The file /workspace/extra/second-brain/portfolio/BOARD.md has been updated successfully. (file state is current in your context — no need to Read it back)

# Portfolio Board

One row per active project. Cards with full detail live in `projects/`.
Operating model + decisions: [PLAN.md](PLAN.md).
Stages: `research → discovery → spec → build → test → feedback → maintain`.
Guard: `review-required` (James approves merges) or `autonomous-ok` (agents proceed, report after).

**Seeded 2026-07-06 from git activity — stages and next actions are drafts until James confirms.**

| Project | Stage | Guard | Next action | Blocked on James | Last activity |
|---|---|---|---|---|---|
| [portfolio-autopilot](projects/portfolio-autopilot.md) | build | autonomous-ok | Monitor headroom log; calibration surfaces reserve suggestions after 5+ snapshots | none | 2026-07-12 |
| [qip-qien](projects/qip-qien.md) | feedback | review-required | SEV-1 fix committed (ee84254); merge sign-off needed | merge approval | 2026-07-19 |
| [congressional-trading](projects/congressional-trading.md) | test | autonomous-ok | Await threshold decision; weekly precision monitor running (Mondays 9am) | threshold decision | 2026-07-19 |
| [FindRefurbishedAppleProduct](projects/FindRefurbishedAppleProduct.md) | discovery | autonomous-ok | Confirm goal — brand new repo | confirm card | 2026-07-06 |
| [TradingBot25](projects/TradingBot25.md) | build | review-required | Confirm goal + current strategy state | confirm card | 2026-06-26 |
| [AgenticLever](projects/AgenticLever.md) | build | autonomous-ok | Confirm goal + next feature direction | confirm goal | 2026-07-20 |
| [pool-monitor](projects/pool-monitor.md) | maintain | autonomous-ok | None — steady state? confirm | confirm card | 2026-06-17 |
| [StageHand](projects/StageHand.md) | discovery | autonomous-ok | Await James answers on 5 toolchain questions; headless-browser gallery capture if Local Recs green-lit | voice, agent, posting, pricing, Local Recs y/n | 2026-07-20 |
| [MentorCore](projects/MentorCore.md) | research | autonomous-ok | Parked — no bandwidth | none | 2026-06-11 |
| [RoadSense](projects/RoadSense.md) | spec | autonomous-ok | Answer 5 launch questions → unblock implementation | auth model, city, GIS license, creator posture, metric | 2026-07-08 |
| [nanoclaw](projects/nanoclaw.md) | build | autonomous-ok | Review push() fix (d4ef752) → deploy to Studio | deploy, metric | 2026-07-20 |
| [projects-monorepo-infra](projects/projects-monorepo-infra.md) | build | review-required | Name the token-spend-avoided metric | metric decision | 2026-07-16 |
| cortex *(no card yet)* | maintain | review-required | Decide: fill Reddit OAuth creds, or drop Reddit ingest (project's own docs call the API "increasingly restrictive") | Reddit creds / keep-or-drop call | 2026-07-12 |
| CodexBar *(no card yet)* | maintain | review-required | Decide upstream-sync strategy (1056 commits behind steipete/CodexBar); scrub steipete paths/bundle-ID from docs | sync strategy | 2026-07-12 |
| CodexBarLocal *(no card yet)* | maintain | review-required | 34 uncommitted changes incl. a stray Xcode scaffold — commit, stash, or discard | commit/stash/discard call | 2026-07-12 |
| CodexBar-ESP32 *(no card yet)* | maintain | autonomous-ok | None right now — mDNS doc gap fixed today; 3 minor observations items open (untested pace-formula dup, lock-ordering) | none | 2026-07-12 |
| localsky_radar *(no card yet)* | build | review-required | `git init` + first commit (2,227 lines, zero version control); rewrite CLAUDE.md (wrongly claims unimplemented) | confirm git-init | 2026-07-12 |

## Decision queue

Questions for James, appended by Nano; answered items move to the card's Notes and are removed here.

- **nanoclaw metric:** Proposed metric = "decisions James answers per week from daily brief" (proxy for brief usefulness). Confirm or rename? (Card currently undefined.)
- **RoadSense launch questions (5):** auth model, generalization city, GIS license, creator posture, 30-day success metric. Sent via Telegram 2026-07-08.
- **congressional-trading dual-poller (2026-07-12):** `com.congresswatch.daily` launchd job confirmed loaded on *both* the Mac Mini and this Studio simultaneously — doubles LLM spend and races notification cooldowns. Project's own `agentic_plan.md` already flags this as unresolved. Which machine is authoritative?
- **qip-ask-qien SEV-1 merge (2026-07-19):** fix committed (ee84254) — admin route guards changed from `requireExpertApiUser` → `requireAdminApiUser` on 4 routes. TypeScript + lint clean. Ready to merge; needs James's sign-off to push.
- **nanoclaw push() fix deploy (2026-07-20):** Fix implemented (d4ef752), 135 tests pass. Awaiting Studio deploy. Design decisions made autonomously: (1) follow-up-turn UX = yes; (2) Claude safety net = yes; (3) tests = yes.

## Recently shipped

- **Portfolio audit** 2026-07-12 — parallel survey across 20 projects; auto-fixed 10 AGENTS.md/CLAUDE.md symmetry gaps, an mDNS doc gap (CodexBar-ESP32), a stale phase claim (MentorCore), a wrong-hostname ntfy-link bug (pool-monitor, verified via 76 passing tests), a test-isolation gap (AgenticLever, verified via 32 passing tests), and this file's own Tailscale hostname drift.
- **nanoclaw** 2026-07-08 — fix(router): mention-sticky Slack session scoping committed

-| [StageHand](projects/StageHand.md) | discovery | autonomous-ok | Await James answers on 5 toolchain questions; headless-browser gallery capture if Local Recs green-lit | voice, agent, posting, pricing, Local Recs y/n | 2026-07-20 |

+| [StageHand](projects/StageHand.md) | discovery | autonomous-ok | Await James answers on 5 toolchain questions; headless-browser gallery capture if Local Recs green-lit | voice, agent, posting, pricing, Local Recs y/n | 2026-07-21 |


Now answering James's agent question:

<message to="telegram-mg-17796">Done — committed (36156c0). `ListingQARetryModule` sits between `video_review` and `build_review_artifacts` in the config. If the first render scores publishable it's a no-op; if it doesn't, it re-runs the ffmpeg command and re-scores, up to 2 times. On exhaustion the job fails with the score and top issues in the error message so you know exactly what broke.

---

On your agent question: StageHand as it exists today is **not an agent** — it's an automated pipeline. The narration critic loop is a loop, and the new retry loop is a loop too, but loops don't make something an agent.

The concrete difference is **who decides what to do next**. In StageHand, *you* decide the steps (they're in the config). The system executes them. An agent is a system that observes state and decides its own next action — the loop is over a perception-action cycle, not a fixed step sequence.

A concrete example you could actually build: imagine the narration fails the critic loop 3 times. An automated pipeline fails the job. An agent would notice *why* it keeps failing — say, the narration keeps mentioning the pool but the photos have no pool — and decide to rewrite the narration brief instead of retrying the same prompt. That "notice why and pick a different action" step is agency. The planning and decision happen at runtime, not at design time.

So what would make StageHand an agent? If instead of running `synthesize_voice → render → qa → retry`, you gave it: "here are the listing photos and the QA rubric — produce a passing reel." Then it would have to figure out the path itself. Every iteration it could observe what failed and choose a different approach: new narration angle, different photo order, different pacing. You'd be giving it a goal and a measure of success, not a map.

That's the progression in Shann's thread: loops (agent finds its own path) → graphs (you draw the map). StageHand is currently a graph. Making it agentic means giving it the goal and letting it design the graph itself.</message>


<context timezone="America/Chicago" />
<task from="telegram-mg-17796" time="Jul 20, 2026, 7:03 PM">Script output:
{
  "burnable_pct": 58.9,
  "tier": "high",
  "implementationModel": "claude-sonnet",
  "eligibleProjects": [
    {
      "project": "StageHand",
      "priority": "P1"
    },
    {
      "project": "nanoclaw",
      "priority": "P1"
    },
    {
      "project": "AgenticLever",
      "priority": "P2"
    },
    {
      "project": "RoadSense",
      "priority": "P2"
    },
    {
      "project": "qip-qien",
      "priority": "P2"
    },
    {
      "project": "congressional-trading",
      "priority": "P3"
    },
    {
      "project": "TradingBot25",
      "priority": "P3"
    }
  ],
  "next_reset_at": "2026-07-25T20:59:59.377Z",
  "providerSnapshot": [
    {
      "name": "Claude",
      "tracked": true,
      "5h_remaining_pct": 100,
      "7d_remaining_pct": 69
    },
    {
      "name": "Codex",
      "tracked": true,
      "5h_remaining_pct": null,
      "7d_remaining_pct": 29
    },
    {
      "name": "Gemini",
      "tracked": false,
      "note": "$20/mo subscription — no CodexBar tracking, manually updated from gemini.google.com/usage"
    },
    {
      "name": "LM Studio",
      "tracked": false,
      "note": "local model server — always-available when running at lm_studio_url"
    }
  ],
  "claude_windows": {
    "5h": {
      "remaining_pct": 100,
      "resets_in_sec": -1
    },
    "7d": {
      "remaining_pct": 69,
      "resets_in_sec": 406798
    }
  }
}

Instructions:
Portfolio Autopilot reset-wake: check quota and run one autopilot cycle. Read /workspace/agent/autopilot-config.json for context. Run node /workspace/agent/autopilot.mjs to see current state, then proceed as the autopilot prompt instructs.</task>

<task from="telegram-mg-17796" time="Jul 21, 2026, 3:30 AM">Script output:
{
  "burnable_pct": 58.9,
  "tier": "high",
  "implementationModel": "claude-sonnet",
  "eligibleProjects": [
    {
      "project": "StageHand",
      "priority": "P1"
    },
    {
      "project": "nanoclaw",
      "priority": "P1"
    },
    {
      "project": "AgenticLever",
      "priority": "P2"
    },
    {
      "project": "RoadSense",
      "priority": "P2"
    },
    {
      "project": "qip-qien",
      "priority": "P2"
    },
    {
      "project": "congressional-trading",
      "priority": "P3"
    },
    {
      "project": "TradingBot25",
      "priority": "P3"
    }
  ],
  "next_reset_at": "2026-07-25T20:59:59.433Z",
  "providerSnapshot": [
    {
      "name": "Claude",
      "tracked": true,
      "5h_remaining_pct": 100,
      "7d_remaining_pct": 69
    },
    {
      "name": "Codex",
      "tracked": true,
      "5h_remaining_pct": null,
      "7d_remaining_pct": 29
    },
    {
      "name": "Gemini",
      "tracked": false,
      "note": "$20/mo subscription — no CodexBar tracking, manually updated from gemini.google.com/usage"
    },
    {
      "name": "LM Studio",
      "tracked": false,
      "note": "local model server — always-available when running at lm_studio_url"
    }
  ],
  "claude_windows": {
    "5h": {
      "remaining_pct": 100,
      "resets_in_sec": -1
    },
    "7d": {
      "remaining_pct": 69,
      "resets_in_sec": 406798
    }
  }
}

Instructions:
Portfolio Autopilot run triggered. Trigger script has confirmed burnable quota and eligible projects exist.

Script `data` contains:
- `burnable_pct`: effective burnable quota (%)
- `tier`: quota tier (minimal/low/medium/high)
- `implementationModel`: model for implementation tasks
- `eligibleProjects`: [{project, priority}] sorted by priority — P1 first
- `next_reset_at`: ISO timestamp when the constraining window resets
- `providerSnapshot`: remaining % for all providers (Claude + Codex) for context
- `claude_windows`: { "5h": { remaining_pct, resets_in_sec }, "7d": { ... } }

## Your job this cycle

1. Read `/workspace/extra/second-brain/portfolio/BOARD.md` and the relevant `projects/*.md` cards for eligible projects.

2. Pick ONE unit of work — the highest-priority eligible project with a clear, actionable `Next action`. Skip anything where `Next action` is "confirm with James" or blocked on external input.

3. Determine task type and proceed accordingly:
   - **Greenfield** (new plan, new feature direction, new project direction): Plan only → auto red-team → send package (plan + critique + numbered open questions) to James via Slack (`slack-infrastructure`). Do NOT start implementation.
   - **Continuation** (`autonomous-ok` guard, clear next action): Implement directly. Report outcome to James after.
   - **review-required** (TradingBot25, qip-qien): Produce change + summary, send to James via Slack (`slack-infrastructure`) for merge approval.

4. Planning always uses Claude Sonnet regardless of `implementationModel`. Implementation uses whatever `implementationModel` says.

5. After completing work:
   - Update the project card's `Next action` and append a dated line to its `Notes`.
   - Update the `Last activity` date in `BOARD.md`.
   - Send James a brief 2–3 line outcome note to `slack-infrastructure`. Use Central Time (America/Chicago) for any timestamps — never UTC.
   - Log the run to `/workspace/agent/autopilot-run-log.jsonl` — one JSON line: `{ timestamp, tier, burnable_pct, project, task_type, model_used, outcome, notes }`.

6. **Schedule the next reset-wake**: After completing work, call `mcp__nanoclaw__schedule_task` with:
   - `processAfter`: the `next_reset_at` value from the trigger data (the exact window reset time)
   - `recurrence`: omit (one-shot)
   - `prompt`: "Portfolio Autopilot reset-wake: check quota and run one autopilot cycle. Read /workspace/agent/autopilot-config.json for context. Run node /workspace/agent/autopilot.mjs to see current state, then proceed as the autopilot prompt instructs."
   - `script`: `node /workspace/agent/autopilot-trigger.mjs 2>/dev/null`
   This ensures the next cycle starts exactly when the window resets, not up to 30 min later.

If no eligible project has a clear actionable next step, log it and send a brief note to `slack-infrastructure`: what's stalled and why. Use Central Time for any times mentioned.

Config at `/workspace/agent/autopilot-config.json` — thresholds and priorities live there.</task>


I have two autopilot tasks coming in simultaneously - one from 7:03 PM and one from 3:30 AM. I need to handle them as a single autopilot cycle (they're likely fired together because of the context compaction). Let me process this as one cycle.

First, write the running lock. Then read the board and project cards to find actionable work.

From what I already know from this session:
- StageHand (P1): All open punch list items blocked - waiting on James's 5 toolchain questions, headless browser needs Local Recs approval, real client data needed, etc.
- nanoclaw (P1): Push fix is merged, just waiting on James to deploy it to Studio and confirm the metrics improve
- AgenticLever (P2): Needs James to confirm the goal and direction for the next feature
- RoadSense (P2): 5 launch questions still pending
- qip-qien (P2): Waiting on SEV-1 merge sign-off
- congressional-trading (P3): Need to make threshold and dual-poller decisions
- TradingBot25 (P3): Needs review

Actually, I realize I just finished the QA retry loop for StageHand that James explicitly asked for, and I also fixed the ECONNRESET issue in AgenticLever earlier. Looking at what's actually blocking progress across all these projects, everything seems to be waiting on James for either deploy confirmation, goal clarification, or sign-offs. Let me check if there's anything I can tackle autonomously without his input.

Congressional-trading is interesting because while it's blocked on the threshold decision, the weekly precision monitor is already running autonomously on Mondays. I should look more carefully at whether there's any actual code work I can do there, and also dig into nanoclaw to see if there's something beyond the push() fix that I could work on. The dual-poller issue on congressional-trading is creating a decision bottleneck — until James clarifies which machine should be authoritative, I should hold off on autonomous code work there. Let me check what nanoclaw might offer instead, since it's been getting recent updates with autopilot tooling and router fixes.

Looking at the nanoclaw timeline, there are multiple fixes already pushed to GitHub but waiting for deployment on the Studio and Mini machines — the push() fix from July 20th, the skip-lock bypass fix, and earlier commits from July 8th. Those are all James actions since I can't SSH into the machines from here to pull and restart the service.

For congressional-trading, the weekly precision monitor is running, but the dual-poller issue has been sitting in the decision queue since July 12th without James's threshold decision. I shouldn't start work on that until he decides which machine to use. Let me check if there are other symmetry gaps in the documentation that have appeared since the auto-fix on July 12th, or if there's anything else I can tackle autonomously.

Looking at the feature/listing-reel-workflow branch, I see recent commits for media hash fixes and QA retry logic. The punch list shows some items blocked on Richard for the ElevenLabs PVC share, but I should check if there's any code cleanup or other autonomous work I can do on this branch while waiting for those dependencies. Looking at the AgenticLever board, it's marked as autonomous-ok and in build stage, but the next action says James needs to confirm the goal. However, the notes already indicate the goal is confirmed—it's a production B2B lead-gen funnel for AI workflow automation targeting local SMBs. Since the site is live and tests pass, there's no clear feature work to do without James explicitly signing off on priorities.

Let me check if congressional-trading or nanoclaw have any autonomous work I could tackle instead. There's a known drift issue in the outcome_tracker that was logged in the last commit, and congressional-trading is marked autonomous-ok despite being P3—maybe there's something actionable there.

I notice two tasks came in during the same period, so I'll treat them as one cycle. First, I'll set up the running lock, then dig into those project cards.


Bash

echo '{"started_at":"2026-07-21T08:30:00Z"}' > /workspace/agent/autopilot-running-lock.json && echo "lock written"

Write autopilot running lock


lock written


Ingest Claude blog post on marketing operations automation


Conversation compacted


This session is being continued from a previous conversation that ran out of context. The summary below covers the earlier portion of the conversation.

Summary:
1. Primary Request and Intent:

Multiple threads in this session:

**A. Wrap-up of prior 6:00 PM autopilot cycle (AgenticLever ECONNRESET fix)**
Complete administrative steps that were pending: schedule reset-wake, clear running lock, send outcome note to slack-infrastructure.

**B. 6:30 PM autopilot cycle (49% burnable, medium tier)**
Process eligible projects and find autonomous work. All blocked → set skip-lock until next 5h window reset (2026-07-21T04:00:00Z).

**C. James's Twitter/X message (3:28 PM)**
James shared https://x.com/shannholmberg/status/2079096565344739643 and asked "how and where we could try this out?" — a tweet explaining loops vs graphs in agentic AI workflows.

**D. James's follow-up questions (9:42 PM, message ID 2970)**
Questions about StageHand's current QA behavior, CLI commands as state machine nodes, Mermaid diagrams vs actual implementation, and the map/territory analogy.

**E. James's implementation request (9:44 PM, message ID 2972)**
"Ok can you implement that outer loop for me please?" — requesting the outer QA→fail→rerender retry loop for StageHand.

**F. James's agent question (9:48 PM, message ID 2974)**
"Would stagehand then be an 'agent'? Would adding the graph make it an agent? If not, what would? I'm still trying to get a concrete example of an agent for me to really grasp the concept intuitively"

**G. 7:03 PM and 3:30 AM autopilot cycles (58.9% burnable, high tier)**
Two tasks arrived together. Running lock written. Cycle mid-execution at time of summary request.

2. Key Technical Concepts:

- **Portfolio Autopilot protocol**: running-lock, skip-lock, reset-wake scheduling, run-log JSONL
- **Skip-lock format**: must include `skip_lock_until` ISO timestamp; trigger script checks `lock.skip_lock_until && new Date(lock.skip_lock_until) > new Date()`
- **Loops vs Graphs in agentic AI**: Loop = agent decides its own path; Graph = you pre-draw the state machine (nodes + routing conditions). A graph is "a map of loops and checkpoints."
- **Map vs Territory**: Mermaid diagram = map describing territory (can drift); declarative config = map IS the territory (changing it changes behavior)
- **StageHand (CreatorFlow)**: Python-based concierge-first real estate reel pipeline; listing reel workflow runs as linear steps through `WorkflowRunner`
- **ListingQARetryModule**: new module implementing outer QA retry loop; sits between `video_review` and `build_review_artifacts`; re-renders + re-scores up to `max_retries` (default 2) times
- **ScoreReport recommendation logic**: `"publishable" if overall >= 85 and not warnings else "revise" if overall >= 65 else "reject"`; warnings = portrait, audio, profile_photo issues; issues = duration out of band
- **Scorecard math**: with 1 photo, duration=20 (at target), portrait, has_audio, has_profile_photo, captions, 60fps, h264/aac → weighted score = 85 exactly → "publishable"
- **WorkflowRunner**: iterates steps, skips `completed_steps`; no built-in retry; resume() re-runs from first incomplete step
- **TDD approach**: Write failing tests first, confirm RED (ImportError), implement, confirm GREEN
- **probe_media mock**: integration test needed `probe_media` patched to return `MediaProbe(duration_seconds=20.0, width=1080, height=1920, has_audio=True, frame_rate=60.0, video_codec="h264", audio_codec="aac")` to produce publishable score
- **pre-existing test failure**: `test_review_server.py` RemoteDisconnected — confirmed pre-existing via `git stash` verification
- **Agent vs automated pipeline**: Agent = system that observes state and decides its own next action at runtime. StageHand is a pipeline (fixed steps in config). Making it agentic = give it goal + rubric, let it design the path.

3. Files and Code Sections:

- **`/workspace/agent/autopilot-running-lock.json`**
  - Written at start of 7:03 PM / 3:30 AM cycle: `{"started_at":"2026-07-21T08:30:00Z"}`
  - Must be cleared at cycle end

- **`/workspace/agent/autopilot-run-log.jsonl`**
  - 6:30 PM all-blocked entry appended: `{"timestamp":"2026-07-21T00:30:00Z","tier":"medium","burnable_pct":49,"project":"none","task_type":"skipped","model_used":"none","outcome":"all_blocked","notes":"All P1/P2 projects blocked: StageHand awaiting 5 toolchain answers, nanoclaw awaiting Studio deploy + metric, AgenticLever awaiting goal confirm, RoadSense awaiting 5 launch questions, qip-qien awaiting merge sign-off. Skip-lock set until 2026-07-21T04:00:00Z (next 5h window reset)."}`

- **`/workspace/agent/autopilot-skip-lock.json`**
  - Set for 6:30 PM cycle: `{"set_at":"2026-07-21T00:30:00Z","reason":"all_blocked","skip_lock_until":"2026-07-21T04:00:00.222Z"}`
  - Note: old skip-lock had wrong format (missing `skip_lock_until`); new one includes it correctly

- **`/workspace/extra/projects/stagehand/core/workflows/listing_reel_modules.py`**
  - Added `ListingQARetryModule` class after `ListingVideoReviewModule`, before `ListingPreRenderScoreModule = ListingScriptReviewModule` aliases:
  ```python
  class ListingQARetryModule:
      """Retries render + QA if the post-render score doesn't clear the publishable bar."""

      def run(self, context: WorkflowContext, params: dict) -> dict:
          post_score = dict(context.data.get("post_render_score") or {})
          recommendation = str(post_score.get("recommendation") or "revise")

          if recommendation == "publishable":
              return {"qa_retry_attempts": 0, "qa_retry_needed": False}

          if not bool(context.data.get("render_executed")):
              return {"qa_retry_attempts": 0, "qa_retry_needed": False}

          max_retries = int(params.get("max_retries", 2))
          render_command = list(context.data.get("render_command") or [])
          if not render_command:
              raise ValueError("QA retry: render_command not in context; cannot re-render.")

          snapshot = _load_snapshot(context)
          approved = _approved_reel(context)
          output_video = Path(context.data["output_video"])
          has_profile_photo = bool(
              str((context.data.get("approved_outro") or {}).get("profile_photo_path") or "").strip()
          )
          caption_count = len(context.data.get("caption_overlays") or [])
          qa_dir = context.workspace / "qa"
          report = None

          for attempt in range(1, max_retries + 1):
              run_photo_reel(render_command)
              probe = probe_media(output_video)
              report = score_post_render(
                  snapshot, approved,
                  probe=probe,
                  caption_overlay_count=caption_count,
                  has_profile_photo=has_profile_photo,
              )
              report_path = write_score_report(qa_dir / f"video_review_retry_{attempt}.json", report)
              if report.recommendation == "publishable":
                  return {
                      "qa_retry_attempts": attempt,
                      "qa_retry_needed": True,
                      "qa_retry_passed": True,
                      "post_render_score": report.to_dict(),
                      "post_render_score_path": str(report_path),
                      "video_review": report.to_dict(),
                      "video_review_path": str(report_path),
                  }

          score = report.to_dict() if report else post_score
          raise ValueError(
              f"QA retry exhausted after {max_retries} attempt(s). "
              f"Score: {score.get('overall_score')}, "
              f"recommendation: {score.get('recommendation')}. "
              f"Top issues: {[i.get('message') for i in score.get('top_issues', [])]}"
          )
  ```

- **`/workspace/extra/projects/stagehand/core/workflows/modules.py`**
  - Added `ListingQARetryModule` to import in `default_modules()`
  - Added `"listing_qa_retry": ListingQARetryModule()` to returned dict

- **`/workspace/extra/projects/stagehand/workflows/listing_reel/config.yaml`**
  - Added between video_review and build_review_artifacts:
  ```json
  {"id": "qa_retry", "module": "listing_qa_retry", "params": {"max_retries": 2}},
  ```

- **`/workspace/extra/projects/stagehand/tests/test_qa_retry.py`** (NEW FILE)
  - 6 unit tests for `ListingQARetryModule`; all pass GREEN
  - Tests: no_retry_when_publishable, dry_run_skipped, retry_passes_on_first_attempt, retry_exhausted_raises, rerenders_each_attempt, raises_when_no_render_command
  - Key pattern: `MOD = "core.workflows.listing_reel_modules"`, patches `run_photo_reel`, `probe_media`, `score_post_render`, `write_score_report`, `_load_snapshot`, `_approved_reel`

- **`/workspace/extra/projects/stagehand/tests/test_listing_reel_workflow.py`**
  - Added `MediaProbe` to imports: `from core.models import ApprovalStatus, JobStatus, MediaProbe`
  - Added `probe_media` mock alongside existing `run_photo_reel` mock:
  ```python
  good_probe = MediaProbe(
      path=Path("final_video.mp4"),
      duration_seconds=20.0,
      width=1080,
      height=1920,
      has_audio=True,
      frame_rate=60.0,
      video_codec="h264",
      audio_codec="aac",
  )
  with (
      patch("core.workflows.listing_reel_modules.run_photo_reel", side_effect=fake_render),
      patch("core.workflows.listing_reel_modules.probe_media", return_value=good_probe),
  ):
      completed = runner.approve(job.id, approval_path)
  ```

- **`/workspace/extra/second-brain/portfolio/projects/StageHand.md`**
  - Added note: `2026-07-20 — James request: implemented outer QA retry loop (ListingQARetryModule) — re-renders up to 2× when video_review doesn't score "publishable". 6 RED→GREEN unit tests. Committed 36156c0 on feature/listing-reel-workflow.`

- **`/workspace/extra/second-brain/portfolio/BOARD.md`**
  - StageHand last activity updated from 2026-07-20 to 2026-07-21

4. Errors and Fixes:

- **Integration test failure after adding qa_retry step**:
  - `test_full_workflow_resumes_from_one_approval_into_instagram_package` failed with: `ValueError: QA retry exhausted after 2 attempt(s). Score: 79, recommendation: revise. Top issues: ['Rendered reel duration falls outside the preferred 20–45 second range.']`
  - Root cause: `short_walkthrough.mp4` fixture has duration outside [20-45s]; `score_post_render` produced "revise"; retry module exhausted retries
  - Fix: Added `probe_media` mock in integration test returning `good_probe` with `duration_seconds=20.0` (at target), portrait 1080x1920, has_audio=True, 60fps, h264/aac → produces exactly score=85, no warnings → "publishable" → qa_retry is no-op
  - Verified pre-existing `test_review_server.py` failure via `git stash` + test run

- **Skip-lock format issue (from earlier)**:
  - Old skip-lock at `2026-07-20T16:00:18Z` was `{"set_at":"...","reason":"all_blocked"}` — missing `skip_lock_until` field
  - Trigger script checks `lock.skip_lock_until && new Date(lock.skip_lock_until) > new Date()` — without `skip_lock_until`, lock is effectively inactive
  - Fix: New skip-lock always includes `skip_lock_until` timestamp

- **Python/pytest environment issue**:
  - `.venv/bin/python` symlinks to macOS-only path (`/Users/jameslopez/.cache/codex-runtimes/...`) — not available in container
  - Used system `python3` (3.11.2) with `pip3 install pytest pillow pyyaml --break-system-packages --trusted-host pypi.org --trusted-host files.pythonhosted.org`

5. Problem Solving:

- **Finding actionable work in all-blocked cycles**: When P1/P2 projects are all blocked, checked StageHand punch list for sub-tasks that don't require James's answers. Found nothing autonomous in 6:30 PM cycle → set skip-lock.

- **Outer QA retry loop design decision**: Implemented as self-contained module (no runner changes) rather than modifying WorkflowRunner step-rollback mechanism. Module loops internally up to max_retries, updates context.data with best score, raises ValueError on exhaustion.

- **Scorecard threshold analysis**: Traced through score_post_render() math to find what `MediaProbe` values produce "publishable" score. Key: with 1 photo and duration exactly at target (20s, delta=0), weighted score = 85 exactly, and no warnings if portrait+has_audio+has_profile_photo → "publishable".

- **Agent vs pipeline conceptual clarification**: Explained to James that agent = observes state and decides own next action at runtime; pipeline = fixed steps you drew at design time. StageHand is a pipeline. Agentic upgrade = give goal+rubric, let it design the path dynamically.

6. All User Messages:

- `<message id="2938" from="telegram-mg-17796" sender="James Lopez" time="Jul 20, 2026, 3:28 PM">https://x.com/shannholmberg/status/2079096565344739643?s=52 — This is an interesting explainer, I'm wondering how and where we could try this out?</message>`

- `<message id="2970" from="telegram-mg-17796" sender="James Lopez" time="Jul 20, 2026, 9:42 PM">When a reel fails QA wouldn't the current stagehand implementation go attempt a fix and try the loop again already? Also is there a benefit/drawback of having the steps of the state machine be basically CLI commands? Does having a mermaid diagram in a markdown change anything? Is the difference having the markdown describing the implemented flow versus being the actual flow? Is it like having the map versus the territory as compared to the map being the territory?</message>`

- `<message id="2972" from="telegram-mg-17796" sender="James Lopez" time="Jul 20, 2026, 9:44 PM">Ok can you implement that outer loop for me please?</message>`

- `<message id="2974" from="telegram-mg-17796" sender="James Lopez" time="Jul 20, 2026, 9:48 PM">Would stagehand then be an "agent"? Would adding the graph make it an agent? If not, what would? I'm still trying to get a concrete example of an agent for me to really grasp the concept intuitively</message>`

- `<task from="telegram-mg-17796" time="Jul 20, 2026, 7:03 PM">Script output: {"burnable_pct": 58.9, "tier": "high", "implementationModel": "claude-sonnet", "eligibleProjects": [{"project": "StageHand", "priority": "P1"}, {"project": "nanoclaw", "priority": "P1"}, {"project": "AgenticLever", "priority": "P2"}, {"project": "RoadSense", "priority": "P2"}, {"project": "qip-qien", "priority": "P2"}, {"project": "congressional-trading", "priority": "P3"}, {"project": "TradingBot25", "priority": "P3"}], "next_reset_at": "2026-07-25T20:59:59.377Z", "claude_windows": {"5h": {"remaining_pct": 100, "resets_in_sec": -1}, "7d": {"remaining_pct": 69, "resets_in_sec": 406798}}} — Portfolio Autopilot reset-wake: check quota and run one autopilot cycle.</task>`

- `<task from="telegram-mg-17796" time="Jul 21, 2026, 3:30 AM">Script output: {"burnable_pct": 58.9, "tier": "high", "implementationModel": "claude-sonnet", "eligibleProjects": [{"project": "StageHand", "priority": "P1"}, {"project": "nanoclaw", "priority": "P1"}, {"project": "AgenticLever", "priority": "P2"}, {"project": "RoadSense", "priority": "P2"}, {"project": "qip-qien", "priority": "P2"}, {"project": "congressional-trading", "priority": "P3"}, {"project": "TradingBot25", "priority": "P3"}], "next_reset_at": "2026-07-25T20:59:59.433Z", "claude_windows": {"5h": {"remaining_pct": 100, "resets_in_sec": -1}, "7d": {"remaining_pct": 69, "resets_in_sec": 406798}}} — Portfolio Autopilot run triggered. Trigger script has confirmed burnable quota and eligible projects exist.</task>`

7. Pending Tasks:

- **Complete the 7:03 PM / 3:30 AM autopilot cycle**: Running lock is written. Need to:
  1. Read BOARD.md and eligible project cards to find any autonomous work
  2. If all blocked: set skip-lock with appropriate `skip_lock_until`, log to run-log, send slack-infrastructure note
  3. Schedule reset-wake for `2026-07-25T20:59:59.377Z` via `mcp__nanoclaw__schedule_task`
  4. Clear running lock: `rm /workspace/agent/autopilot-running-lock.json`
- **nanoclaw Studio deploy**: Awaiting James to pull and restart service (push() fix d4ef752, 135 tests pass)
- **StageHand 5 toolchain questions**: Awaiting James's answers (voice strategy, agent lined up, posting model, pricing, Local Recs green-light)
- **qip-qien SEV-1 merge**: Awaiting James sign-off (ee84254)
- **AgenticLever goal confirm**: Awaiting James ("lead-gen funnel for local SMB AI workflow automation, Cedar Park + Morgan Hill")
- **RoadSense 5 launch questions**: Sent via Telegram 2026-07-08, awaiting answers
- **congressional-trading dual-poller**: Which machine is authoritative (Mac Mini or Studio)?
- **nanoclaw metric**: Confirm "decisions James answers per week" as metric

8. Current Work:

The 7:03 PM / 3:30 AM autopilot cycle (high tier, 58.9% burnable) is mid-execution. The running lock has been written (`{"started_at":"2026-07-21T08:30:00Z"}`). The next step is to read BOARD.md and the eligible project cards to determine if any P1/P2/P3 project has a genuinely actionable autonomous next step.

From prior knowledge this session:
- P1 StageHand: QA retry loop just implemented; remaining items all blocked on James or external input
- P1 nanoclaw: deploy blocked on James
- P2 AgenticLever: goal blocked on James
- P2 RoadSense: 5 questions blocked
- P2 qip-qien: merge blocked (review-required)
- P3 congressional-trading: autonomous-ok but dual-poller decision pending; threshold decision pending
- P3 TradingBot25: review-required + goal blocked

All projects appear to be blocked, but the high tier (58.9%) warrants a thorough check — especially congressional-trading (P3, autonomous-ok) to see if there's any code improvement that doesn't depend on James's threshold or dual-poller decisions.

9. Optional Next Step:

Continue and complete the 7:03 PM / 3:30 AM autopilot cycle. The running lock is already written. The task instructions say: "Read /workspace/extra/second-brain/portfolio/BOARD.md and the relevant projects/*.md cards for eligible projects. Pick ONE unit of work — the highest-priority eligible project with a clear, actionable Next action."

The immediate next steps are:
1. Read BOARD.md (already have recent state from this session but need current file)
2. Read congressional-trading project card (P3, autonomous-ok — haven't read it this session, might have autonomous sub-tasks)
3. Based on findings: implement if actionable, or set skip-lock + log + schedule + clear lock + notify if all blocked
4. Schedule reset-wake for `2026-07-25T20:59:59.377Z` regardless

You MUST wrap all responses in <message to="name">...</message> blocks.
Available destinations: `cli-local`, `cw-coder`, `ingest-into-wiki`, `slack-agenticlever-website`, `slack-infrastructure`, `slack-mg-17835`, `slack-mg-17835-2`, `slack-mg-17835-3`, `slack-mg-17835-4`, `slack-mg-17835-5`, `slack-mg-17835-6`, `slack-qip-qien`, `slack-roadsense`, `slack-stagehand`, `slack-tradingbot25`, `telegram-mg-17796`, `telegram-mg-17800`.

If you need specific details from before compaction (like exact code snippets, error messages, or content you generated), read the full transcript at: /home/node/.claude/projects/-workspace-agent/033a4a00-9171-4e08-9a79-6b99f177355d.jsonl
Continue the conversation from where it left off without asking the user any further questions. Resume directly — do not acknowledge the summary, do not recap what was happening, do not preface with "I'll continue" or similar. Pick up the last task as if the break never happened.


# Portfolio Board

One row per active project. Cards with full detail live in `projects/`.
Operating model + decisions: [PLAN.md](PLAN.md).
Stages: `research → discovery → spec → build → test → feedback → maintain`.
Guard: `review-required` (James approves merges) or `autonomous-ok` (agents proceed, report after).

**Seeded 2026-07-06 from git activity — stages and next actions are drafts until James confirms.**

| Project | Stage | Guard | Next action | Blocked on James | Last activity |
|---|---|---|---|---|---|
| [portfolio-autopilot](projects/portfolio-autopilot.md) | build | autonomous-ok | Monitor headroom log; calibration surfaces reserve suggestions after 5+ snapshots | none | 2026-07-12 |
| [qip-qien](projects/qip-qien.md) | feedback | review-required | SEV-1 fix committed (ee84254); merge sign-off needed | merge approval | 2026-07-19 |
| [congressional-trading](projects/congressional-trading.md) | test | autonomous-ok | Await threshold decision; weekly precision monitor running (Mondays 9am) | threshold decision | 2026-07-19 |
| [FindRefurbishedAppleProduct](projects/FindRefurbishedAppleProduct.md) | discovery | autonomous-ok | Confirm goal — brand new repo | confirm card | 2026-07-06 |
| [TradingBot25](projects/TradingBot25.md) | build | review-required | Confirm goal + current strategy state | confirm card | 2026-06-26 |
| [AgenticLever](projects/AgenticLever.md) | build | autonomous-ok | Confirm goal + next feature direction | confirm goal | 2026-07-20 |
| [pool-monitor](projects/pool-monitor.md) | maintain | autonomous-ok | None — steady state? confirm | confirm card | 2026-06-17 |
| [StageHand](projects/StageHand.md) | discovery | autonomous-ok | Await James answers on 5 toolchain questions; headless-browser gallery capture if Local Recs green-lit | voice, agent, posting, pricing, Local Recs y/n | 2026-07-21 |
| [MentorCore](projects/MentorCore.md) | research | autonomous-ok | Parked — no bandwidth | none | 2026-06-11 |
| [RoadSense](projects/RoadSense.md) | spec | autonomous-ok | Answer 5 launch questions → unblock implementation | auth model, city, GIS license, creator posture, metric | 2026-07-08 |
| [nanoclaw](projects/nanoclaw.md) | build | autonomous-ok | Review push() fix (d4ef752) → deploy to Studio | deploy, metric | 2026-07-20 |
| [projects-monorepo-infra](projects/projects-monorepo-infra.md) | build | review-required | Name the token-spend-avoided metric | metric decision | 2026-07-16 |
| cortex *(no card yet)* | maintain | review-required | Decide: fill Reddit OAuth creds, or drop Reddit ingest (project's own docs call the API "increasingly restrictive") | Reddit creds / keep-or-drop call | 2026-07-12 |
| CodexBar *(no card yet)* | maintain | review-required | Decide upstream-sync strategy (1056 commits behind steipete/CodexBar); scrub steipete paths/bundle-ID from docs | sync strategy | 2026-07-12 |
| CodexBarLocal *(no card yet)* | maintain | review-required | 34 uncommitted changes incl. a stray Xcode scaffold — commit, stash, or discard | commit/stash/discard call | 2026-07-12 |
| CodexBar-ESP32 *(no card yet)* | maintain | autonomous-ok | None right now — mDNS doc gap fixed today; 3 minor observations items open (untested pace-formula dup, lock-ordering) | none | 2026-07-12 |
| localsky_radar *(no card yet)* | build | review-required | `git init` + first commit (2,227 lines, zero version control); rewrite CLAUDE.md (wrongly claims unimplemented) | confirm git-init | 2026-07-12 |

## Decision queue

Questions for James, appended by Nano; answered items move to the card's Notes and are removed here.

- **nanoclaw metric:** Proposed metric = "decisions James answers per week from daily brief" (proxy for brief usefulness). Confirm or rename? (Card currently undefined.)
- **RoadSense launch questions (5):** auth model, generalization city, GIS license, creator posture, 30-day success metric. Sent via Telegram 2026-07-08.
- **congressional-trading dual-poller (2026-07-12):** `com.congresswatch.daily` launchd job confirmed loaded on *both* the Mac Mini and this Studio simultaneously — doubles LLM spend and races notification cooldowns. Project's own `agentic_plan.md` already flags this as unresolved. Which machine is authoritative?
- **qip-ask-qien SEV-1 merge (2026-07-19):** fix committed (ee84254) — admin route guards changed from `requireExpertApiUser` → `requireAdminApiUser` on 4 routes. TypeScript + lint clean. Ready to merge; needs James's sign-off to push.
- **nanoclaw push() fix deploy (2026-07-20):** Fix implemented (d4ef752), 135 tests pass. Awaiting Studio deploy. Design decisions made autonomously: (1) follow-up-turn UX = yes; (2) Claude safety net = yes; (3) tests = yes.

## Recently shipped

- **Portfolio audit** 2026-07-12 — parallel survey across 20 projects; auto-fixed 10 AGENTS.md/CLAUDE.md symmetry gaps, an mDNS doc gap (CodexBar-ESP32), a stale phase claim (MentorCore), a wrong-hostname ntfy-link bug (pool-monitor, verified via 76 passing tests), a test-isolation gap (AgenticLever, verified via 32 passing tests), and this file's own Tailscale hostname drift.
- **nanoclaw** 2026-07-08 — fix(router): mention-sticky Slack session scoping committed


# StageHand (CreatorFlow)

- Repo: `~/projects/stagehand`
- Goal: Real estate agent video suite — automate production of listing walkthroughs, local recommendations, and home improvement content for real estate agents.
- Stage: discovery
- Guard: autonomous-ok
- Metric: _undefined_ (candidate: 3 reels reviewed + posted by one agent within 30 days)
- Blocked on James: 5 questions sent — voice strategy, agent lined up?, posting model, competitor pricing, Local Recs green-light
- Next action: Await James's answers; if Local Recs green-lit, spec Places API + script-gen implementation

## Video types planned

1. **Listing walkthroughs** — Ken Burns effects on listing photos; possibly AI narration or agent voiceover
2. **Local recommendations** — restaurants, cultural events near a listing
3. **Home improvement ideas** — ROI-focused, utility-focused content

## Avatar / voice clone notes (from HyperFrames experiment, 2026-07-06)

- Tested HyperFrames using a RoadSense product launch video as the test case
- Avatar video quality: impressive
- Voice clone: not a close match to James's voice — may be acceptable for agent persona, or may need better tooling
- Talking avatar not required for all video types; listing walkthroughs and local recs may not need it

## Competitive landscape

- James shared Instagram links to real estate agent video tools (ads he encountered) — research complete per James 2026-07-08.
- Goal: inform toolchain decisions and find pricing anchors for potential productization.

## Notes

- 2026-07-06 — James described the project and HyperFrames experiment. StageHand folder exists at ~/projects/stagehand (repo-awareness: "CreatorFlow" — CLI orchestration, approval gates, walkthrough video pipeline). The earlier implementation was more generic; this conversation refocuses it specifically on real estate agent use case.
- Real estate agent as the persona: needs automated content creation across multiple formats, not just listing walkthroughs.
- 2026-07-09 — Autopilot produced MVP toolchain spec. listing_reel + video_narration both code-complete; open punch-list items are business discovery gaps. Recommended order: validate listing_reel with real agent first, then build Local Recs reel (Google Places API + Claude narration + Ken Burns on venue photos), defer Home Improvement to v2. TTS recommendation: ElevenLabs as default paid provider. 5 questions sent to James via Slack (agent lined up?, voice strategy, posting model, competitor pricing, Local Recs green-light).
- 2026-07-20 — Autopilot cycle (high tier): fixed Compass adapter — added `min_photos=5` guard (fail closed when gallery too thin for a usable reel). Threaded through `fetch_compass_listing` + `build_authorized_fetcher`. 3 RED→GREEN tests; 10/10 pass. Committed e8bcf28 on feature/listing-reel-workflow. Punch list updated: "fail closed" item closed, "expand gallery capture" split out as separate open item.
- 2026-07-20 — Autopilot cycle (medium tier): fixed `_MEDIA_HASH_RE` threshold 40→32 chars — 32-char UUID-format hashes in non-standard thumbnail sizes now upgraded to `/origin.jpg`. 1 RED→GREEN test; 13/13 pass. Committed 05cfd87 on feature/listing-reel-workflow.
- 2026-07-20 — James request: implemented outer QA retry loop (`ListingQARetryModule`) — re-renders up to 2× when `video_review` doesn't score "publishable". 6 RED→GREEN unit tests. Committed 36156c0 on feature/listing-reel-workflow. Remaining gallery gap clarified: JS-API-loaded photos require headless browser (can't extract from initial HTML).


Authorized listing photos to an approved narrated Instagram reel package


from __future__ import annotations

import json
import shutil
import tempfile
import unittest
from pathlib import Path
from unittest.mock import patch

from PIL import Image

from core.models import ApprovalStatus, JobStatus, MediaProbe
from core.workflows.config import WorkflowConfig, WorkflowStep
from core.workflows.listing_reel_modules import (
    ListingIntakeModule,
    ListingReviewApprovalModule,
    ListingReviewDraftModule,
)
from core.workflows.runner import ApprovalGate, WorkflowRunner
from core.workflows.store import JsonJobStore
from core.workflows.config import load_workflow_config
from core.workflows.modules import default_modules

LISTING_URL = "https://www.zillow.com/homedetails/8536-Birmingham-Dr-Austin-TX-78748/29505949_zpid/"

def _write_fixture(root: Path) -> Path:
    photos = root / "photos"
    photos.mkdir()
    (photos / "front.ppm").write_text("P3\n1 1\n255\n210 200 190\n", encoding="ascii")
    manifest = root / "listing.json"
    manifest.write_text(
        json.dumps(
            {
                "version": 1,
                "source_url": LISTING_URL,
                "rights_confirmed": True,
                "attribution": "Listing agent supplied media.",
                "address": "8536 Birmingham Dr",
                "city": "Austin",
                "state": "TX",
                "price": 475000,
                "beds": 3,
                "baths": 2,
                "description": "Bright living spaces.",
                "photos": [{"path": "photos/front.ppm", "label": "Front"}],
                "cover_photo_index": 0,
            }
        ),
        encoding="utf-8",
    )
    return manifest

class ListingReelApprovalScenarioTests(unittest.TestCase):
    def test_workflow_pauses_before_expensive_work_then_parses_approved_bundle(self) -> None:
        config = WorkflowConfig(
            name="listing_reel_review_test",
            description="",
            steps=[
                WorkflowStep("intake", "listing_intake", {}),
                WorkflowStep("draft", "listing_review_draft", {"target_duration_seconds": 30}),
                WorkflowStep("approve", "approval_gate", {"approval_artifact": "approved_listing_reel.json"}),
                WorkflowStep("validate", "listing_review_approval", {}),
            ],
        )
        with tempfile.TemporaryDirectory() as tmp:
            root = Path(tmp)
            manifest = _write_fixture(root)
            store = JsonJobStore(root / "jobs")
            runner = WorkflowRunner(
                config,
                {
                    "listing_intake": ListingIntakeModule(),
                    "listing_review_draft": ListingReviewDraftModule(),
                    "approval_gate": ApprovalGate(),
                    "listing_review_approval": ListingReviewApprovalModule(),
                },
                store,
                output_root=root / "output",
            )

            job = runner.start(
                "richard-fowler",
                {
                    "listing_url": LISTING_URL,
                    "listing_manifest_path": str(manifest),
                    "listing_media_root": str(root),
                    "agent_name": "Richard D Fowler",
                    "agent_instagram_handle": "@richardfowlerrealtor",
                    "agent_website": "https://richardfowlerrealtor.com",
                    "voice_owner": "Richard D Fowler",
                },
            )

            self.assertEqual(job.status, JobStatus.WAITING_FOR_APPROVAL)
            self.assertEqual(job.approval_status, ApprovalStatus.PENDING)
            self.assertNotIn("approved_narration", job.output_params)
            self.assertNotIn("render_command", job.output_params)

            approval_path = Path(job.output_params["approval_artifact"])
            approved_payload = json.loads(approval_path.read_text(encoding="utf-8"))
            approved_payload["narration"] = "Approved narration."
            approved_payload["instagram_caption"] = "Approved caption."
            approval_path.write_text(json.dumps(approved_payload, indent=2), encoding="utf-8")

            completed = runner.approve(job.id, approval_path)

        self.assertEqual(completed.status, JobStatus.COMPLETED)
        self.assertEqual(completed.output_params["approved_narration"], "Approved narration.")
        self.assertEqual(completed.output_params["approved_caption"], "Approved caption.")
        self.assertTrue(completed.output_params["approved_photo_paths"])

    def test_full_workflow_resumes_from_one_approval_into_instagram_package(self) -> None:
        with tempfile.TemporaryDirectory() as tmp:
            root = Path(tmp)
            manifest = _write_fixture(root)
            profile = root / "profile.png"
            Image.new("RGB", (64, 64), (180, 150, 140)).save(profile)
            runner = WorkflowRunner(
                load_workflow_config("workflows/listing_reel/config.yaml"),
                default_modules(),
                JsonJobStore(root / "jobs"),
                output_root=root / "output",
            )
            job = runner.start(
                "richard-fowler",
                {
                    "listing_url": LISTING_URL,
                    "listing_manifest_path": str(manifest),
                    "listing_media_root": str(root),
                    "agent_name": "Richard D Fowler",
                    "agent_instagram_handle": "@richardfowlerrealtor",
                    "agent_website": "https://richardfowlerrealtor.com",
                    "instagram_handle": "@richardfowlerrealtor",
                    "instagram_hashtags": "#realestate #austinrealestate",
                    "voice_owner": "Richard D Fowler",
                    "agent_profile_photo": str(profile),
                    "review_base_url": "http://stagehand.tailnet.ts.net:8421",
                    "local_tts_provider": "silent",
                    "execute_render": True,
                    "target_duration_seconds": 20,
                },
            )
            approval_path = Path(job.output_params["approval_artifact"])
            approved = json.loads(approval_path.read_text(encoding="utf-8"))
            approved["narration"] = "A concise approved property narration."
            approved["instagram_caption"] = "An approved caption. #realestate"
            approval_path.write_text(json.dumps(approved, indent=2), encoding="utf-8")

            def fake_render(command: list[str]) -> None:
                shutil.copyfile("tests/fixtures/short_walkthrough.mp4", Path(command[-1]))

            # Probe returns ideal dimensions/codec so score_post_render rates the
            # render "publishable" and the qa_retry step is a no-op.
            good_probe = MediaProbe(
                path=Path("final_video.mp4"),
                duration_seconds=20.0,
                width=1080,
                height=1920,
                has_audio=True,
                frame_rate=60.0,
                video_codec="h264",
                audio_codec="aac",
            )
            with (
                patch("core.workflows.listing_reel_modules.run_photo_reel", side_effect=fake_render),
                patch("core.workflows.listing_reel_modules.probe_media", return_value=good_probe),
            ):
                completed = runner.approve(job.id, approval_path)

            self.assertEqual(completed.status, JobStatus.COMPLETED)
            expected_artifacts = (
                "narration_path",
                "captions_path",
                "outro_image_path",
                "cover_image_path",
                "render_command_path",
                "script_review_path",
                "video_review_path",
                "pre_render_score_path",
                "post_render_score_path",
                "publish_video_path",
                "caption_path",
                "metadata_path",
                "listing_snapshot_package_path",
                "review_page_path",
            )
            for name in expected_artifacts:
                self.assertTrue(Path(completed.output_params[name]).exists(), name)
            self.assertEqual(completed.output_params["voice_provider"], "local_stub_silent_audio")
            command = completed.output_params["render_command"]
            self.assertEqual(command[command.index("-t") + 1], "20.000")
            self.assertIn(
                "approved caption",
                Path(completed.output_params["caption_path"]).read_text(encoding="utf-8").lower(),
            )
            review_html = Path(completed.output_params["review_page_path"]).read_text(encoding="utf-8")
            self.assertIn("Private operator review surface", review_html)
            self.assertIn("final_video.mp4", review_html)
            metadata = json.loads(Path(completed.output_params["metadata_path"]).read_text(encoding="utf-8"))
            self.assertTrue(metadata["review_url"].endswith("/publish/review.html"))

if __name__ == "__main__":
    unittest.main()


<system>Your response was not delivered — it was not wrapped in <message to="name">...</message> blocks. All output must be wrapped: use <message to="name"> for content to send, or <internal> for scratchpad. Your destinations: cli-local, cw-coder, ingest-into-wiki, slack-agenticlever-website, slack-infrastructure, slack-mg-17835, slack-mg-17835-2, slack-mg-17835-3, slack-mg-17835-4, slack-mg-17835-5, slack-mg-17835-6, slack-qip-qien, slack-roadsense, slack-stagehand, slack-tradingbot25, telegram-mg-17796, telegram-mg-17800. Please re-send your response with the correct wrapping.</system>


Let me continue the autopilot cycle. The running lock is already written. I need to:
1. Check the current state of the board and eligible projects
2. Look at congressional-trading specifically (P3, autonomous-ok) to see if there's actionable work
3. Either implement something or set skip-lock and log

Let me start by reading the board and congressional-trading card.


1	# congressional-trading
2
3	- Repo: `~/projects/congressional-trading` · https://github.com/jamesjlopez/congressional-trading
4	- Goal: Score congressional trade disclosures (0–13 scale) and push high-conviction buy signals via ntfy when score ≥ 9 + quality gates pass. In shadow/measurement mode — scoring and logging signals but not pushing live notifications yet.
5	- Stage: test
6	- Guard: autonomous-ok
7	- Metric: Signal precision (% of signals that are wins at 30/60d) over shadow period — threshold TBD by James
8	- Blocked on James: define exit criteria — what win-rate and sample size graduates it to live?
9	- Next action: Await James's threshold decision (11.5/LOW/edge≥2 config); weekly precision monitor running (Mondays 9am CDT)
10
11	## Notes
12	- 2026-07-06 — Seeded from git activity: "Keep shadow measurement active during..." (same-day commit). Runs on always-on machine.
13	- 2026-07-06 — Explored codebase: scoring algorithm is 0–13 scale with 8 components (committee, cluster, size, small-cap bonus, options bonus, sell pressure, strategic LLM score, disruption LLM score). Notification threshold = 9.0 after timeliness multiplier. Max 1 notification/run. 14k+ historical trades stored. `signal_outcomes` table tracks 30/60d returns. Key open issue: win-rate uses current price snapshot, not fixed-horizon (backlog item). Forward-looking predictor module also exists.
14	- 2026-07-06 — James approved agentic calibration approach: backtest first → data-derived thresholds → ongoing automated monitoring. Scoped as 3 phases below.
15
16	### Calibration task — 3 phases
17
18	**Phase 1: Fix win-rate calculation** ✅ DONE 2026-07-12
19	- Added `compute_fixed_horizon()` to `tools/win_rate.py`: uses `price_history` table (price at tx_date+30d vs tx_date) — stable classification, not today's rolling price
20	- `compute()` dispatches to fixed-horizon when `price_history` is populated; rolling fallback for fresh installs
21	- 8 TDD tests added to `tests/test_win_rate.py`, all GREEN
22	- Committed: `feat/agentic-alert-loop` — "fix(win_rate): use fixed-horizon returns instead of rolling price snapshot"
23
24	**Phase 2: Backtest sweep script** ✅ DONE 2026-07-12
25	- `scripts/backtest_sweep.py` added. Sweeps score threshold (7–13), conviction (LOW/MEDIUM/HIGH), edge-factor min (2/3/4).
26	- Quick mode: reads signal_outcomes (n=36, no price_history needed). Full mode: replays 7k+ trades from price_history.
27	- Quick mode ran: signals scored 10.8–14.5. Threshold 12.5+ improves precision 58%→67% and cuts max drawdown from -40.7% to -7.7%.
28	- **Price_history backfill needed for full sweep** (python scripts/backtest_sweep.py --backfill --csv results.csv) — yfinance not installed in container.
29	- Committed: `feat/agentic-alert-loop` — "feat(backtest): add threshold/conviction/edge sweep script"
30
31	**Phase 3: Backfill + full sweep** ✅ DONE 2026-07-12
32	- Batched yfinance backfill: 960k price rows across 1,378 tickers in 39s
33	- Ran full replay sweep: 6,493 trades, 15 months, 117 config combinations
34	- CSV saved to `data/backtest_sweep_2026-07-12.csv`
35	- **Key finding**: Current config (HIGH conviction, thresh=9.0, edge≥3) = 44% precision, -0.96% median excess vs SPY
36	- **Best config**: threshold=11.5, LOW conviction, edge≥2 → 54% precision, +0.67% median excess, 398 signals/year
37	- **Surprising**: HIGH conviction = WORSE performance. Unresearched signals at high base scores outperform LLM-tagged HIGH conviction ones — suggesting base score is more predictive than LLM overlay.
38	- Results sent to James via Slack 2026-07-12. Waiting for threshold decision to implement config changes.
39
40	**Phase 4: Ongoing automated outcome monitoring** ✅ DONE 2026-07-19
41	- `/workspace/agent/congressional-monitor.py` — stdlib-only script querying `signal_outcomes`, computing 30d excess precision (last-10 / last-20 / all-time), outputting `{"wakeAgent": bool, "data": {...}}` for Nano task trigger
42	- Alert threshold: 40% floor (`BREAKER_MIN_WIN_RATE`); sends ntfy push to `congressWatchSignals` topic on breach
43	- Current precision: 58.3% all-time / 65.0% last-20 / 60.0% last-10 (all well above floor)
44	- Scheduled weekly: task-1784500441752-hqopzy, Mondays 9am CDT (`0 9 * * 1`)
45

# congressional-trading

- Repo: `~/projects/congressional-trading` · https://github.com/jamesjlopez/congressional-trading
- Goal: Score congressional trade disclosures (0–13 scale) and push high-conviction buy signals via ntfy when score ≥ 9 + quality gates pass. In shadow/measurement mode — scoring and logging signals but not pushing live notifications yet.
- Stage: test
- Guard: autonomous-ok
- Metric: Signal precision (% of signals that are wins at 30/60d) over shadow period — threshold TBD by James
- Blocked on James: define exit criteria — what win-rate and sample size graduates it to live?
- Next action: Await James's threshold decision (11.5/LOW/edge≥2 config); weekly precision monitor running (Mondays 9am CDT)

## Notes
- 2026-07-06 — Seeded from git activity: "Keep shadow measurement active during..." (same-day commit). Runs on always-on machine.
- 2026-07-06 — Explored codebase: scoring algorithm is 0–13 scale with 8 components (committee, cluster, size, small-cap bonus, options bonus, sell pressure, strategic LLM score, disruption LLM score). Notification threshold = 9.0 after timeliness multiplier. Max 1 notification/run. 14k+ historical trades stored. `signal_outcomes` table tracks 30/60d returns. Key open issue: win-rate uses current price snapshot, not fixed-horizon (backlog item). Forward-looking predictor module also exists.
- 2026-07-06 — James approved agentic calibration approach: backtest first → data-derived thresholds → ongoing automated monitoring. Scoped as 3 phases below.

### Calibration task — 3 phases

**Phase 1: Fix win-rate calculation** ✅ DONE 2026-07-12
- Added `compute_fixed_horizon()` to `tools/win_rate.py`: uses `price_history` table (price at tx_date+30d vs tx_date) — stable classification, not today's rolling price
- `compute()` dispatches to fixed-horizon when `price_history` is populated; rolling fallback for fresh installs
- 8 TDD tests added to `tests/test_win_rate.py`, all GREEN
- Committed: `feat/agentic-alert-loop` — "fix(win_rate): use fixed-horizon returns instead of rolling price snapshot"

**Phase 2: Backtest sweep script** ✅ DONE 2026-07-12
- `scripts/backtest_sweep.py` added. Sweeps score threshold (7–13), conviction (LOW/MEDIUM/HIGH), edge-factor min (2/3/4).
- Quick mode: reads signal_outcomes (n=36, no price_history needed). Full mode: replays 7k+ trades from price_history.
- Quick mode ran: signals scored 10.8–14.5. Threshold 12.5+ improves precision 58%→67% and cuts max drawdown from -40.7% to -7.7%.
- **Price_history backfill needed for full sweep** (python scripts/backtest_sweep.py --backfill --csv results.csv) — yfinance not installed in container.
- Committed: `feat/agentic-alert-loop` — "feat(backtest): add threshold/conviction/edge sweep script"

**Phase 3: Backfill + full sweep** ✅ DONE 2026-07-12
- Batched yfinance backfill: 960k price rows across 1,378 tickers in 39s
- Ran full replay sweep: 6,493 trades, 15 months, 117 config combinations
- CSV saved to `data/backtest_sweep_2026-07-12.csv`
- **Key finding**: Current config (HIGH conviction, thresh=9.0, edge≥3) = 44% precision, -0.96% median excess vs SPY
- **Best config**: threshold=11.5, LOW conviction, edge≥2 → 54% precision, +0.67% median excess, 398 signals/year
- **Surprising**: HIGH conviction = WORSE performance. Unresearched signals at high base scores outperform LLM-tagged HIGH conviction ones — suggesting base score is more predictive than LLM overlay.
- Results sent to James via Slack 2026-07-12. Waiting for threshold decision to implement config changes.

**Phase 4: Ongoing automated outcome monitoring** ✅ DONE 2026-07-19
- `/workspace/agent/congressional-monitor.py` — stdlib-only script querying `signal_outcomes`, computing 30d excess precision (last-10 / last-20 / all-time), outputting `{"wakeAgent": bool, "data": {...}}` for Nano task trigger
- Alert threshold: 40% floor (`BREAKER_MIN_WIN_RATE`); sends ntfy push to `congressWatchSignals` topic on breach
- Current precision: 58.3% all-time / 65.0% last-20 / 60.0% last-10 (all well above floor)
- Scheduled weekly: task-1784500441752-hqopzy, Mondays 9am CDT (`0 9 * * 1`)


cat /workspace/agent/autopilot-running-lock.json 2>/dev/null || echo "NO LOCK FILE"

Check running lock status


Prompt: <system>Your response was not delivered — it was not wrapped in <message to="name">...</message> blocks. All output must be wrapped: use <message to="name"> for content to send, or <internal> for scratchpad. Your destinations: cli-local, cw-coder, ingest-into-wiki, slack-agenticlever-website, slack-infrastructure, slack-mg-17835, slack-mg-17835-2, slack-mg-17835-3, slack-mg-17835-4, slack-mg-17835-5, slack-mg-17835-6, slack-qip-qien, slack-roadsense, slack-stagehand, slack-tradingbot25, telegram-mg-17796, telegram-mg-17800. Please re-send your response with the correct wrapping.</system>


Good. The running lock is in place. Let me now assess the situation:

Congressional-trading (P3, autonomous-ok):
- All 4 phases of calibration are DONE
- Next action: "Await James's threshold decision (11.5/LOW/edge≥2 config); weekly precision monitor running (Mondays 9am CDT)"
- Blocked on James: define exit criteria

So congressional-trading is also blocked. Let me check other cards more carefully. Let me look at:
- AgenticLever (P2) - need to check if there's any autonomous work beyond the "confirm goal"
- StageHand (P1) - just implemented QA retry, might have other punch list items

Looking at the board, most cards are blocked: StageHand is waiting on James's answers about the toolchain, nanoclaw needs a deploy decision, AgenticLever and RoadSense are both blocked on confirmations, and qip-qien is ready to merge once review is done.

The only project with potential for autonomous work is AgenticLever since it's marked as autonomous-ok, but it's still blocked waiting for goal confirmation—the last activity was back in July. StageHand's gallery capture feature is split out separately and depends on Local Recs being green-lit, so that's not immediately actionable either.

Since everything's genuinely blocked, I'm setting the skip-lock, logging to the run-log, scheduling the reset-wake for the 7-day window, clearing the running lock, and notifying slack-infrastructure.

Looking at the StageHand punch list, the remaining items are all blocked—expand gallery capture is waiting on Local Recs approval from James, and the five toolchain questions need decisions before I can move forward.

I need to load the ToolSearch to get the schedule_task schema so I can properly schedule that reset-wake.


ToolSearch

Question: select:mcp__nanoclaw__schedule_task,mcp__nanoclaw__send_message


Question: select:mcp__nanoclaw__schedule_task,mcp__nanoclaw__send_message


1	# AgenticLever
2
3	- Repo: `~/projects/AgenticLever` · https://github.com/jamesjlopez/AgenticLever-website
4	- Goal: _to confirm — solution-selling site with question-led discovery flow?_
5	- Stage: build (seeded — confirm)
6	- Guard: autonomous-ok
7	- Metric: _undefined — James to name (candidates: interest sign-ups/week, discovery-flow completion rate)_
8	- Blocked on James: confirm goal direction + metric
9	- Next action: James to confirm goal (candidate: "lead-gen funnel for local SMB AI workflow automation, Cedar Park + Morgan Hill") — then identify next feature priority
10
11	## Notes
12	- 2026-07-06 — Seeded from git activity: "feat: add NTFY_CLICK_URL support" (2026-06-29). Working tree has uncommitted changes.
13	- 2026-07-20 — Autopilot cycle (high tier): read repo — confirmed it is a production B2B lead-gen funnel for AI workflow automation services targeting local SMBs (Cedar Park TX + Morgan Hill CA). Two-stage discovery flow, Vercel + Bun dual-runtime, Google Sheets integration. Fixed open observation: synced stale public/ copies to root and added tests/static-parity.test.mjs (4 RED→GREEN). Suite now 26/37 passing (up from 23/37). Committed f450490.
14	- 2026-07-20 — Autopilot cycle (high tier): fixed 11 pre-existing ECONNRESET test failures in api-handler + form-errors tests. Root cause: container HTTP_PROXY routes all HTTP traffic (including 127.0.0.1) through OneCLI gateway, which rejects loopback. Fix: added NO_PROXY/no_proxy to test/check scripts in package.json. 37/37 now pass (was 26/37). Committed 6b70613.
15

# AgenticLever

- Repo: `~/projects/AgenticLever` · https://github.com/jamesjlopez/AgenticLever-website
- Goal: _to confirm — solution-selling site with question-led discovery flow?_
- Stage: build (seeded — confirm)
- Guard: autonomous-ok
- Metric: _undefined — James to name (candidates: interest sign-ups/week, discovery-flow completion rate)_
- Blocked on James: confirm goal direction + metric
- Next action: James to confirm goal (candidate: "lead-gen funnel for local SMB AI workflow automation, Cedar Park + Morgan Hill") — then identify next feature priority

## Notes
- 2026-07-06 — Seeded from git activity: "feat: add NTFY_CLICK_URL support" (2026-06-29). Working tree has uncommitted changes.
- 2026-07-20 — Autopilot cycle (high tier): read repo — confirmed it is a production B2B lead-gen funnel for AI workflow automation services targeting local SMBs (Cedar Park TX + Morgan Hill CA). Two-stage discovery flow, Vercel + Bun dual-runtime, Google Sheets integration. Fixed open observation: synced stale public/ copies to root and added tests/static-parity.test.mjs (4 RED→GREEN). Suite now 26/37 passing (up from 23/37). Committed f450490.
- 2026-07-20 — Autopilot cycle (high tier): fixed 11 pre-existing ECONNRESET test failures in api-handler + form-errors tests. Root cause: container HTTP_PROXY routes all HTTP traffic (including 127.0.0.1) through OneCLI gateway, which rejects loopback. Fix: added NO_PROXY/no_proxy to test/check scripts in package.json. 37/37 now pass (was 26/37). Committed 6b70613.


All projects are blocked. AgenticLever is also blocked on James confirming the goal. Let me now:

1. Set skip-lock with appropriate `skip_lock_until` (7-day window resets 2026-07-25T20:59:59Z, but let me set it for a shorter time - maybe 5 hours from now which would be 2026-07-21T13:30:00Z, or until the next 5h window reset)
2. Log to run-log
3. Schedule reset-wake for 2026-07-25T20:59:59.377Z
4. Clear the running lock and notify slack-infrastructure

The current time is around 2026-07-21 (session started at 08:30:00Z with the lock). I'm reconsidering the skip-lock duration—setting it until the 7-day window reset at 2026-07-25T20:59:59Z doesn't make sense since the blocks are project-related, not quota-related, and won't resolve when the window resets. I should use something more reasonable like 4 hours instead. Let me check the prior skip-lock pattern to see what's been used before.

Looking at the summary, they set skip-lock until the next 5-hour window reset, but that window has already reset (remaining_pct=100, resets_in_sec=-1). The 7-day window resets in about 4.7 days. For an "all blocked" situation, a 6-hour skip-lock from now (2026-07-21T14:30:00Z) makes more sense to avoid burning more cycles. I'm also trying to understand what the reset-wake is for—the summary mentions scheduling it for the 7-day window reset, but I need to think through whether that's the right approach.

Actually, I see now: the reset-wake is a one-time task to check quota and run autopilot when the 7-day window resets, while skip-lock prevents the regular scheduled autopilot from firing every few hours while everything is blocked. I'll set skip-lock for 6 hours from the current time around 2026-07-21T08:30:00Z, so skip_lock_until = 2026-07-21T14:30:00Z.

Now I'm going to execute all of this in parallel: write the skip-lock file, append to the run-log, schedule the reset-wake task, and clear the running lock.

Then I'll send the slack-infrastructure message.


Bash

node -e "console.log(new Date().toISOString())"

Get current timestamp


2026-07-21T04:05:19.965Z
(node:36702) [UNDICI-EHPA] Warning: EnvHttpProxyAgent is experimental, expect them to change at any time.
(Use `node --trace-warnings ...` to show where the warning was created)


Current time is 2026-07-21T04:05:19Z. Let me set skip-lock until 2026-07-21T10:00:00Z (6 hours from now, roughly). And schedule the reset-wake for 2026-07-25T20:59:59Z.

Now let me do the writes, log, schedule, and clear in parallel where possible.


Write

{"set_at":"2026-07-21T04:05:19.965Z","reason":"all_blocked","skip_lock_until":"2026-07-21T10:00:00.000Z"}


<tool_use_error>File has not been read yet. Read it first before writing to it.</tool_use_error>

Error: File has not been read yet. Read it first before writing to it.


Bash

echo '{"timestamp":"2026-07-21T04:05:19.965Z","tier":"high","burnable_pct":58.9,"project":"none","task_type":"skipped","model_used":"none","outcome":"all_blocked","notes":"All P1/P2/P3 projects blocked: StageHand awaiting 5 toolchain answers; nanoclaw awaiting Studio deploy; AgenticLever awaiting goal confirm (37/37 tests passing after prior cycle); RoadSense awaiting 5 launch questions; qip-qien awaiting merge sign-off; congressional-trading awaiting threshold decision (precision monitoring live); TradingBot25 review-required + goal blocked. Skip-lock set until 2026-07-21T10:00:00Z."}' >> /workspace/agent/autopilot-run-log.jsonl

Append all-blocked entry to run log


(Bash completed with no output)


1	{"set_at":"2026-07-21T00:30:00Z","reason":"all_blocked","skip_lock_until":"2026-07-21T04:00:00.222Z"}
2


The file /workspace/agent/autopilot-skip-lock.json has been updated successfully. (file state is current in your context — no need to Read it back)


Prompt: Portfolio Autopilot reset-wake: 7-day quota window has reset. Check quota and run one autopilot cycle.

node --input-type=module -e "
const r = await fetch('http://localhost:4000/api/quota-check');
const d = await r.json();
console.log(JSON.stringify({ wakeAgent: (d.burnable_pct ?? 0) >= 10, data: d }));
" 2>/dev/null || echo '{"wakeAgent":true,"data":{"reason":"quota-check-unavailable"}}'


Task scheduled (id: task-1784606740673-y5glmc, runs at: 2026-07-25T20:59:59.000Z)


Now let me clear the running lock and send the slack-infrastructure notification.


rm /workspace/agent/autopilot-running-lock.json && echo "lock cleared"

Clear autopilot running lock


lock cleared


<message to="slack-infrastructure">
**Autopilot cycle — 2026-07-21 04:05Z** (high tier, 58.9% burnable)

All P1/P2/P3 projects blocked — no autonomous work available:
- **StageHand** — awaiting 5 toolchain answers from James
- **nanoclaw** — awaiting Studio deploy (push() fix d4ef752 ready)
- **AgenticLever** — awaiting goal confirm (37/37 tests passing post-cycle)
- **RoadSense** — awaiting 5 launch questions
- **qip-qien** — awaiting merge sign-off (SEV-1 fix ee84254)
- **congressional-trading** — awaiting threshold decision (precision: 58.3% all-time, monitoring live)
- **TradingBot25** — review-required + goal blocked

Skip-lock set until 10:00Z. Reset-wake scheduled for 2026-07-25T20:59:59Z (7d window).
</message>


<context timezone="America/Chicago" />
<task from="telegram-mg-17796" time="Jul 20, 2026, 8:00 AM">Script output:
{
  "updatedRepos": [
    {
      "name": "anthropics/skills",
      "updated": "2026-07-21T07:58:33Z",
      "desc": "Public repository for Agent Skills",
      "url": "https://github.com/anthropics/skills"
    },
    {
      "name": "anthropics/k12-teacher-skills",
      "updated": "2026-07-21T07:58:10Z",
      "desc": "Skills and eval rubrics for K-12 teachers, co-developed with Learning Commons",
      "url": "https://github.com/anthropics/k12-teacher-skills"
    },
    {
      "name": "anthropics/anthropic-cli",
      "updated": "2026-07-21T07:58:06Z",
      "desc": "The CLI for the Claude API",
      "url": "https://github.com/anthropics/anthropic-cli"
    },
    {
      "name": "anthropics/claude-agent-sdk-python",
      "updated": "2026-07-21T07:55:05Z",
      "desc": null,
      "url": "https://github.com/anthropics/claude-agent-sdk-python"
    },
    {
      "name": "anthropics/code-migration-kit-with-claude-code",
      "updated": "2026-07-21T07:52:12Z",
      "desc": "Prompts, templates, and scripts for running large-scale language migrations with Claude Code",
      "url": "https://github.com/anthropics/code-migration-kit-with-claude-code"
    },
    {
      "name": "anthropics/knowledge-work-plugins",
      "updated": "2026-07-21T07:51:08Z",
      "desc": "Open source repository of plugins primarily intended for knowledge workers to use in Claude Cowork",
      "url": "https://github.com/anthropics/knowledge-work-plugins"
    },
    {
      "name": "anthropics/claude-code",
      "updated": "2026-07-21T07:50:20Z",
      "desc": "Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.",
      "url": "https://github.com/anthropics/claude-code"
    },
    {
      "name": "anthropics/claude-cookbooks",
      "updated": "2026-07-21T07:49:42Z",
      "desc": "A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.",
      "url": "https://github.com/anthropics/claude-cookbooks"
    },
    {
      "name": "anthropics/financial-services",
      "updated": "2026-07-21T07:49:13Z",
      "desc": null,
      "url": "https://github.com/anthropics/financial-services"
    },
    {
      "name": "anthropics/anthropic-sdk-python",
      "updated": "2026-07-21T07:46:39Z",
      "desc": null,
      "url": "https://github.com/anthropics/anthropic-sdk-python"
    },
    {
      "name": "anthropics/claude-for-legal",
      "updated": "2026-07-21T07:46:08Z",
      "desc": "A suite of plugins for legal workflows",
      "url": "https://github.com/anthropics/claude-for-legal"
    },
    {
      "name": "anthropics/life-sciences",
      "updated": "2026-07-21T07:45:46Z",
      "desc": "Repo for the Claude Code Marketplace to use with the Claude for Life Sciences Launch. This will continue to host the marketplace.json long-term, but not the actual MCP servers.",
      "url": "https://github.com/anthropics/life-sciences"
    },
    {
      "name": "anthropics/claude-code-action",
      "updated": "2026-07-21T07:36:03Z",
      "desc": null,
      "url": "https://github.com/anthropics/claude-code-action"
    },
    {
      "name": "anthropics/prompt-eng-interactive-tutorial",
      "updated": "2026-07-21T07:28:20Z",
      "desc": "Anthropic's Interactive Prompt Engineering Tutorial",
      "url": "https://github.com/anthropics/prompt-eng-interactive-tutorial"
    },
    {
      "name": "anthropics/claude-code-security-review",
      "updated": "2026-07-21T07:18:36Z",
      "desc": "An AI-powered security review GitHub Action using Claude to analyze code changes for security vulnerabilities.",
      "url": "https://github.com/anthropics/claude-code-security-review"
    },
    {
      "name": "anthropics/claude-plugins-official",
      "updated": "2026-07-21T07:18:08Z",
      "desc": "Official, Anthropic-managed directory of high quality Claude Code Plugins.",
      "url": "https://github.com/anthropics/claude-plugins-official"
    },
    {
      "name": "anthropics/anthropic-sdk-php",
      "updated": "2026-07-21T07:15:28Z",
      "desc": "Access to Anthropic's safety-first language model APIs in PHP",
      "url": "https://github.com/anthropics/anthropic-sdk-php"
    },
    {
      "name": "anthropics/original_performance_takehome",
      "updated": "2026-07-21T07:05:14Z",
      "desc": "Anthropic's original performance take-home, now open for you to try!",
      "url": "https://github.com/anthropics/original_performance_takehome"
    },
    {
      "name": "anthropics/cwc-workshops",
      "updated": "2026-07-21T07:04:16Z",
      "desc": null,
      "url": "https://github.com/anthropics/cwc-workshops"
    },
    {
      "name": "anthropics/claude-plugins-community",
      "updated": "2026-07-21T07:02:58Z",
      "desc": "Community plugin marketplace for Claude Cowork and Claude Code. Read-only mirror — submit plugins at clau.de/plugin-directory-submission.",
      "url": "https://github.com/anthropics/claude-plugins-community"
    },
    {
      "name": "anthropics/anthropic-sdk-typescript",
      "updated": "2026-07-21T06:56:19Z",
      "desc": "Access to Anthropic's safety-first language model APIs in TypeScript",
      "url": "https://github.com/anthropics/anthropic-sdk-typescript"
    },
    {
      "name": "anthropics/claude-quickstarts",
      "updated": "2026-07-21T06:52:16Z",
      "desc": "A collection of projects designed to help developers quickly get started with building deployable applications using the Claude API",
      "url": "https://github.com/anthropics/claude-quickstarts"
    },
    {
      "name": "anthropics/courses",
      "updated": "2026-07-21T06:52:14Z",
      "desc": "Anthropic's educational courses",
      "url": "https://github.com/anthropics/courses"
    },
    {
      "name": "anthropics/claude-tag-plugins",
      "updated": "2026-07-21T06:47:28Z",
      "desc": null,
      "url": "https://github.com/anthropics/claude-tag-plugins"
    },
    {
      "name": "anthropics/jacobian-lens",
      "updated": "2026-07-21T05:57:30Z",
      "desc": " Companion code for the global workspace interpretability paper",
      "url": "https://github.com/anthropics/jacobian-lens"
    },
    {
      "name": "anthropics/defending-code-reference-harness",
      "updated": "2026-07-21T05:56:04Z",
      "desc": "Skills for threat modeling, scanning, triage, patching, plus an autonomous scanning harness you can /customize",
      "url": "https://github.com/anthropics/defending-code-reference-harness"
    },
    {
      "name": "anthropics/anthropic-sdk-csharp",
      "updated": "2026-07-21T05:42:59Z",
      "desc": "Access to Anthropic's safety-first language model APIs in C#",
      "url": "https://github.com/anthropics/anthropic-sdk-csharp"
    },
    {
      "name": "anthropics/claude-agent-sdk-demos",
      "updated": "2026-07-21T05:39:20Z",
      "desc": "Claude Code SDK Demos",
      "url": "https://github.com/anthropics/claude-agent-sdk-demos"
    },
    {
      "name": "anthropics/PySvelte",
      "updated": "2026-07-21T05:11:29Z",
      "desc": "A library for bridging Python and HTML/Javascript (via Svelte) for creating interactive visualizations",
      "url": "https://github.com/anthropics/PySvelte"
    },
    {
      "name": "anthropics/claude-desktop-buddy",
      "updated": "2026-07-21T05:07:44Z",
      "desc": "Reference and an example for the Bluetooth API for makers in Claude Cowork & Claude Code Desktop",
      "url": "https://github.com/anthropics/claude-desktop-buddy"
    }
  ],
  "newSkillCommits": []
}

Instructions:
Check for new or updated Anthropic GitHub repos and ingest anything relevant into the second brain wiki at /workspace/extra/second-brain/.

The script has provided `data` with two fields:
- `updatedRepos`: repos in the anthropics org updated since last check
- `newSkillCommits`: new commits to anthropics/skills

For each item in updatedRepos and newSkillCommits:
1. Evaluate relevance — prioritize: skills, plugins, Claude Code updates, agent SDKs, new tools. Skip: internal tooling, Rust/infra libs (buffa, connect-rust), coursework unless it's about agents.
2. For relevant repos: fetch the README, extract what the tool/skill does, who it's for, and any notable features
3. Create or update wiki pages in /workspace/extra/second-brain/wiki/tools/ or a new wiki/repos/ folder as appropriate
4. Update wiki/index.md and wiki/log.md
5. Message James (telegram-mg-17796) with a concise summary of what was new and what was ingested. If nothing relevant, send a brief "checked GitHub, nothing new worth ingesting" message.</task>


I have a GitHub monitoring task. Let me evaluate the repos:

High relevance (should ingest):
1. `anthropics/skills` - "Public repository for Agent Skills" - directly relevant
2. `anthropics/knowledge-work-plugins` - "Open source repository of plugins primarily intended for knowledge workers to use in Claude Cowork"
3. `anthropics/claude-plugins-official` - "Official, Anthropic-managed directory of high quality Claude Code Plugins"
4. `anthropics/claude-plugins-community` - "Community plugin marketplace for Claude Cowork and Claude Code"
5. `anthropics/claude-agent-sdk-python` - Agent SDK, directly relevant
6. `anthropics/claude-agent-sdk-demos` - SDK demos showing practical implementations
7. `anthropics/code-migration-kit-with-claude-code` - Templates and scripts for large-scale language migrations
8. `anthropics/defending-code-reference-harness` - Security-focused skills for threat modeling and autonomous scanning
9. `anthropics/anthropic-cli` - The CLI for the Claude API
10. `anthropics/claude-code-security-review` - AI-powered security review tool

Looking at the rest of the repos, some like the financial services and legal plugins have limited relevance to my current focus, though the jacobian-lens research on interpretability is interesting. The desktop buddy reference for the Bluetooth API and the Claude workshops could be useful depending on what I'm building, but I should verify what the tag plugins repo actually contains.

Now I'm narrowing down to the highest-value repositories and planning to fetch their READMEs in parallel to understand what each one offers—the agent skills, knowledge work plugins, official plugins directory, agent SDK, code migration kit, security reference, CLI tool, and Bluetooth API reference all seem most promising for understanding Claude's capabilities and integration options.


On it — evaluating 30 updated Anthropic repos, fetching READMEs on the relevant ones now.


Message sent to telegram-mg-17796 (id: 3005)


Agent

Fetch READMEs from top-priority Anthropic repos

Prompt:
Fetch the README content from each of these GitHub repos. For each, use WebFetch on the raw README URL. Return the repo name and first 200 lines of its README content.

Repos to fetch:
1. https://raw.githubusercontent.com/anthropics/skills/main/README.md
2. https://raw.githubusercontent.com/anthropics/knowledge-work-plugins/main/README.md
3. https://raw.githubusercontent.com/anthropics/claude-agent-sdk-python/main/README.md
4. https://raw.githubusercontent.com/anthropics/code-migration-kit-with-claude-code/main/README.md
5. https://raw.githubusercontent.com/anthropics/defending-code-reference-harness/main/README.md
6. https://raw.githubusercontent.com/anthropics/claude-desktop-buddy/main/README.md
7. https://raw.githubusercontent.com/anthropics/claude-tag-plugins/main/README.md
8. https://raw.githubusercontent.com/anthropics/anthropic-cli/main/README.md

Return each repo's content clearly labeled. This is research only — no file writing.


Fetch READMEs from secondary Anthropic repos

Prompt:
Fetch the README content from each of these GitHub repos. For each, use WebFetch on the raw README URL. Return the repo name and first 200 lines of content.

Repos:
1. https://raw.githubusercontent.com/anthropics/claude-plugins-official/main/README.md
2. https://raw.githubusercontent.com/anthropics/claude-plugins-community/main/README.md
3. https://raw.githubusercontent.com/anthropics/claude-agent-sdk-demos/main/README.md
4. https://raw.githubusercontent.com/anthropics/claude-code-security-review/main/README.md
5. https://raw.githubusercontent.com/anthropics/jacobian-lens/main/README.md
6. https://raw.githubusercontent.com/anthropics/cwc-workshops/main/README.md

Return each clearly labeled. This is research only — no file writing.


Perfect! Here are the README contents from each repository:

---

## 1. claude-plugins-official
https://raw.githubusercontent.com/anthropics/claude-plugins-official/main/README.md

A curated plugins directory for Claude Code organized into internal and external plugin sections. Emphasizes trusting plugins before installation since Anthropic cannot verify third-party software. The directory separates Anthropic-developed plugins in `/plugins` from community contributions in `/external_plugins`. Installation uses Claude Code's plugin system with `/plugin install {plugin-name}@claude-plugins-official`. Addresses critical requirements including immutable plugin name slugs (cannot change after publishing without breaking installations) and uses `displayName` for UI labeling. Covers skill-bundle plugins, which can declare skills directly using `strict: false` mode with explicit skill array declarations.

---

## 2. claude-plugins-community
https://raw.githubusercontent.com/anthropics/claude-plugins-community/main/README.md

Functions as a read-only mirror of the community plugin marketplace for Claude Cowork and Claude Code products. Maintains a `.claude-plugin/marketplace.json` file listing available community plugins that undergoes nightly synchronization from Anthropic's internal review system. For Claude Code users, community plugins are accessed via:
```bash
claude plugin marketplace add anthropics/claude-plugins-community
claude plugin install <plugin-name>@claude-community
```
Plugin developers must submit through the official submission portal rather than direct PRs. All submissions undergo automated security review before approval.

---

## 3. claude-agent-sdk-demos
https://raw.githubusercontent.com/anthropics/claude-agent-sdk-demos/main/README.md

Contains demonstrations of the Claude Agent SDK for local development only (NOT for production or scaling). Available demos include:
- Email Agent (IMAP email assistant)
- Excel Demo (spreadsheet/Excel file handling)
- Hello World (basic SDK example)
- Hello World V2 (V2 Session API with send()/stream())
- Research Agent (multi-agent research with subagent coordination)
- AskUserQuestion Previews (branding assistant with HTML preview cards)
- Simple Chat App (React + Express chat UI with WebSocket)
- Resume Generator (web-search powered .docx resume)

Prerequisites: Bun runtime (or Node.js 18+) and Anthropic API key. Each demo has its own directory with setup instructions. Licensed under MIT.

---

## 4. claude-code-security-review
https://raw.githubusercontent.com/anthropics/claude-code-security-review/main/README.md

GitHub Action that uses Claude for AI-powered security analysis of code changes in PRs. Features include diff-aware scanning, automatic PR commenting, language-agnostic analysis, and false positive filtering. Setup requires adding a workflow file to `.github/workflows/security.yml` with appropriate permissions and Claude API key as a secret.

**Important warning:** The action is NOT hardened against prompt injection attacks and should only review trusted PRs. Detects injection attacks, authentication flaws, data exposure, cryptographic issues, input validation problems, business logic flaws, configuration weaknesses, supply chain risks, code execution vulnerabilities, and XSS variants. Includes pytest test suites and includes a `/security-review` slash command in Claude Code for integrated analysis.

---

## 5. jacobian-lens
https://raw.githubusercontent.com/anthropics/jacobian-lens/main/README.md

Reference implementation of the Jacobian lens (NOT maintained, NOT accepting contributions). Serves as companion code for research on verbalizable representations in language models. The lens interprets what internal activations incline the model to generate by transporting residual-stream vectors through layers using average input-output Jacobians, then decoding via the model's unembedding into ranked token lists.

Installation: `pip install -e .` Includes an interactive visualization tool (`walkthrough.ipynb`) that loads models, applies lenses, and renders layer-by-layer analyses. Pre-fitted lenses can be applied to text prompts; fitting uses 1000 sequences of 128 tokens from web-text corpora. Code under Apache License 2.0.

---

## 6. cwc-workshops
https://raw.githubusercontent.com/anthropics/cwc-workshops/main/README.md

Workshop materials from Anthropic's "Code with Claude" initiatives (not actively maintained, not accepting contributions). Contains ten workshops:
1. Picking the Right Model — LLM evaluation auditing across models/parameters
2. Compose Multi-Agent Systems — Refactoring complex agents using Managed Agents
3. How We Claude Code — Three-phase AI-assisted workflow documentation
4. Ship Your First Managed Agent — Streamlit incident dashboard project
5. Agent Battle — Competitive agent optimization challenge
6. Agents That Remember — Memory persistence exploration
7. Eval-Driven Agent Development — Iterative agent improvement via quantitative evaluation
8. Deal Desk — Multi-agent M&A research system
9. The Research Desk — SEC filings research with Next.js
10. Additional workshop (implied in description)

All materials distributed under Apache License 2.0.

Prompt:
Fetch the README content from each of these GitHub repos. For each, use WebFetch on the raw README URL. Return the repo name and first 200 lines of content.

Repos:
1. https://raw.githubusercontent.com/anthropics/claude-plugins-official/main/README.md
2. https://raw.githubusercontent.com/anthropics/claude-plugins-community/main/README.md
3. https://raw.githubusercontent.com/anthropics/claude-agent-sdk-demos/main/README.md
4. https://raw.githubusercontent.com/anthropics/claude-code-security-review/main/README.md
5. https://raw.githubusercontent.com/anthropics/jacobian-lens/main/README.md
6. https://raw.githubusercontent.com/anthropics/cwc-workshops/main/README.md

Return each clearly labeled. This is research only — no file writing.