so each manifest can specify which style to use. Now I'm mapping out which template goes with each listing: Cedar Park gets the Essential template, The Hills gets Feature Spotlight, and Leander gets the Branded one. I need to write a script to pull down the photos, update the renderer to handle template parameters, generate the manifests, and create a run script that orchestrates everything. Let me first examine the listing_reel_modules.py to see how parameters get passed through to the renderer, and check what's already in the input directory to understand the current job structure.","signature":"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"}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":8165,"cache_read_input_tokens":62657,"output_tokens":1092,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":8165,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":1092,"cache_read_input_tokens":62657,"cache_creation_input_tokens":8165,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":8165},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcprofmmFMAUPLyNCwAhg","type":"assistant","uuid":"1f045c26-bcfe-4c7c-b07d-043aefb55a56","timestamp":"2026-07-08T15:53:31.556Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"1f045c26-bcfe-4c7c-b07d-043aefb55a56","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcprojqLURr5TM8GBa27L","type":"message","role":"assistant","content":[{"type":"text","text":"All 3 listings covered with photos. Now let me read the workflow modules and plan the template implementation."}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":8165,"cache_read_input_tokens":62657,"output_tokens":1092,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":8165,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":1092,"cache_read_input_tokens":62657,"cache_creation_input_tokens":8165,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":8165},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcprofmmFMAUPLyNCwAhg","type":"assistant","uuid":"3dc9c4a5-99db-4362-91c7-13c7ce96ade1","timestamp":"2026-07-08T15:53:31.557Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"3dc9c4a5-99db-4362-91c7-13c7ce96ade1","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcprojqLURr5TM8GBa27L","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01AetLQawHYnhP87ZZLaaE1v","name":"Bash","input":{"command":"cat /workspace/extra/projects/stagehand/core/workflows/listing_reel_modules.py && echo \"===\" && head -80 /workspace/extra/projects/stagehand/core/workflows/modules.py"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":8165,"cache_read_input_tokens":62657,"output_tokens":1092,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":8165,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":1092,"cache_read_input_tokens":62657,"cache_creation_input_tokens":8165,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":8165},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcprofmmFMAUPLyNCwAhg","type":"assistant","uuid":"f5c61dfe-5251-41eb-92e8-dff5aa285354","timestamp":"2026-07-08T15:53:32.345Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"f5c61dfe-5251-41eb-92e8-dff5aa285354","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AetLQawHYnhP87ZZLaaE1v","type":"tool_result","content":"from __future__ import annotations\n\nimport json\nfrom pathlib import Path\n\nfrom core.listings.manifest import listing_snapshot_from_dict, load_listing_source, source_policy_for\nfrom core.listings.models import AgentProfile\nfrom core.listings.review import build_review_bundle, parse_approved_review, snapshot_digest\nfrom core.media.ffmpeg_utils import probe_media\nfrom core.media.listing_graphics import create_contact_outro, create_listing_cover\nfrom core.media.photo_reel import build_photo_reel_command, run_photo_reel\nfrom core.workflows.runner import WorkflowContext\n\n\nclass ListingIntakeModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n listing_url = str(context.data.get(\"listing_url\") or \"\")\n manifest_path = context.data.get(\"listing_manifest_path\")\n media_root = str(context.data.get(\"listing_media_root\") or Path(str(manifest_path)).parent)\n snapshot = load_listing_source(\n listing_url,\n manifest_path=manifest_path,\n media_root=media_root,\n )\n snapshot_path = context.workspace / \"listing_snapshot.json\"\n snapshot_path.write_text(json.dumps(snapshot.to_dict(), indent=2), encoding=\"utf-8\")\n return {\n \"listing_snapshot_path\": str(snapshot_path),\n \"listing_snapshot_sha256\": snapshot_digest(snapshot),\n \"listing_media_root\": media_root,\n \"listing_source_policy\": source_policy_for(listing_url).value,\n }\n\n\nclass ListingReviewDraftModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n snapshot = _load_snapshot(context)\n agent = AgentProfile.from_mapping(\n {\n \"name\": context.data.get(\"agent_name\"),\n \"instagram_handle\": context.data.get(\"agent_instagram_handle\"),\n \"phone\": context.data.get(\"agent_phone\"),\n \"email\": context.data.get(\"agent_email\"),\n \"website\": context.data.get(\"agent_website\"),\n \"voice_owner\": context.data.get(\"voice_owner\"),\n }\n )\n bundle = build_review_bundle(\n snapshot,\n agent,\n target_duration_seconds=float(\n context.data.get(\"target_duration_seconds\")\n or params.get(\"target_duration_seconds\", 30)\n ),\n )\n draft = json.dumps(bundle, indent=2)\n draft_path = context.workspace / \"listing_review_draft.json\"\n draft_path.write_text(draft, encoding=\"utf-8\")\n return {\n \"generated_script\": draft,\n \"listing_review_draft_path\": str(draft_path),\n }\n\n\nclass ListingReviewApprovalModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n snapshot = _load_snapshot(context)\n approved = parse_approved_review(\n str(context.data.get(\"approved_script\") or \"\"),\n snapshot,\n media_root=context.data[\"listing_media_root\"],\n )\n approved_path = context.workspace / \"approved_listing_reel.normalized.json\"\n approved_payload = {\n \"narration\": approved.narration,\n \"instagram_caption\": approved.instagram_caption,\n \"photo_order\": [photo.relative_path for photo in approved.photos],\n \"cover_photo_path\": approved.cover_photo.relative_path,\n \"outro\": approved.outro,\n \"target_duration_seconds\": approved.target_duration_seconds,\n }\n approved_path.write_text(json.dumps(approved_payload, indent=2), encoding=\"utf-8\")\n return {\n \"approved_narration\": approved.narration,\n \"approved_caption\": approved.instagram_caption,\n \"approved_photo_paths\": [str(photo.path) for photo in approved.photos],\n \"approved_cover_photo_path\": str(approved.cover_photo.path),\n \"approved_outro\": approved.outro,\n \"target_duration_seconds\": approved.target_duration_seconds,\n \"approved_listing_reel_path\": str(approved_path),\n }\n\n\nclass ListingGraphicsModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n snapshot = _load_snapshot(context)\n cover_source = Path(context.data[\"approved_cover_photo_path\"])\n cover_photo = next((photo for photo in snapshot.photos if photo.path == cover_source), None)\n if cover_photo is None:\n raise ValueError(\"Approved cover photo is not part of the listing snapshot\")\n fact_parts = []\n if snapshot.beds is not None:\n fact_parts.append(f\"{snapshot.beds:g} bed\")\n if snapshot.baths is not None:\n fact_parts.append(f\"{snapshot.baths:g} bath\")\n if snapshot.square_feet is not None:\n fact_parts.append(f\"{snapshot.square_feet:,} sq ft\")\n locality = \", \".join(part for part in (snapshot.city, snapshot.state) if part)\n title = snapshot.address or snapshot.display_location or \"Featured property\"\n subtitle_parts = ([] if title == locality else ([locality] if locality else [])) + fact_parts\n subtitle = \" · \".join(subtitle_parts)\n price = f\"${snapshot.price:,}\" if snapshot.price is not None else \"\"\n cover_path = create_listing_cover(\n cover_source,\n context.workspace / \"cover.jpg\",\n title=title,\n subtitle=subtitle,\n price=price,\n focal_point=cover_photo.focal_point,\n )\n\n outro = dict(context.data.get(\"approved_outro\") or {})\n outro_path = create_contact_outro(\n context.workspace / \"outro.png\",\n agent_name=str(outro.get(\"agent_name\") or \"\"),\n cta=str(outro.get(\"cta\") or \"Schedule a private tour\"),\n instagram_handle=str(outro.get(\"instagram_handle\") or \"\"),\n phone=str(outro.get(\"phone\") or \"\"),\n email=str(outro.get(\"email\") or \"\"),\n website=str(outro.get(\"website\") or \"\"),\n )\n return {\"cover_image_path\": str(cover_path), \"outro_image_path\": str(outro_path)}\n\n\nclass ListingPhotoReelRenderModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n _load_snapshot(context) # Re-verifies approved media hashes immediately before render.\n narration_duration = float(\n context.data.get(\"narration_duration_seconds\")\n or context.data.get(\"target_duration_seconds\")\n or 30\n )\n outro_duration = float(params.get(\"outro_duration_seconds\", 4.5))\n target_duration = float(context.data.get(\"target_duration_seconds\") or 30)\n total_duration = min(\n 45.0,\n max(20.0, target_duration, narration_duration + outro_duration),\n )\n output_path = context.workspace / \"final_video.mp4\"\n command = build_photo_reel_command(\n photo_paths=context.data.get(\"approved_photo_paths\") or [],\n narration_audio=Path(context.data[\"narration_path\"]),\n outro_image=Path(context.data[\"outro_image_path\"]),\n caption_overlays=context.data.get(\"caption_overlays\") or [],\n output_video=output_path,\n total_duration_seconds=total_duration,\n outro_duration_seconds=outro_duration,\n width=int(params.get(\"width\", 1080)),\n height=int(params.get(\"height\", 1920)),\n fps=int(params.get(\"fps\", 30)),\n )\n command_path = context.workspace / \"render_command.txt\"\n command_path.write_text(\" \".join(command), encoding=\"utf-8\")\n result = {\n \"output_video\": str(output_path),\n \"render_command\": command,\n \"render_command_path\": str(command_path),\n \"render_executed\": False,\n \"output_duration_seconds\": total_duration,\n }\n if bool(context.data.get(\"execute_render\", False)):\n run_photo_reel(command)\n probe = probe_media(output_path)\n result.update(\n {\n \"render_executed\": True,\n \"rendered_duration_seconds\": probe.duration_seconds,\n \"rendered_width\": probe.width,\n \"rendered_height\": probe.height,\n \"rendered_frame_rate\": probe.frame_rate,\n \"rendered_video_codec\": probe.video_codec,\n \"rendered_audio_codec\": probe.audio_codec,\n }\n )\n return result\n\n\ndef _load_snapshot(context: WorkflowContext):\n raw = json.loads(Path(context.data[\"listing_snapshot_path\"]).read_text(encoding=\"utf-8\"))\n return listing_snapshot_from_dict(raw, media_root=context.data[\"listing_media_root\"], verify_media=True)\n===\nfrom __future__ import annotations\n\nimport json\nimport re\nimport shutil\nimport subprocess\nfrom collections import defaultdict\nfrom pathlib import Path\nfrom typing import Any\n\nfrom core.media.caption_image import create_caption_image\nfrom core.media.coqui_tts import coqui_is_available, create_coqui_audio\nfrom core.media.ffmpeg_utils import (\n build_render_command,\n build_timed_audio_command,\n create_silent_audio,\n create_thumbnail,\n probe_media,\n probe_peak_volume_db,\n run_render_command,\n)\nfrom core.media.local_tts import LocalTtsError, create_say_audio, say_is_available\nfrom core.publishing.instagram import build_caption, build_metadata\nfrom core.workflows.runner import WorkflowContext\n\n_VIDEO_EXTENSIONS = {\".mov\", \".mp4\", \".mpeg\", \".mpg\", \".avi\", \".mkv\", \".webm\"}\n\n\nclass LocalTranscriptionModule:\n def __init__(self, transcription_client: Any = None) -> None:\n self._client = transcription_client\n\n def run(self, context: WorkflowContext, params: dict) -> dict:\n input_path = context.data[\"input_path\"]\n\n client = self._client or context.data.get(\"transcription_client\")\n if client is not None:\n audio_path = _audio_path_for_transcription(input_path, context.workspace)\n if hasattr(client, \"transcribe_with_segments\"):\n text, segments = client.transcribe_with_segments(audio_path)\n valid_segments = [s for s in segments if s[\"end\"] > s[\"start\"]]\n return {\"transcript\": text, \"transcript_segments\": valid_segments}\n return {\"transcript\": client.transcribe(audio_path)}\n\n # Offline/demo fallback — explicit placeholder so it's obvious in logs\n transcript = context.data.get(\n \"transcript\",\n f\"[DEMO PLACEHOLDER — no transcription provider configured for {Path(input_path).name}]\",\n )\n return {\"transcript\": transcript}\n\n\nclass LocalScriptModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n transcript = context.data.get(\"transcript\", \"\")\n listing_context = context.data.get(\"listing_description\") or context.data.get(\"listing_context\") or \"\"\n target_duration = context.data.get(\"target_duration_seconds\") or params.get(\"target_duration_seconds\", 60)\n script = _clean_transcript_for_narration(transcript)\n if listing_context:\n script = f\"{script}\\n\\nOperator context to consider during review: {listing_context}\".strip()\n return {\"generated_script\": script, \"target_duration_seconds\": target_duration}\n\n\nclass LocalVoiceModule:\n def __init__(self, tts_client: Any = None) -> None:\n self._tts_client = tts_client\n\n def run(self, context: WorkflowContext, params: dict) -> dict:\n script = context.data.get(\"approved_narration\") or context.data.get(\"approved_script\", \"\")\n transcript_segments = context.data.get(\"transcript_segments\")\n\n narration_text_path = context.workspace / \"narration.txt\"\n narration_text_path.write_text(script, encoding=\"utf-8\")\n\n # Total duration: prefer input video duration so timed TTS fills the full video.\n target_duration = float(\n context.data.get(\"input_duration_seconds\")\n or context.data.get(\"target_duration_seconds\")\n or (transcript_segments[-1][\"end\"] + 2.0 if transcript_segments else None)\n or _estimate_narration_duration_seconds(script)","is_error":false}]},"uuid":"0528a4a7-f31b-494e-9738-50c5f7fc2ca2","timestamp":"2026-07-08T15:53:32.375Z","toolUseResult":{"stdout":"from __future__ import annotations\n\nimport json\nfrom pathlib import Path\n\nfrom core.listings.manifest import listing_snapshot_from_dict, load_listing_source, source_policy_for\nfrom core.listings.models import AgentProfile\nfrom core.listings.review import build_review_bundle, parse_approved_review, snapshot_digest\nfrom core.media.ffmpeg_utils import probe_media\nfrom core.media.listing_graphics import create_contact_outro, create_listing_cover\nfrom core.media.photo_reel import build_photo_reel_command, run_photo_reel\nfrom core.workflows.runner import WorkflowContext\n\n\nclass ListingIntakeModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n listing_url = str(context.data.get(\"listing_url\") or \"\")\n manifest_path = context.data.get(\"listing_manifest_path\")\n media_root = str(context.data.get(\"listing_media_root\") or Path(str(manifest_path)).parent)\n snapshot = load_listing_source(\n listing_url,\n manifest_path=manifest_path,\n media_root=media_root,\n )\n snapshot_path = context.workspace / \"listing_snapshot.json\"\n snapshot_path.write_text(json.dumps(snapshot.to_dict(), indent=2), encoding=\"utf-8\")\n return {\n \"listing_snapshot_path\": str(snapshot_path),\n \"listing_snapshot_sha256\": snapshot_digest(snapshot),\n \"listing_media_root\": media_root,\n \"listing_source_policy\": source_policy_for(listing_url).value,\n }\n\n\nclass ListingReviewDraftModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n snapshot = _load_snapshot(context)\n agent = AgentProfile.from_mapping(\n {\n \"name\": context.data.get(\"agent_name\"),\n \"instagram_handle\": context.data.get(\"agent_instagram_handle\"),\n \"phone\": context.data.get(\"agent_phone\"),\n \"email\": context.data.get(\"agent_email\"),\n \"website\": context.data.get(\"agent_website\"),\n \"voice_owner\": context.data.get(\"voice_owner\"),\n }\n )\n bundle = build_review_bundle(\n snapshot,\n agent,\n target_duration_seconds=float(\n context.data.get(\"target_duration_seconds\")\n or params.get(\"target_duration_seconds\", 30)\n ),\n )\n draft = json.dumps(bundle, indent=2)\n draft_path = context.workspace / \"listing_review_draft.json\"\n draft_path.write_text(draft, encoding=\"utf-8\")\n return {\n \"generated_script\": draft,\n \"listing_review_draft_path\": str(draft_path),\n }\n\n\nclass ListingReviewApprovalModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n snapshot = _load_snapshot(context)\n approved = parse_approved_review(\n str(context.data.get(\"approved_script\") or \"\"),\n snapshot,\n media_root=context.data[\"listing_media_root\"],\n )\n approved_path = context.workspace / \"approved_listing_reel.normalized.json\"\n approved_payload = {\n \"narration\": approved.narration,\n \"instagram_caption\": approved.instagram_caption,\n \"photo_order\": [photo.relative_path for photo in approved.photos],\n \"cover_photo_path\": approved.cover_photo.relative_path,\n \"outro\": approved.outro,\n \"target_duration_seconds\": approved.target_duration_seconds,\n }\n approved_path.write_text(json.dumps(approved_payload, indent=2), encoding=\"utf-8\")\n return {\n \"approved_narration\": approved.narration,\n \"approved_caption\": approved.instagram_caption,\n \"approved_photo_paths\": [str(photo.path) for photo in approved.photos],\n \"approved_cover_photo_path\": str(approved.cover_photo.path),\n \"approved_outro\": approved.outro,\n \"target_duration_seconds\": approved.target_duration_seconds,\n \"approved_listing_reel_path\": str(approved_path),\n }\n\n\nclass ListingGraphicsModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n snapshot = _load_snapshot(context)\n cover_source = Path(context.data[\"approved_cover_photo_path\"])\n cover_photo = next((photo for photo in snapshot.photos if photo.path == cover_source), None)\n if cover_photo is None:\n raise ValueError(\"Approved cover photo is not part of the listing snapshot\")\n fact_parts = []\n if snapshot.beds is not None:\n fact_parts.append(f\"{snapshot.beds:g} bed\")\n if snapshot.baths is not None:\n fact_parts.append(f\"{snapshot.baths:g} bath\")\n if snapshot.square_feet is not None:\n fact_parts.append(f\"{snapshot.square_feet:,} sq ft\")\n locality = \", \".join(part for part in (snapshot.city, snapshot.state) if part)\n title = snapshot.address or snapshot.display_location or \"Featured property\"\n subtitle_parts = ([] if title == locality else ([locality] if locality else [])) + fact_parts\n subtitle = \" · \".join(subtitle_parts)\n price = f\"${snapshot.price:,}\" if snapshot.price is not None else \"\"\n cover_path = create_listing_cover(\n cover_source,\n context.workspace / \"cover.jpg\",\n title=title,\n subtitle=subtitle,\n price=price,\n focal_point=cover_photo.focal_point,\n )\n\n outro = dict(context.data.get(\"approved_outro\") or {})\n outro_path = create_contact_outro(\n context.workspace / \"outro.png\",\n agent_name=str(outro.get(\"agent_name\") or \"\"),\n cta=str(outro.get(\"cta\") or \"Schedule a private tour\"),\n instagram_handle=str(outro.get(\"instagram_handle\") or \"\"),\n phone=str(outro.get(\"phone\") or \"\"),\n email=str(outro.get(\"email\") or \"\"),\n website=str(outro.get(\"website\") or \"\"),\n )\n return {\"cover_image_path\": str(cover_path), \"outro_image_path\": str(outro_path)}\n\n\nclass ListingPhotoReelRenderModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n _load_snapshot(context) # Re-verifies approved media hashes immediately before render.\n narration_duration = float(\n context.data.get(\"narration_duration_seconds\")\n or context.data.get(\"target_duration_seconds\")\n or 30\n )\n outro_duration = float(params.get(\"outro_duration_seconds\", 4.5))\n target_duration = float(context.data.get(\"target_duration_seconds\") or 30)\n total_duration = min(\n 45.0,\n max(20.0, target_duration, narration_duration + outro_duration),\n )\n output_path = context.workspace / \"final_video.mp4\"\n command = build_photo_reel_command(\n photo_paths=context.data.get(\"approved_photo_paths\") or [],\n narration_audio=Path(context.data[\"narration_path\"]),\n outro_image=Path(context.data[\"outro_image_path\"]),\n caption_overlays=context.data.get(\"caption_overlays\") or [],\n output_video=output_path,\n total_duration_seconds=total_duration,\n outro_duration_seconds=outro_duration,\n width=int(params.get(\"width\", 1080)),\n height=int(params.get(\"height\", 1920)),\n fps=int(params.get(\"fps\", 30)),\n )\n command_path = context.workspace / \"render_command.txt\"\n command_path.write_text(\" \".join(command), encoding=\"utf-8\")\n result = {\n \"output_video\": str(output_path),\n \"render_command\": command,\n \"render_command_path\": str(command_path),\n \"render_executed\": False,\n \"output_duration_seconds\": total_duration,\n }\n if bool(context.data.get(\"execute_render\", False)):\n run_photo_reel(command)\n probe = probe_media(output_path)\n result.update(\n {\n \"render_executed\": True,\n \"rendered_duration_seconds\": probe.duration_seconds,\n \"rendered_width\": probe.width,\n \"rendered_height\": probe.height,\n \"rendered_frame_rate\": probe.frame_rate,\n \"rendered_video_codec\": probe.video_codec,\n \"rendered_audio_codec\": probe.audio_codec,\n }\n )\n return result\n\n\ndef _load_snapshot(context: WorkflowContext):\n raw = json.loads(Path(context.data[\"listing_snapshot_path\"]).read_text(encoding=\"utf-8\"))\n return listing_snapshot_from_dict(raw, media_root=context.data[\"listing_media_root\"], verify_media=True)\n===\nfrom __future__ import annotations\n\nimport json\nimport re\nimport shutil\nimport subprocess\nfrom collections import defaultdict\nfrom pathlib import Path\nfrom typing import Any\n\nfrom core.media.caption_image import create_caption_image\nfrom core.media.coqui_tts import coqui_is_available, create_coqui_audio\nfrom core.media.ffmpeg_utils import (\n build_render_command,\n build_timed_audio_command,\n create_silent_audio,\n create_thumbnail,\n probe_media,\n probe_peak_volume_db,\n run_render_command,\n)\nfrom core.media.local_tts import LocalTtsError, create_say_audio, say_is_available\nfrom core.publishing.instagram import build_caption, build_metadata\nfrom core.workflows.runner import WorkflowContext\n\n_VIDEO_EXTENSIONS = {\".mov\", \".mp4\", \".mpeg\", \".mpg\", \".avi\", \".mkv\", \".webm\"}\n\n\nclass LocalTranscriptionModule:\n def __init__(self, transcription_client: Any = None) -> None:\n self._client = transcription_client\n\n def run(self, context: WorkflowContext, params: dict) -> dict:\n input_path = context.data[\"input_path\"]\n\n client = self._client or context.data.get(\"transcription_client\")\n if client is not None:\n audio_path = _audio_path_for_transcription(input_path, context.workspace)\n if hasattr(client, \"transcribe_with_segments\"):\n text, segments = client.transcribe_with_segments(audio_path)\n valid_segments = [s for s in segments if s[\"end\"] > s[\"start\"]]\n return {\"transcript\": text, \"transcript_segments\": valid_segments}\n return {\"transcript\": client.transcribe(audio_path)}\n\n # Offline/demo fallback — explicit placeholder so it's obvious in logs\n transcript = context.data.get(\n \"transcript\",\n f\"[DEMO PLACEHOLDER — no transcription provider configured for {Path(input_path).name}]\",\n )\n return {\"transcript\": transcript}\n\n\nclass LocalScriptModule:\n def run(self, context: WorkflowContext, params: dict) -> dict:\n transcript = context.data.get(\"transcript\", \"\")\n listing_context = context.data.get(\"listing_description\") or context.data.get(\"listing_context\") or \"\"\n target_duration = context.data.get(\"target_duration_seconds\") or params.get(\"target_duration_seconds\", 60)\n script = _clean_transcript_for_narration(transcript)\n if listing_context:\n script = f\"{script}\\n\\nOperator context to consider during review: {listing_context}\".strip()\n return {\"generated_script\": script, \"target_duration_seconds\": target_duration}\n\n\nclass LocalVoiceModule:\n def __init__(self, tts_client: Any = None) -> None:\n self._tts_client = tts_client\n\n def run(self, context: WorkflowContext, params: dict) -> dict:\n script = context.data.get(\"approved_narration\") or context.data.get(\"approved_script\", \"\")\n transcript_segments = context.data.get(\"transcript_segments\")\n\n narration_text_path = context.workspace / \"narration.txt\"\n narration_text_path.write_text(script, encoding=\"utf-8\")\n\n # Total duration: prefer input video duration so timed TTS fills the full video.\n target_duration = float(\n context.data.get(\"input_duration_seconds\")\n or context.data.get(\"target_duration_seconds\")\n or (transcript_segments[-1][\"end\"] + 2.0 if transcript_segments else None)\n or _estimate_narration_duration_seconds(script)","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"f5c61dfe-5251-41eb-92e8-dff5aa285354","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"0528a4a7-f31b-494e-9738-50c5f7fc2ca2","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcprojqLURr5TM8GBa27L","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01Un2TmdQ1gJ7ZSU9k2go24e","name":"Bash","input":{"command":"ls /workspace/extra/projects/stagehand/input/ && echo \"===\" && ls /workspace/extra/projects/stagehand/workflows/ 2>/dev/null && echo \"===\" && cat /workspace/extra/projects/stagehand/workflows/listing_reel/config.yaml 2>/dev/null"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":3,"cache_creation_input_tokens":8165,"cache_read_input_tokens":62657,"output_tokens":1092,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":8165,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":3,"output_tokens":1092,"cache_read_input_tokens":62657,"cache_creation_input_tokens":8165,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":8165},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcprofmmFMAUPLyNCwAhg","type":"assistant","uuid":"d0838520-8f69-40f0-af0f-d39bb48ab19b","timestamp":"2026-07-08T15:53:32.583Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"d0838520-8f69-40f0-af0f-d39bb48ab19b","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Un2TmdQ1gJ7ZSU9k2go24e","type":"tool_result","content":"IMG_2157.MOV\nvoice_samples\n===\nlisting_reel\npublish_instagram\nvideo_narration\n===\n{\n \"name\": \"listing_reel\",\n \"description\": \"Authorized listing photos to an approved narrated Instagram reel package\",\n \"steps\": [\n {\"id\": \"intake\", \"module\": \"listing_intake\", \"params\": {}},\n {\n \"id\": \"draft_review\",\n \"module\": \"listing_review_draft\",\n \"params\": {\"target_duration_seconds\": 30}\n },\n {\n \"id\": \"approve_listing_reel\",\n \"module\": \"approval_gate\",\n \"params\": {\"required\": true, \"approval_artifact\": \"approved_listing_reel.json\"}\n },\n {\"id\": \"validate_approval\", \"module\": \"listing_review_approval\", \"params\": {}},\n {\n \"id\": \"synthesize_voice\",\n \"module\": \"voice_synthesis\",\n \"params\": {\"reserved_outro_seconds\": 4.5}\n },\n {\"id\": \"build_captions\", \"module\": \"captions\", \"params\": {\"style\": \"modern_bold\"}},\n {\"id\": \"build_graphics\", \"module\": \"listing_graphics\", \"params\": {}},\n {\n \"id\": \"render_reel\",\n \"module\": \"listing_photo_reel\",\n \"params\": {\"width\": 1080, \"height\": 1920, \"fps\": 30, \"outro_duration_seconds\": 4.5}\n },\n {\"id\": \"package_instagram\", \"module\": \"instagram_package\", \"params\": {\"aspect_ratio\": \"9:16\"}}\n ]\n}","is_error":false}]},"uuid":"16df6ae0-6d1b-44fb-9804-f29d265d503e","timestamp":"2026-07-08T15:53:32.624Z","toolUseResult":{"stdout":"IMG_2157.MOV\nvoice_samples\n===\nlisting_reel\npublish_instagram\nvideo_narration\n===\n{\n \"name\": \"listing_reel\",\n \"description\": \"Authorized listing photos to an approved narrated Instagram reel package\",\n \"steps\": [\n {\"id\": \"intake\", \"module\": \"listing_intake\", \"params\": {}},\n {\n \"id\": \"draft_review\",\n \"module\": \"listing_review_draft\",\n \"params\": {\"target_duration_seconds\": 30}\n },\n {\n \"id\": \"approve_listing_reel\",\n \"module\": \"approval_gate\",\n \"params\": {\"required\": true, \"approval_artifact\": \"approved_listing_reel.json\"}\n },\n {\"id\": \"validate_approval\", \"module\": \"listing_review_approval\", \"params\": {}},\n {\n \"id\": \"synthesize_voice\",\n \"module\": \"voice_synthesis\",\n \"params\": {\"reserved_outro_seconds\": 4.5}\n },\n {\"id\": \"build_captions\", \"module\": \"captions\", \"params\": {\"style\": \"modern_bold\"}},\n {\"id\": \"build_graphics\", \"module\": \"listing_graphics\", \"params\": {}},\n {\n \"id\": \"render_reel\",\n \"module\": \"listing_photo_reel\",\n \"params\": {\"width\": 1080, \"height\": 1920, \"fps\": 30, \"outro_duration_seconds\": 4.5}\n },\n {\"id\": \"package_instagram\", \"module\": \"instagram_package\", \"params\": {\"aspect_ratio\": \"9:16\"}}\n ]\n}","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"d0838520-8f69-40f0-af0f-d39bb48ab19b","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"type":"last-prompt","leafUuid":"16df6ae0-6d1b-44fb-9804-f29d265d503e","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}
{"type":"ai-title","aiTitle":"Review competitive analysis documentation","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}
{"parentUuid":"16df6ae0-6d1b-44fb-9804-f29d265d503e","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcprqjJPvs3jrX2bomLsL","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Now I have a complete picture of the codebase. Let me plan the template implementation:\n\n**Current flow:**\n1. `ListingGraphicsModule` calls `create_contact_outro()` (fixed dark blue/gold color scheme)\n2. `ListingPhotoReelRenderModule` calls `build_photo_reel_command()` (fixed zoom_increment=0.06, fade transition, bottom captions at H-h-160)\n3. Both are configured via `params` in the workflow config, but the visual template params aren't currently passable\n\n**What I need to add for 3 templates:**\n\nFor `photo_reel.py`:\nI'll add template support with configurable transition types, zoom styles, and caption positioning. Template 1 \"Essential\" uses subtle zoom (0.04) with fade transitions and bottom captions, Template 2 \"Feature Spotlight\" goes bolder with faster zoom (0.08) and slide-left transitions with centered captions for a more dynamic feel, and Template 3 \"Branded\" keeps it slow and elegant with minimal zoom (0.03) and extended outro timing for a premium presentation.\n\nFor `listing_graphics.py`:\n- Add theme color schemes to the contact outro function, with Template 1 using the current dark blue palette, Template 2 switching to high-contrast deep charcoal and bright white, and Template 3 adopting warm rich tones like deep brown and dark gold.\n\nThen I need to thread the template parameter through the config and both modules, creating workflow configs that can specify which template to use.\n\nFor the demo itself, I'll need to download photos for all three listings and create their manifests, but there's an approval gate in the workflow that I need to handle. Instead of going through the interactive approval process, I can pre-create the approved bundles programmatically. The workflow supports a `--tts-provider` option where I can specify XTTS-v2 for local generation, so I'll set that up and bypass the approval gate for the demo. I should simplify the approach: build template support into the renderer, download the photos, create the manifests, and write a demo script that handles the full workflow automatically including the approval step. Let me check what local TTS options are available, particularly the coqui/XTTS-v2 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ShWEsfJA7Ims1CwxXfJyOH3XdIj0RWGvvvFn1ZmznMejP1NpTGmDwa19bQfU4NYxwsadS7OdEAOTWK7qgaZ9CGCmnAR3UyogyDRmIvedYkW8AK2yVtfspbjR1Ye2l9HGTMTGwq7u/qi8P0QJgwzwkY5TI7M8riluCm8r5yDYfva0YSHXtXxgB"}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4862,"cache_read_input_tokens":70822,"output_tokens":1257,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":4862,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":1257,"cache_read_input_tokens":70822,"cache_creation_input_tokens":4862,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":4862},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcprqhqqRNw8BakF7YGQu","type":"assistant","uuid":"3e33bde2-7635-45b1-ab9a-cf49a7b1fda8","timestamp":"2026-07-08T15:53:57.895Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"3e33bde2-7635-45b1-ab9a-cf49a7b1fda8","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcprqjJPvs3jrX2bomLsL","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01AXWEc6UmRfkaiBy9G8hiVh","name":"Bash","input":{"command":"grep -n \"coqui\\|xtts\\|tts.provider\\|tts_provider\" /workspace/extra/projects/stagehand/cli/main.py | head -30 && echo \"===\" && grep -n \"def.*coqui\\|CoquiTts\\|coqui\" /workspace/extra/projects/stagehand/core/media/coqui_tts.py | head -20"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4862,"cache_read_input_tokens":70822,"output_tokens":1257,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":4862,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":1257,"cache_read_input_tokens":70822,"cache_creation_input_tokens":4862,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":4862},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcprqhqqRNw8BakF7YGQu","type":"assistant","uuid":"01a5e8ec-dec9-4e00-8ea4-b4ac63be7682","timestamp":"2026-07-08T15:53:57.915Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"01a5e8ec-dec9-4e00-8ea4-b4ac63be7682","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AXWEc6UmRfkaiBy9G8hiVh","type":"tool_result","content":"29: run_parser.add_argument(\"--tts-provider\", choices=[\"say\", \"coqui\", \"elevenlabs\", \"silent\"], default=\"say\")\n91: \"--tts-provider\",\n92: choices=[\"elevenlabs\", \"say\", \"coqui\", \"silent\"],\n144: \"local_tts_provider\": args.tts_provider,\n147: \"coqui_tts_platform\": settings.coqui_tts_platform,\n148: \"coqui_tts_image\": settings.coqui_tts_image,\n149: \"coqui_tts_model\": settings.coqui_tts_model,\n164: provider = args.tts_provider\n190: \"local_tts_provider\": provider,\n196: \"coqui_tts_platform\": settings.coqui_tts_platform,\n197: \"coqui_tts_image\": settings.coqui_tts_image,\n198: \"coqui_tts_model\": settings.coqui_tts_model,\n222: provider = getattr(args, \"tts_provider\", None) or job_input.get(\"local_tts_provider\")\n227: raise SystemExit(\"--tts-provider elevenlabs requires --voice-id or DEFAULT_VOICE_ID in .env\")\n229: raise SystemExit(\"--tts-provider elevenlabs requires ELEVENLABS_API_KEY in .env\")\n===\n9:class CoquiTtsError(RuntimeError):\n13:def coqui_is_available() -> bool:\n17:def build_coqui_command(\n22: image: str = \"ghcr.io/coqui-ai/tts-cpu\",\n75:def create_coqui_audio(\n79: image: str = \"ghcr.io/coqui-ai/tts-cpu\",\n86: command = build_coqui_command(\n97: raise CoquiTtsError((exc.stderr or exc.stdout or \"Coqui TTS synthesis failed\").strip()) from exc","is_error":false}]},"uuid":"f1ff6680-fe59-48c0-800d-3964dec48cc2","timestamp":"2026-07-08T15:53:57.929Z","toolUseResult":{"stdout":"29: run_parser.add_argument(\"--tts-provider\", choices=[\"say\", \"coqui\", \"elevenlabs\", \"silent\"], default=\"say\")\n91: \"--tts-provider\",\n92: choices=[\"elevenlabs\", \"say\", \"coqui\", \"silent\"],\n144: \"local_tts_provider\": args.tts_provider,\n147: \"coqui_tts_platform\": settings.coqui_tts_platform,\n148: \"coqui_tts_image\": settings.coqui_tts_image,\n149: \"coqui_tts_model\": settings.coqui_tts_model,\n164: provider = args.tts_provider\n190: \"local_tts_provider\": provider,\n196: \"coqui_tts_platform\": settings.coqui_tts_platform,\n197: \"coqui_tts_image\": settings.coqui_tts_image,\n198: \"coqui_tts_model\": settings.coqui_tts_model,\n222: provider = getattr(args, \"tts_provider\", None) or job_input.get(\"local_tts_provider\")\n227: raise SystemExit(\"--tts-provider elevenlabs requires --voice-id or DEFAULT_VOICE_ID in .env\")\n229: raise SystemExit(\"--tts-provider elevenlabs requires ELEVENLABS_API_KEY in .env\")\n===\n9:class CoquiTtsError(RuntimeError):\n13:def coqui_is_available() -> bool:\n17:def build_coqui_command(\n22: image: str = \"ghcr.io/coqui-ai/tts-cpu\",\n75:def create_coqui_audio(\n79: image: str = \"ghcr.io/coqui-ai/tts-cpu\",\n86: command = build_coqui_command(\n97: raise CoquiTtsError((exc.stderr or exc.stdout or \"Coqui TTS synthesis failed\").strip()) from exc","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"01a5e8ec-dec9-4e00-8ea4-b4ac63be7682","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"f1ff6680-fe59-48c0-800d-3964dec48cc2","isSidechain":false,"message":{"model":"claude-sonnet-4-6","id":"msg_011CcprqjJPvs3jrX2bomLsL","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01JBiJ3LY9cBHZpckCtqMpWK","name":"Bash","input":{"command":"grep -n \"tts.provider\\|tts_provider\\|listing.reel\\|listing_reel\" /workspace/extra/projects/stagehand/cli/main.py | head -40"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":4862,"cache_read_input_tokens":70822,"output_tokens":1257,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":4862,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[{"input_tokens":1,"output_tokens":1257,"cache_read_input_tokens":70822,"cache_creation_input_tokens":4862,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":4862},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011CcprqhqqRNw8BakF7YGQu","type":"assistant","uuid":"3b7fc6c7-88de-4967-92fe-f80242b77c3d","timestamp":"2026-07-08T15:53:58.084Z","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"3b7fc6c7-88de-4967-92fe-f80242b77c3d","isSidechain":false,"promptId":"e581e1e5-3c4a-4c5f-b425-48b550189592","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01JBiJ3LY9cBHZpckCtqMpWK","type":"tool_result","content":"29: run_parser.add_argument(\"--tts-provider\", choices=[\"say\", \"coqui\", \"elevenlabs\", \"silent\"], default=\"say\")\n76: \"listing-reel\",\n91: \"--tts-provider\",\n117: elif args.command == \"listing-reel\":\n118: workflow_name = \"listing_reel\"\n144: \"local_tts_provider\": args.tts_provider,\n163: elif args.command == \"listing-reel\":\n164: provider = args.tts_provider\n172: raise SystemExit(\"listing-reel requires --agent-name or AGENT_NAME in .env\")\n174: raise SystemExit(\"listing-reel requires at least one public contact field\")\n190: \"local_tts_provider\": provider,\n222: provider = getattr(args, \"tts_provider\", None) or job_input.get(\"local_tts_provider\")\n227: raise SystemExit(\"--tts-provider elevenlabs requires --voice-id or DEFAULT_VOICE_ID in .env\")\n229: raise SystemExit(\"--tts-provider elevenlabs requires ELEVENLABS_API_KEY in .env\")","is_error":false}]},"uuid":"1d04d3cd-f626-49a8-854e-57c683315033","timestamp":"2026-07-08T15:53:58.102Z","toolUseResult":{"stdout":"29: run_parser.add_argument(\"--tts-provider\", choices=[\"say\", \"coqui\", \"elevenlabs\", \"silent\"], default=\"say\")\n76: \"listing-reel\",\n91: \"--tts-provider\",\n117: elif args.command == \"listing-reel\":\n118: workflow_name = \"listing_reel\"\n144: \"local_tts_provider\": args.tts_provider,\n163: elif args.command == \"listing-reel\":\n164: provider = args.tts_provider\n172: raise SystemExit(\"listing-reel requires --agent-name or AGENT_NAME in .env\")\n174: raise SystemExit(\"listing-reel requires at least one public contact field\")\n190: \"local_tts_provider\": provider,\n222: provider = getattr(args, \"tts_provider\", None) or job_input.get(\"local_tts_provider\")\n227: raise SystemExit(\"--tts-provider elevenlabs requires --voice-id or DEFAULT_VOICE_ID in .env\")\n229: raise SystemExit(\"--tts-provider elevenlabs requires ELEVENLABS_API_KEY in .env\")","stderr":"","interrupted":false,"isImage":false,"noOutputExpected":false},"sourceToolAssistantUUID":"3b7fc6c7-88de-4967-92fe-f80242b77c3d","userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"parentUuid":"1d04d3cd-f626-49a8-854e-57c683315033","isSidechain":false,"type":"assistant","uuid":"02058030-6a8a-4661-aecb-a9e8d961f509","timestamp":"2026-07-08T15:53:58.472Z","message":{"id":"9f8d2821-2161-4faf-8dd6-ab0d91501b1a","container":null,"model":"","role":"assistant","stop_reason":"stop_sequence","stop_sequence":"","type":"message","usage":{"input_tokens":0,"output_tokens":0,"cache_creation_input_tokens":0,"cache_read_input_tokens":0,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":null,"cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":0},"inference_geo":null,"iterations":null,"speed":null},"content":[{"type":"text","text":"You're out of extra usage · resets 1:30pm (America/Chicago)"}],"context_management":null},"error":"rate_limit","isApiErrorMessage":true,"apiErrorStatus":429,"userType":"external","entrypoint":"sdk-ts","cwd":"/workspace/agent","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5","version":"2.1.128","gitBranch":"HEAD"}
{"type":"last-prompt","leafUuid":"02058030-6a8a-4661-aecb-a9e8d961f509","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}
{"type":"ai-title","aiTitle":"Review competitive analysis documentation","sessionId":"13091a77-b26e-4df1-8d3a-a8583fd156c5"}