1	# Claude Fable 5 and Mythos 5
2
3	**Type:** Frontier Claude models
4	**By:** Anthropic
5	**Status:** Fable 5 (GA), Mythos 5 (Preview)
6	**Source:** `anthropics/skills` — claude-api skill commit #1294 (June 9, 2026)
7
8	## What they are
9
10	**Claude Mythos 5** — The underlying frontier model. Preview availability.
11
12	**Claude Fable 5** — Same model as Mythos with Anthropic's additional safety/alignment layer applied. The production-ready version. Launch benchmark: state-of-the-art across most tested benchmarks; lead grows as tasks get longer and more complex (reported by practitioners — see [[X AI Signal Sweep - 2026-06-09]]).
13
14	## Key API differences from prior Claude models
15
16	### Always-on adaptive thinking
17	- Adaptive thinking is always on for Fable 5 — cannot be disabled.
18	- Sending `extended_thinking: { enabled: false }` returns HTTP 400.
19	- Plan for thinking token overhead in context budgets.
20
21	### New tokenizer
22	- Approximately **30% more tokens** per equivalent input compared to prior Claude models.
23	- Cost accounting must be recalibrated — don't assume prior per-task estimates carry over.
24	- Use [[AgentsView]] or independent accounting to track actual spend at launch (pricing databases may lag).
25
26	### Protected-thinking display and replay rules
27	- Extended thinking blocks have display/replay restrictions.
28	- Review Anthropic's current docs for exact rules before surfacing thinking content in products.
29
30	### Refusal stop reason + classifier fallback
31
32	Fable 5 has conservative classifiers that block requests in three specific areas:
33
34	| `stop_details.category` | Fires on |
35	|---|---|
36	| `"cyber"` | Offensive cybersecurity content — exploits, malware, attack tooling |
37	| `"bio"` | Biology / life-sciences — lab methods, molecular mechanisms |
38	| `"reasoning_extraction"` | Requests attempting to extract the model's summarized thinking |
39
40	Response shape on a block:
41	```json
42	{
43	  "stop_reason": "refusal",
44	  "stop_details": {
45	    "type": "refusal",
46	    "category": "cyber",
47	    "explanation": "..."
48	  }
49	}
50	```
51
52	Branch on **`stop_reason`**, not `content` or `stop_details`. `stop_details` can be `null` — treat that as a generic refusal.
53
54	**Server-side fallback (recommended):** Pass `fallbacks: [{"model": "claude-opus-4-8"}]` + beta header. On a classifier block, the API automatically retries with Opus 4.8. Currently supported on Claude API and Claude Platform on AWS.
55
56	```bash
57	-H "anthropic-beta: server-side-fallback-2026-06-01"
58	"fallbacks": [{ "model": "claude-opus-4-8" }]
59	```
60
61	**`stop_details.recommended_model`** — populated only when fallbacks are configured but the fallback model couldn't execute (rate-limited/overloaded). Names the model to retry directly.
62
63	**Billing change (when NOT using server-side fallback):** `stop_details.fallback_credit_token` lets you bill the fallback request as a cache read (cheaper). Requires action if you handle fallback client-side.
64
65	Source: `claude-cookbooks/fable_5_fallback_billing/guide.ipynb` (June 2026)
66
67	The skills repo also ships **SDK fallback middleware** for handling `"refusal"` stop_reason in production SDK flows.
68
69	### Data retention
70	- 30-day data-retention requirement (stricter than prior models in some configurations).
71	- Relevant for regulated use cases (HIPAA, etc.).
72
73	## Migration
74
75	Anthropic added a full "Migrating to Claude Fable 5" guide + checklist to the claude-api skill:
76
77	1. **Tokenizer recalibration** — update cost estimates, re-validate context-window budgets.
78	2. **Thinking opt-out removal** — remove any `extended_thinking: false` from request payloads.
79	3. **Refusal stop reason** — add `"refusal"` to stop_reason handlers and wire in SDK fallback middleware.
80	4. **Data retention review** — check compliance posture against the 30-day window.
81	5. **Prompt re-tuning** — Fable/Mythos has behavioral changes vs 4.x models; prompts that were tuned for 4.7 or Opus 4.8 may need adjustments (not API breaking changes, behavioral shifts).
82
83	**Mythos Preview path:** Separate migration checklist in the skill for moving from Mythos Preview → GA or Fable 5.
84
85	## Real-world performance validation (Cognition / Devin, July 2026)
86
87	Silas Alberti (Cognition SVP of Research) reports on Fable 5 powering Devin:
88	- **Overnight autonomous runs:** "I wake up, and it's been working for eight hours straight" — context coherence holds through messy production environments
89	- **Frontier Code benchmark:** ~30% on hardest internal subset vs ~10% for prior Opus (3× improvement). Internal eval using top engineers asking "Would I keep this code?" — more predictive than public benchmarks for production use.
90	- **Key behavioral improvements:** states invariants before execution; acknowledges knowledge gaps rather than fabricating; uses debugging tools correctly under noisy signals.
91
92	See [[Claude Blog - Cognition Claude Fable 5]] and [[Frontier Code Evaluation]] for full detail.
93
94	## Practical notes for James's stack
95
96	- **congressional-trading** — Recalibrate token budgets for any Fable 5 runs; the 30% tokenizer difference directly affects context window planning.
97	- **qip-qien** — Fable 5's strong performance on long, complex knowledge-work tasks (9+ hour autonomous sessions reported by Ethan Mollick) makes it the right model for the expert-draft pipeline when conviction threshold is high. Cognition's validation (honest uncertainty + no hallucinated answers) directly supports the expert-draft trust model.
98	- **Pool Monitor / Arduino** — No impact; those are Python scripts with no Claude API calls.
99	- **nanoclaw autopilot** — 8h overnight autonomous validation supports using Fable 5 for long autopilot cycles when quota allows.
100
101	## Practical usage guidance
102
103	Anthropic published a field guide (July 6, 2026) on how to work effectively with Fable:
104
105	> "Claude Fable is the first model where the quality of the work is bottlenecked by your ability to clarify its unknowns."
106
107	Fable executes instructions more literally and completely than prior models — the gap is no longer model capability, it's your specification quality. See [[Finding Your Unknowns Framework]] for a pre-flight protocol.
108
109	## Related
110
111	- [[Claude Blog - Field Guide to Claude Fable]] — Practical prompting guide: 4-quadrant unknowns model + 8 elicitation techniques
112	- [[Finding Your Unknowns Framework]] — Concept page distilling the field guide framework
113	- [[X AI Signal Sweep - 2026-06-09]] — Practitioner capability reports (Karpathy, Mollick, Shipper, Willison)
114	- [[Frontier Model Qualitative Step Change]] — Pattern for evaluating major model jumps
115	- [[AgentsView]] — Cost accounting when pricing databases lag launch
116	- [[Managed Agents]] — Opus 4.8 tool-description guidance (applicable to Fable 5 behavioral profile)
117	- [[Anthropic Skills Repo]] — Source of the migration guide and API reference
118	- [[Claude Blog - Cognition Claude Fable 5]] — Cognition's production validation: 3× Frontier Code improvement, 8h overnight autonomous runs
119	- [[Frontier Code Evaluation]] — Evaluation methodology concept from Cognition's approach
120

/workspace/extra/second-brain/wiki/tools/Claude Fable 5 and Mythos 5.md

# Claude Fable 5 and Mythos 5

**Type:** Frontier Claude models
**By:** Anthropic
**Status:** Fable 5 (GA), Mythos 5 (Preview)
**Source:** `anthropics/skills` — claude-api skill commit #1294 (June 9, 2026)

## What they are

**Claude Mythos 5** — The underlying frontier model. Preview availability.

**Claude Fable 5** — Same model as Mythos with Anthropic's additional safety/alignment layer applied. The production-ready version. Launch benchmark: state-of-the-art across most tested benchmarks; lead grows as tasks get longer and more complex (reported by practitioners — see [[X AI Signal Sweep - 2026-06-09]]).

## Key API differences from prior Claude models

### Always-on adaptive thinking
- Adaptive thinking is always on for Fable 5 — cannot be disabled.
- Sending `extended_thinking: { enabled: false }` returns HTTP 400.
- Plan for thinking token overhead in context budgets.

### New tokenizer
- Approximately **30% more tokens** per equivalent input compared to prior Claude models.
- Cost accounting must be recalibrated — don't assume prior per-task estimates carry over.
- Use [[AgentsView]] or independent accounting to track actual spend at launch (pricing databases may lag).

### Protected-thinking display and replay rules
- Extended thinking blocks have display/replay restrictions.
- Review Anthropic's current docs for exact rules before surfacing thinking content in products.

### Refusal stop reason + classifier fallback

Fable 5 has conservative classifiers that block requests in three specific areas:

| `stop_details.category` | Fires on |
|---|---|
| `"cyber"` | Offensive cybersecurity content — exploits, malware, attack tooling |
| `"bio"` | Biology / life-sciences — lab methods, molecular mechanisms |
| `"reasoning_extraction"` | Requests attempting to extract the model's summarized thinking |

Response shape on a block:
```json
{
  "stop_reason": "refusal",
  "stop_details": {
    "type": "refusal",
    "category": "cyber",
    "explanation": "..."
  }
}
```

Branch on **`stop_reason`**, not `content` or `stop_details`. `stop_details` can be `null` — treat that as a generic refusal.

**Server-side fallback (recommended):** Pass `fallbacks: [{"model": "claude-opus-4-8"}]` + beta header. On a classifier block, the API automatically retries with Opus 4.8. Currently supported on Claude API and Claude Platform on AWS.

```bash
-H "anthropic-beta: server-side-fallback-2026-06-01"
"fallbacks": [{ "model": "claude-opus-4-8" }]
```

**`stop_details.recommended_model`** — populated only when fallbacks are configured but the fallback model couldn't execute (rate-limited/overloaded). Names the model to retry directly.

**Billing change (when NOT using server-side fallback):** `stop_details.fallback_credit_token` lets you bill the fallback request as a cache read (cheaper). Requires action if you handle fallback client-side.

Source: `claude-cookbooks/fable_5_fallback_billing/guide.ipynb` (June 2026)

The skills repo also ships **SDK fallback middleware** for handling `"refusal"` stop_reason in production SDK flows.

### Data retention
- 30-day data-retention requirement (stricter than prior models in some configurations).
- Relevant for regulated use cases (HIPAA, etc.).

## Migration

Anthropic added a full "Migrating to Claude Fable 5" guide + checklist to the claude-api skill:

1. **Tokenizer recalibration** — update cost estimates, re-validate context-window budgets.
2. **Thinking opt-out removal** — remove any `extended_thinking: false` from request payloads.
3. **Refusal stop reason** — add `"refusal"` to stop_reason handlers and wire in SDK fallback middleware.
4. **Data retention review** — check compliance posture against the 30-day window.
5. **Prompt re-tuning** — Fable/Mythos has behavioral changes vs 4.x models; prompts that were tuned for 4.7 or Opus 4.8 may need adjustments (not API breaking changes, behavioral shifts).

**Mythos Preview path:** Separate migration checklist in the skill for moving from Mythos Preview → GA or Fable 5.

## Real-world performance validation (Cognition / Devin, July 2026)

Silas Alberti (Cognition SVP of Research) reports on Fable 5 powering Devin:
- **Overnight autonomous runs:** "I wake up, and it's been working for eight hours straight" — context coherence holds through messy production environments
- **Frontier Code benchmark:** ~30% on hardest internal subset vs ~10% for prior Opus (3× improvement). Internal eval using top engineers asking "Would I keep this code?" — more predictive than public benchmarks for production use.
- **Key behavioral improvements:** states invariants before execution; acknowledges knowledge gaps rather than fabricating; uses debugging tools correctly under noisy signals.

See [[Claude Blog - Cognition Claude Fable 5]] and [[Frontier Code Evaluation]] for full detail.

## Practical notes for James's stack

- **congressional-trading** — Recalibrate token budgets for any Fable 5 runs; the 30% tokenizer difference directly affects context window planning.
- **qip-qien** — Fable 5's strong performance on long, complex knowledge-work tasks (9+ hour autonomous sessions reported by Ethan Mollick) makes it the right model for the expert-draft pipeline when conviction threshold is high. Cognition's validation (honest uncertainty + no hallucinated answers) directly supports the expert-draft trust model.
- **Pool Monitor / Arduino** — No impact; those are Python scripts with no Claude API calls.
- **nanoclaw autopilot** — 8h overnight autonomous validation supports using Fable 5 for long autopilot cycles when quota allows.

## Practical usage guidance

Anthropic published a field guide (July 6, 2026) on how to work effectively with Fable:

> "Claude Fable is the first model where the quality of the work is bottlenecked by your ability to clarify its unknowns."

Fable executes instructions more literally and completely than prior models — the gap is no longer model capability, it's your specification quality. See [[Finding Your Unknowns Framework]] for a pre-flight protocol.

## Related

- [[Claude Blog - Field Guide to Claude Fable]] — Practical prompting guide: 4-quadrant unknowns model + 8 elicitation techniques
- [[Finding Your Unknowns Framework]] — Concept page distilling the field guide framework
- [[X AI Signal Sweep - 2026-06-09]] — Practitioner capability reports (Karpathy, Mollick, Shipper, Willison)
- [[Frontier Model Qualitative Step Change]] — Pattern for evaluating major model jumps
- [[AgentsView]] — Cost accounting when pricing databases lag launch
- [[Managed Agents]] — Opus 4.8 tool-description guidance (applicable to Fable 5 behavioral profile)
- [[Anthropic Skills Repo]] — Source of the migration guide and API reference
- [[Claude Blog - Cognition Claude Fable 5]] — Cognition's production validation: 3× Frontier Code improvement, 8h overnight autonomous runs
- [[Frontier Code Evaluation]] — Evaluation methodology concept from Cognition's approach


/workspace/extra/second-brain/wiki/sources/Claude Blog - Dynamic Workflows in Claude Code.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Running an AI-Native Engineering Org.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Founders Playbook.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Introducing Dynamic Workflows.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Managed Agents Self-Hosted Sandboxes.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Lessons from Building Claude Code How We Use Skills.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Best Practices for Claude Cowork.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Self-Service Data Analytics with Claude.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Claude Cowork Product Guide.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Claude for Foundation Models.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Connector Observability.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Whats New in Claude Managed Agents.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Building With Claude Managed Agents.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Field Guide to Claude Fable.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Marketing Ops Cowork Automation.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Cognition Claude Fable 5.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - AI Code Migration.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Fable 5 in Claude Cowork.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Working at the Frontier Cursor.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - CISO Guide to Agentic AI.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - Datadog Universal Machine Tool for Claude Code.md
/workspace/extra/second-brain/wiki/sources/Claude Blog - AI-Native SDLC Security.md


Now I have a clear picture. Let me proceed with writing the pages.

**All three posts are relevant:**

1. **Product Designer / Claude Design** — Nate Parrott, engineering content. Source page needed. No concept page needed (workflow tips, not a new architectural concept). The HTML effectiveness and design workflow are covered in the existing [[HTML Effectiveness Examples]] tool page. This is mostly a human-interest/workflow story.

2. **Context Engineering for Claude 5** — Thariq Shihipar. HIGHLY relevant. Source page + concept page. Key new concepts: "progressive disclosure" in context, "deferred loading" for tool schemas, "claude doctor" command, the specific practices of context engineering for Fable-era models.
3. **Claude Models Explained** — Model selection guide introducing the "Advisor Strategy" pattern of pairing a lower-cost worker model with a capable advisor. Source page needed, and the Advisor Strategy warrants its own concept page. I can either update the existing [[Claude Fable 5 and Mythos 5]] page with the selection framework or create a dedicated concept page.

I'll now create the source pages for all three posts and the concept pages for context engineering and the advisor strategy.

For the context engineering concept page, the core principles are reducing system prompts rather than expanding them, implementing five practice shifts around judgment over rules and progressive disclosure, and using deferred loading where tool schemas are stored separately and accessed only when needed through ToolSearch. I also need to update the existing pages to link these new sources and concepts, and add entries to the wiki ingest log. I'm checking what concept pages already exist to avoid duplication—there's a page on CLAUDE.md progressive disclosure and another on Claude code skills, but "Context Engineering for Claude 5" would be a distinct new concept. Now I'll start writing out all the files I need to create and update, following the naming conventions I see in the existing pages.


Now I'll write all three source pages, the concept page, and update the existing files in parallel.


Write

/workspace/extra/second-brain/wiki/sources/Claude Blog - Product Designer Claude Design.md

# Claude Blog - Product Designer Claude Design

**Author:** Nate Parrott, Product Designer at Anthropic
**Date:** July 24, 2026
**URL:** https://claude.com/blog/how-the-product-designer-who-built-claude-design-uses-it-to-explore-ideas-before-building-them
**Category:** Engineering / Product

## Summary

Nate Parrott (built Claude Design) explains how he uses the tool himself and why HTML is its core medium. The piece is part founder-story, part workflow guide.

## Key points

- **Origin**: Built Claude Design while working on Claude Code for VS Code — needed to keep pace with engineering velocity without waiting days for traditional design output.
- **HTML as the medium**: "Claude is really good with HTML" — single-file HTML artifacts are interactive, visual, and shareable, which makes them ideal for prototypes, decks, and animations.
- **Scope expanded**: Started with product mockups → now covers slide decks, landing pages, one-pagers, emails, animations.
- **Claude Opus 5 vision**: Enhanced vision capabilities now let Claude read charts, diagrams, and screenshots as input for presentation-quality output.
- **Brand integration**: Upload brand files (fonts, colors, logos) → incorporated into prompts; consistent output without manual cleanup.

## Workflow best practices from Parrott

1. Plan prompts thoroughly before starting — specify visual direction (fonts, colors, moodboard references)
2. Build reusable design systems from brand assets (upload once, reference always)
3. Request multiple options, then remix preferred elements
4. Use sketches for layouts difficult to describe verbally
5. Wireframe early — faster iteration before committing to polish
6. Reserve manual edits (resize, recolor, rearrange) for final refinements
7. Provide real project context (GitHub components, screenshots of existing screens)
8. Queue multiple prompts simultaneously for parallel exploration

## Integrations highlighted

- **GitHub**: connects to existing components and screens
- **Web search + MCP**: external information for design context
- **Voice input**: hands-free dictation and commenting

## Notable quote

> "Everything we draw should be alive by default" — Bret Victor's philosophy; HTML artifacts embody this (interactive by nature, not static images)

## Related

- [[HTML Effectiveness Examples]] — Anthropic's reference collection of single-file HTML artifacts
- [[Claude Code]] — production counterpart to Claude Design
- [[Claude Fable 5 and Mythos 5]] — Opus 5 vision improvements referenced in the post


File created successfully at: /workspace/extra/second-brain/wiki/sources/Claude Blog - Product Designer Claude Design.md (file state is current in your context — no need to Read it back)

# Claude Blog - Product Designer Claude Design

**Author:** Nate Parrott, Product Designer at Anthropic
**Date:** July 24, 2026
**URL:** https://claude.com/blog/how-the-product-designer-who-built-claude-design-uses-it-to-explore-ideas-before-building-them
**Category:** Engineering / Product

## Summary

Nate Parrott (built Claude Design) explains how he uses the tool himself and why HTML is its core medium. The piece is part founder-story, part workflow guide.

## Key points

- **Origin**: Built Claude Design while working on Claude Code for VS Code — needed to keep pace with engineering velocity without waiting days for traditional design output.
- **HTML as the medium**: "Claude is really good with HTML" — single-file HTML artifacts are interactive, visual, and shareable, which makes them ideal for prototypes, decks, and animations.
- **Scope expanded**: Started with product mockups → now covers slide decks, landing pages, one-pagers, emails, animations.
- **Claude Opus 5 vision**: Enhanced vision capabilities now let Claude read charts, diagrams, and screenshots as input for presentation-quality output.
- **Brand integration**: Upload brand files (fonts, colors, logos) → incorporated into prompts; consistent output without manual cleanup.

## Workflow best practices from Parrott

1. Plan prompts thoroughly before starting — specify visual direction (fonts, colors, moodboard references)
2. Build reusable design systems from brand assets (upload once, reference always)
3. Request multiple options, then remix preferred elements
4. Use sketches for layouts difficult to describe verbally
5. Wireframe early — faster iteration before committing to polish
6. Reserve manual edits (resize, recolor, rearrange) for final refinements
7. Provide real project context (GitHub components, screenshots of existing screens)
8. Queue multiple prompts simultaneously for parallel exploration

## Integrations highlighted

- **GitHub**: connects to existing components and screens
- **Web search + MCP**: external information for design context
- **Voice input**: hands-free dictation and commenting

## Notable quote

> "Everything we draw should be alive by default" — Bret Victor's philosophy; HTML artifacts embody this (interactive by nature, not static images)

## Related

- [[HTML Effectiveness Examples]] — Anthropic's reference collection of single-file HTML artifacts
- [[Claude Code]] — production counterpart to Claude Design
- [[Claude Fable 5 and Mythos 5]] — Opus 5 vision improvements referenced in the post


/workspace/extra/second-brain/wiki/sources/Claude Blog - Context Engineering for Claude 5.md

# Claude Blog - Context Engineering for Claude 5

**Author:** Thariq Shihipar, Member of Technical Staff, Anthropic
**Date:** July 24, 2026
**URL:** https://claude.com/blog/the-new-rules-of-context-engineering-for-claude-5-generation-models
**Categories:** Claude Code, Agents

## Summary

Anthropic removed over 80% of Claude Code's system prompt for Fable/Mythos-generation models with *no measurable loss on coding evals*. This post explains the five practice shifts behind that change — and what they mean for anyone building with Claude 5-generation models.

## The headline result

- 80%+ reduction in Claude Code system prompt length
- Zero degradation on coding evaluations
- Shift from "heavily constrained instructions" → "model judgment + progressive disclosure"

## What is context engineering?

The assembly of system prompts, CLAUDE.md files, skills, memory, and references that accompany a user query. With Fable/Mythos, this assembly matters *differently* than with prior models — more isn't better.

## Five practice shifts

### 1. Judgment over rules
- Old: rigid rules ("always do X", "never do Y")
- New: enable model judgment ("here's the goal and the tradeoffs — decide")
- Why: Fable executes instructions more literally; over-specified rules cause rigidity and edge-case failures

### 2. Tool interface design over examples
- Old: provide examples of how to use a tool
- New: design the tool interface to be self-explanatory
- Better tool descriptions > example-heavy prompts

### 3. Progressive disclosure over upfront loading
- Old: dump everything into the system prompt or CLAUDE.md
- New: surface context at the moment it's needed
- Mechanism: **deferred loading** — tool schemas stored separately, accessed via ToolSearch when the agent needs them (not loaded upfront)
- Result: smaller active context, lower noise, faster decisions

### 4. Eliminate redundant instructions
- Audit every instruction: does it appear in more than one place? Can the model infer it from context?
- Cross-context redundancy (same rule in system prompt AND CLAUDE.md AND skill) adds noise, not reliability

### 5. Automatic memory over manual CLAUDE.md documentation
- Old: engineer manually maintains CLAUDE.md to capture project state
- New: auto-memory — Claude saves relevant context automatically, at the right time, in the right scope
- Implication: CLAUDE.md evolves from a "manual wiki" to a lightweight pointer/gotchas file

## Context structure layers (current Claude Code model)

| Layer | Role | Notes |
|---|---|---|
| System Prompt | Product-specific guidance | Minimal — judgment-enabling, not rule-listing |
| CLAUDE.md | Repo-specific gotchas, lightweight docs | Not a manual wiki anymore; mostly pointers |
| Skills | Lightweight guides with progressive disclosure | Triggered on demand via ToolSearch, not loaded upfront |
| References | In-depth specs, code mockups, codebases | Accessed via @ mentions when needed |

## New tools / commands

- **`claude doctor`** — New diagnostic command. Helps users identify over-specified or poorly structured skills/CLAUDE.md files for Fable-era models. Surfaces what to trim.
- **Artifacts** — Rich visual/interactive references replacing simple markdown specs. First-class context input.
- **Dynamic workflows** — Verification rubrics that agents use to validate their own implementation quality (see [[Claude Code Dynamic Workflows]])

## Applicability to James's stack

- **CLAUDE.md files across all projects**: these are now over-specified relative to Fable's capabilities. `claude doctor` is the right first step before a CLAUDE.md audit.
- **Nanoclaw agent instructions**: CLAUDE.local.md + CLAUDE.md follow the old "rules-heavy" pattern — worth an eventual pass to convert rules to judgment-enabling guidance.
- **Skills architecture**: the progressive disclosure model described here is exactly how NanoClaw's deferred tools work (via ToolSearch). This post validates that architecture.
- **Context size anxiety**: if an agent's performance degrades, removing context is now as plausible a fix as adding it.

## Related

- [[Context Engineering for Claude 5]] — concept page distilling the 5 shifts
- [[Claude Code Skills Best Practices]] — Thariq's prior post on skill categories and progressive disclosure
- [[CLAUDE.md Progressive Disclosure]] — existing concept on CLAUDE.md structure; this post extends it
- [[Claude Fable 5 and Mythos 5]] — the model family these practices target
- [[Finding Your Unknowns Framework]] — companion practice: since Fable executes better, user clarity is now the bottleneck


File created successfully at: /workspace/extra/second-brain/wiki/sources/Claude Blog - Context Engineering for Claude 5.md (file state is current in your context — no need to Read it back)

# Claude Blog - Context Engineering for Claude 5

**Author:** Thariq Shihipar, Member of Technical Staff, Anthropic
**Date:** July 24, 2026
**URL:** https://claude.com/blog/the-new-rules-of-context-engineering-for-claude-5-generation-models
**Categories:** Claude Code, Agents

## Summary

Anthropic removed over 80% of Claude Code's system prompt for Fable/Mythos-generation models with *no measurable loss on coding evals*. This post explains the five practice shifts behind that change — and what they mean for anyone building with Claude 5-generation models.

## The headline result

- 80%+ reduction in Claude Code system prompt length
- Zero degradation on coding evaluations
- Shift from "heavily constrained instructions" → "model judgment + progressive disclosure"

## What is context engineering?

The assembly of system prompts, CLAUDE.md files, skills, memory, and references that accompany a user query. With Fable/Mythos, this assembly matters *differently* than with prior models — more isn't better.

## Five practice shifts

### 1. Judgment over rules
- Old: rigid rules ("always do X", "never do Y")
- New: enable model judgment ("here's the goal and the tradeoffs — decide")
- Why: Fable executes instructions more literally; over-specified rules cause rigidity and edge-case failures

### 2. Tool interface design over examples
- Old: provide examples of how to use a tool
- New: design the tool interface to be self-explanatory
- Better tool descriptions > example-heavy prompts

### 3. Progressive disclosure over upfront loading
- Old: dump everything into the system prompt or CLAUDE.md
- New: surface context at the moment it's needed
- Mechanism: **deferred loading** — tool schemas stored separately, accessed via ToolSearch when the agent needs them (not loaded upfront)
- Result: smaller active context, lower noise, faster decisions

### 4. Eliminate redundant instructions
- Audit every instruction: does it appear in more than one place? Can the model infer it from context?
- Cross-context redundancy (same rule in system prompt AND CLAUDE.md AND skill) adds noise, not reliability

### 5. Automatic memory over manual CLAUDE.md documentation
- Old: engineer manually maintains CLAUDE.md to capture project state
- New: auto-memory — Claude saves relevant context automatically, at the right time, in the right scope
- Implication: CLAUDE.md evolves from a "manual wiki" to a lightweight pointer/gotchas file

## Context structure layers (current Claude Code model)

| Layer | Role | Notes |
|---|---|---|
| System Prompt | Product-specific guidance | Minimal — judgment-enabling, not rule-listing |
| CLAUDE.md | Repo-specific gotchas, lightweight docs | Not a manual wiki anymore; mostly pointers |
| Skills | Lightweight guides with progressive disclosure | Triggered on demand via ToolSearch, not loaded upfront |
| References | In-depth specs, code mockups, codebases | Accessed via @ mentions when needed |

## New tools / commands

- **`claude doctor`** — New diagnostic command. Helps users identify over-specified or poorly structured skills/CLAUDE.md files for Fable-era models. Surfaces what to trim.
- **Artifacts** — Rich visual/interactive references replacing simple markdown specs. First-class context input.
- **Dynamic workflows** — Verification rubrics that agents use to validate their own implementation quality (see [[Claude Code Dynamic Workflows]])

## Applicability to James's stack

- **CLAUDE.md files across all projects**: these are now over-specified relative to Fable's capabilities. `claude doctor` is the right first step before a CLAUDE.md audit.
- **Nanoclaw agent instructions**: CLAUDE.local.md + CLAUDE.md follow the old "rules-heavy" pattern — worth an eventual pass to convert rules to judgment-enabling guidance.
- **Skills architecture**: the progressive disclosure model described here is exactly how NanoClaw's deferred tools work (via ToolSearch). This post validates that architecture.
- **Context size anxiety**: if an agent's performance degrades, removing context is now as plausible a fix as adding it.

## Related

- [[Context Engineering for Claude 5]] — concept page distilling the 5 shifts
- [[Claude Code Skills Best Practices]] — Thariq's prior post on skill categories and progressive disclosure
- [[CLAUDE.md Progressive Disclosure]] — existing concept on CLAUDE.md structure; this post extends it
- [[Claude Fable 5 and Mythos 5]] — the model family these practices target
- [[Finding Your Unknowns Framework]] — companion practice: since Fable executes better, user clarity is now the bottleneck


/workspace/extra/second-brain/wiki/sources/Claude Blog - Claude Models Explained.md

# Claude Blog - Claude Models Explained

**Author:** Anthropic (no specific author listed)
**Date:** July 24, 2026
**URL:** https://claude.com/blog/claude-models-explained-choosing-the-best-model-for-your-use-case
**Categories:** Enterprise AI, Agents, Claude Code

## Summary

Anthropic's official guide to the current model family and how to choose. Introduces the "Advisor Strategy" for cost-effective quality optimization and formalizes the model-class naming (Fable, Mythos, Opus, Sonnet, Haiku).

## Model family

| Model class | Purpose | Key characteristics |
|---|---|---|
| **Mythos / Fable** | Most capable | "Frontier capabilities across domains"; coding, agents, novel problem-solving |
| **Opus** | Reasoning-intensive enterprise | Powerful general performer; faster/cheaper alternative to Fable when quality bar met |
| **Sonnet** | Everyday / general purpose | Balanced performance/cost/speed; good for high-volume sub-agents |
| **Haiku** | High-frequency workloads | Lowest cost and fastest model class |

## Selection framework — 4 questions

1. **How difficult is the task?** (novel/ambiguous vs. well-specified)
2. **What latency requirements exist?** (user-facing interactive vs. batch)
3. **What access constraints apply?** (plan tier, regional availability)
4. **What are the unit economics?** (per-task cost × volume)

## Starting guidance

> Start with the most intelligent generally available model, then adjust effort levels for performance/cost optimization — don't start with cheaper models.

More capable models often prove *more* economical: "require fewer turns and less thinking time to get most tasks right." Fewer retries + fewer error-recovery loops offset the per-token cost premium.

## The Advisor Strategy

Pair a lower-cost **worker model** with a capable **advisor model** for cost-effective quality:

> "Sonnet 5 with Fable 5 advisor achieves within 10% of Fable 5's score at 63% of the cost."

Pattern: Worker handles execution → Advisor reviews outputs and provides correction signals → Worker re-executes with feedback.

Relevant whenever:
- You need Fable-level quality on a workload that's too expensive to run entirely on Fable
- You want a quality gate without full Fable cost per task
- Sub-agents need smart oversight without smart execution throughout

## Use-case routing

| Use case | Recommended model |
|---|---|
| High-frequency customer-facing | Sonnet |
| Complex reasoning / novel problems | Fable or Opus |
| High-volume production (eval-confirmed) | Haiku or Sonnet |
| Latency-sensitive | Haiku or Sonnet |
| Sub-agent in multi-agent pipeline | Sonnet (worker) + Fable (advisor gate) |

## Evaluation guidance

Build custom evals from **production workloads**, not public benchmarks — frontier models saturate standard test performance. The eval question is "would a domain expert keep this output?" not a benchmark score.

## Related

- [[Claude Fable 5 and Mythos 5]] — deep technical reference (API differences, migration checklist, real-world perf)
- [[Frontier Code Evaluation]] — "would I keep this code?" eval methodology
- [[Eval-Routed Local-First Code Delegation]] — routing by eval verdict, not guessing
- [[Finding Your Unknowns Framework]] — route by problem ambiguity (Fable for underspecified; Sonnet for clear-spec)
- [[Claude Blog - Working at the Frontier Cursor]] — global vs local reasoning as routing signal


File created successfully at: /workspace/extra/second-brain/wiki/sources/Claude Blog - Claude Models Explained.md (file state is current in your context — no need to Read it back)

# Claude Blog - Claude Models Explained

**Author:** Anthropic (no specific author listed)
**Date:** July 24, 2026
**URL:** https://claude.com/blog/claude-models-explained-choosing-the-best-model-for-your-use-case
**Categories:** Enterprise AI, Agents, Claude Code

## Summary

Anthropic's official guide to the current model family and how to choose. Introduces the "Advisor Strategy" for cost-effective quality optimization and formalizes the model-class naming (Fable, Mythos, Opus, Sonnet, Haiku).

## Model family

| Model class | Purpose | Key characteristics |
|---|---|---|
| **Mythos / Fable** | Most capable | "Frontier capabilities across domains"; coding, agents, novel problem-solving |
| **Opus** | Reasoning-intensive enterprise | Powerful general performer; faster/cheaper alternative to Fable when quality bar met |
| **Sonnet** | Everyday / general purpose | Balanced performance/cost/speed; good for high-volume sub-agents |
| **Haiku** | High-frequency workloads | Lowest cost and fastest model class |

## Selection framework — 4 questions

1. **How difficult is the task?** (novel/ambiguous vs. well-specified)
2. **What latency requirements exist?** (user-facing interactive vs. batch)
3. **What access constraints apply?** (plan tier, regional availability)
4. **What are the unit economics?** (per-task cost × volume)

## Starting guidance

> Start with the most intelligent generally available model, then adjust effort levels for performance/cost optimization — don't start with cheaper models.

More capable models often prove *more* economical: "require fewer turns and less thinking time to get most tasks right." Fewer retries + fewer error-recovery loops offset the per-token cost premium.

## The Advisor Strategy

Pair a lower-cost **worker model** with a capable **advisor model** for cost-effective quality:

> "Sonnet 5 with Fable 5 advisor achieves within 10% of Fable 5's score at 63% of the cost."

Pattern: Worker handles execution → Advisor reviews outputs and provides correction signals → Worker re-executes with feedback.

Relevant whenever:
- You need Fable-level quality on a workload that's too expensive to run entirely on Fable
- You want a quality gate without full Fable cost per task
- Sub-agents need smart oversight without smart execution throughout

## Use-case routing

| Use case | Recommended model |
|---|---|
| High-frequency customer-facing | Sonnet |
| Complex reasoning / novel problems | Fable or Opus |
| High-volume production (eval-confirmed) | Haiku or Sonnet |
| Latency-sensitive | Haiku or Sonnet |
| Sub-agent in multi-agent pipeline | Sonnet (worker) + Fable (advisor gate) |

## Evaluation guidance

Build custom evals from **production workloads**, not public benchmarks — frontier models saturate standard test performance. The eval question is "would a domain expert keep this output?" not a benchmark score.

## Related

- [[Claude Fable 5 and Mythos 5]] — deep technical reference (API differences, migration checklist, real-world perf)
- [[Frontier Code Evaluation]] — "would I keep this code?" eval methodology
- [[Eval-Routed Local-First Code Delegation]] — routing by eval verdict, not guessing
- [[Finding Your Unknowns Framework]] — route by problem ambiguity (Fable for underspecified; Sonnet for clear-spec)
- [[Claude Blog - Working at the Frontier Cursor]] — global vs local reasoning as routing signal


/workspace/extra/second-brain/wiki/concepts/Context Engineering for Claude 5.md

# Context Engineering for Claude 5

**Source:** [[Claude Blog - Context Engineering for Claude 5]] (Thariq Shihipar, Anthropic, July 24, 2026)

## The principle

With Fable/Mythos-generation models, **more context is not better**. Anthropic removed 80%+ of Claude Code's system prompt with no measurable quality loss. The craft is now: what to *not* include and *when* to surface what you do include.

## Five shifts that define the new practice

### 1. Judgment > rules
Don't list what the model should do — describe the goal and the tradeoffs. Fable executes instructions more literally than prior models; rigid rules cause brittle edge-case failures. Let the model decide within a well-described outcome space.

### 2. Tool interface > examples
A well-designed tool description makes examples unnecessary. Invest in the interface, not the usage tutorial.

### 3. Progressive disclosure > upfront loading
Surface context at the moment it's needed:
- **Deferred tools**: store tool schemas separately; make them searchable (ToolSearch pattern) rather than pre-loaded in every context
- Load skills only when triggered, not as ambient context
- Result: active context is smaller, signal-to-noise is higher

### 4. Eliminate redundancy
If the same instruction appears in system prompt, CLAUDE.md, and a skill, you have one instruction and three noise sources. Deduplicate; trust the model to carry context once it's established.

### 5. Auto-memory > manual documentation
CLAUDE.md should no longer serve as a manually-maintained project wiki. Let auto-memory save relevant context at the right time and scope. CLAUDE.md becomes a lightweight gotchas + pointers file.

## Context layers (Claude Code model)

```
System Prompt (minimal, judgment-enabling)
  └── CLAUDE.md (repo gotchas, not a wiki)
       └── Skills (triggered on demand via ToolSearch)
            └── References (@ mentioned when needed: specs, codebases, artifacts)
```

## Diagnostic tool

**`claude doctor`** — new Claude Code command that identifies over-specified or poorly structured skills/CLAUDE.md files for Fable-era models.

## When this applies

Any agent or workflow built on a Fable/Mythos-generation model. This includes:
- Claude Code project setups (CLAUDE.md + skills)
- NanoClaw agents (system prompts, CLAUDE.local.md, tool loading patterns)
- Managed Agent deployments
- Any system prompt written for Claude 4.x that hasn't been audited for 5.x

## What it does NOT apply to

Older Claude (4.x) models still benefit from more explicit rules and examples. The shift is generation-specific.

## Related

- [[CLAUDE.md Progressive Disclosure]] — file-structure analog; this is the model-capability analog
- [[Claude Code Skills Best Practices]] — Thariq's prior work on skill structure
- [[Finding Your Unknowns Framework]] — companion: output quality is now bottlenecked by user clarity, not model capability
- [[Claude Blog - Context Engineering for Claude 5]] — source post with full detail


File created successfully at: /workspace/extra/second-brain/wiki/concepts/Context Engineering for Claude 5.md (file state is current in your context — no need to Read it back)

# Context Engineering for Claude 5

**Source:** [[Claude Blog - Context Engineering for Claude 5]] (Thariq Shihipar, Anthropic, July 24, 2026)

## The principle

With Fable/Mythos-generation models, **more context is not better**. Anthropic removed 80%+ of Claude Code's system prompt with no measurable quality loss. The craft is now: what to *not* include and *when* to surface what you do include.

## Five shifts that define the new practice

### 1. Judgment > rules
Don't list what the model should do — describe the goal and the tradeoffs. Fable executes instructions more literally than prior models; rigid rules cause brittle edge-case failures. Let the model decide within a well-described outcome space.

### 2. Tool interface > examples
A well-designed tool description makes examples unnecessary. Invest in the interface, not the usage tutorial.

### 3. Progressive disclosure > upfront loading
Surface context at the moment it's needed:
- **Deferred tools**: store tool schemas separately; make them searchable (ToolSearch pattern) rather than pre-loaded in every context
- Load skills only when triggered, not as ambient context
- Result: active context is smaller, signal-to-noise is higher

### 4. Eliminate redundancy
If the same instruction appears in system prompt, CLAUDE.md, and a skill, you have one instruction and three noise sources. Deduplicate; trust the model to carry context once it's established.

### 5. Auto-memory > manual documentation
CLAUDE.md should no longer serve as a manually-maintained project wiki. Let auto-memory save relevant context at the right time and scope. CLAUDE.md becomes a lightweight gotchas + pointers file.

## Context layers (Claude Code model)

```
System Prompt (minimal, judgment-enabling)
  └── CLAUDE.md (repo gotchas, not a wiki)
       └── Skills (triggered on demand via ToolSearch)
            └── References (@ mentioned when needed: specs, codebases, artifacts)
```

## Diagnostic tool

**`claude doctor`** — new Claude Code command that identifies over-specified or poorly structured skills/CLAUDE.md files for Fable-era models.

## When this applies

Any agent or workflow built on a Fable/Mythos-generation model. This includes:
- Claude Code project setups (CLAUDE.md + skills)
- NanoClaw agents (system prompts, CLAUDE.local.md, tool loading patterns)
- Managed Agent deployments
- Any system prompt written for Claude 4.x that hasn't been audited for 5.x

## What it does NOT apply to

Older Claude (4.x) models still benefit from more explicit rules and examples. The shift is generation-specific.

## Related

- [[CLAUDE.md Progressive Disclosure]] — file-structure analog; this is the model-capability analog
- [[Claude Code Skills Best Practices]] — Thariq's prior work on skill structure
- [[Finding Your Unknowns Framework]] — companion: output quality is now bottlenecked by user clarity, not model capability
- [[Claude Blog - Context Engineering for Claude 5]] — source post with full detail


Review eligible projects and execute autopilot cycle


Now I need to:
1. Update `Claude Fable 5 and Mythos 5.md` with the Advisor Strategy
2. Update `Home.md` — add entries to Sources and Concepts sections
3. Update `Wiki Ingest Log.md` with a dated entry

Let me do these now.

For the Fable 5 page, I'll add a section about the Advisor Strategy and model selection framework.

For Home.md, I need to add:
- To Sources section: the three new source pages
- To Concepts section: the context engineering concept

For the Ingest Log, I need to add a new dated entry at the top.

Let me do all of these concurrently.


Now update the Fable 5 tool page, Home.md, and the Ingest Log.


Edit

/workspace/extra/second-brain/wiki/tools/Claude Fable 5 and Mythos 5.md

## Related

- [[Claude Blog - Field Guide to Claude Fable]] — Practical prompting guide: 4-quadrant unknowns model + 8 elicitation techniques

## The Advisor Strategy (July 2026)

Pair a lower-cost worker model with a capable advisor model for cost-effective quality:

> "Sonnet 5 with Fable 5 advisor achieves within 10% of Fable 5's score at 63% of the cost."

Worker handles execution → Advisor reviews outputs → Worker re-executes with correction signals. Use when you need Fable-level quality gates without Fable cost per execution step.

See [[Claude Blog - Claude Models Explained]] for the full model-selection framework.

## Related

- [[Claude Blog - Field Guide to Claude Fable]] — Practical prompting guide: 4-quadrant unknowns model + 8 elicitation techniques


The file /workspace/extra/second-brain/wiki/tools/Claude Fable 5 and Mythos 5.md has been updated successfully. (file state is current in your context — no need to Read it back)

## The Advisor Strategy (July 2026)

Pair a lower-cost worker model with a capable advisor model for cost-effective quality:

> "Sonnet 5 with Fable 5 advisor achieves within 10% of Fable 5's score at 63% of the cost."

Worker handles execution → Advisor reviews outputs → Worker re-executes with correction signals. Use when you need Fable-level quality gates without Fable cost per execution step.

See [[Claude Blog - Claude Models Explained]] for the full model-selection framework.

## Related

- [[Claude Blog - Field Guide to Claude Fable]] — Practical prompting guide: 4-quadrant unknowns model + 8 elicitation techniques

# Claude Fable 5 and Mythos 5

**Type:** Frontier Claude models
**By:** Anthropic
**Status:** Fable 5 (GA), Mythos 5 (Preview)
**Source:** `anthropics/skills` — claude-api skill commit #1294 (June 9, 2026)

## What they are

**Claude Mythos 5** — The underlying frontier model. Preview availability.

**Claude Fable 5** — Same model as Mythos with Anthropic's additional safety/alignment layer applied. The production-ready version. Launch benchmark: state-of-the-art across most tested benchmarks; lead grows as tasks get longer and more complex (reported by practitioners — see [[X AI Signal Sweep - 2026-06-09]]).

## Key API differences from prior Claude models

### Always-on adaptive thinking
- Adaptive thinking is always on for Fable 5 — cannot be disabled.
- Sending `extended_thinking: { enabled: false }` returns HTTP 400.
- Plan for thinking token overhead in context budgets.

### New tokenizer
- Approximately **30% more tokens** per equivalent input compared to prior Claude models.
- Cost accounting must be recalibrated — don't assume prior per-task estimates carry over.
- Use [[AgentsView]] or independent accounting to track actual spend at launch (pricing databases may lag).

### Protected-thinking display and replay rules
- Extended thinking blocks have display/replay restrictions.
- Review Anthropic's current docs for exact rules before surfacing thinking content in products.

### Refusal stop reason + classifier fallback

Fable 5 has conservative classifiers that block requests in three specific areas:

| `stop_details.category` | Fires on |
|---|---|
| `"cyber"` | Offensive cybersecurity content — exploits, malware, attack tooling |
| `"bio"` | Biology / life-sciences — lab methods, molecular mechanisms |
| `"reasoning_extraction"` | Requests attempting to extract the model's summarized thinking |

Response shape on a block:
```json
{
  "stop_reason": "refusal",
  "stop_details": {
    "type": "refusal",
    "category": "cyber",
    "explanation": "..."
  }
}
```

Branch on **`stop_reason`**, not `content` or `stop_details`. `stop_details` can be `null` — treat that as a generic refusal.

**Server-side fallback (recommended):** Pass `fallbacks: [{"model": "claude-opus-4-8"}]` + beta header. On a classifier block, the API automatically retries with Opus 4.8. Currently supported on Claude API and Claude Platform on AWS.

```bash
-H "anthropic-beta: server-side-fallback-2026-06-01"
"fallbacks": [{ "model": "claude-opus-4-8" }]
```

**`stop_details.recommended_model`** — populated only when fallbacks are configured but the fallback model couldn't execute (rate-limited/overloaded). Names the model to retry directly.

**Billing change (when NOT using server-side fallback):** `stop_details.fallback_credit_token` lets you bill the fallback request as a cache read (cheaper). Requires action if you handle fallback client-side.

Source: `claude-cookbooks/fable_5_fallback_billing/guide.ipynb` (June 2026)

The skills repo also ships **SDK fallback middleware** for handling `"refusal"` stop_reason in production SDK flows.

### Data retention
- 30-day data-retention requirement (stricter than prior models in some configurations).
- Relevant for regulated use cases (HIPAA, etc.).

## Migration

Anthropic added a full "Migrating to Claude Fable 5" guide + checklist to the claude-api skill:

1. **Tokenizer recalibration** — update cost estimates, re-validate context-window budgets.
2. **Thinking opt-out removal** — remove any `extended_thinking: false` from request payloads.
3. **Refusal stop reason** — add `"refusal"` to stop_reason handlers and wire in SDK fallback middleware.
4. **Data retention review** — check compliance posture against the 30-day window.
5. **Prompt re-tuning** — Fable/Mythos has behavioral changes vs 4.x models; prompts that were tuned for 4.7 or Opus 4.8 may need adjustments (not API breaking changes, behavioral shifts).

**Mythos Preview path:** Separate migration checklist in the skill for moving from Mythos Preview → GA or Fable 5.

## Real-world performance validation (Cognition / Devin, July 2026)

Silas Alberti (Cognition SVP of Research) reports on Fable 5 powering Devin:
- **Overnight autonomous runs:** "I wake up, and it's been working for eight hours straight" — context coherence holds through messy production environments
- **Frontier Code benchmark:** ~30% on hardest internal subset vs ~10% for prior Opus (3× improvement). Internal eval using top engineers asking "Would I keep this code?" — more predictive than public benchmarks for production use.
- **Key behavioral improvements:** states invariants before execution; acknowledges knowledge gaps rather than fabricating; uses debugging tools correctly under noisy signals.

See [[Claude Blog - Cognition Claude Fable 5]] and [[Frontier Code Evaluation]] for full detail.

## Practical notes for James's stack

- **congressional-trading** — Recalibrate token budgets for any Fable 5 runs; the 30% tokenizer difference directly affects context window planning.
- **qip-qien** — Fable 5's strong performance on long, complex knowledge-work tasks (9+ hour autonomous sessions reported by Ethan Mollick) makes it the right model for the expert-draft pipeline when conviction threshold is high. Cognition's validation (honest uncertainty + no hallucinated answers) directly supports the expert-draft trust model.
- **Pool Monitor / Arduino** — No impact; those are Python scripts with no Claude API calls.
- **nanoclaw autopilot** — 8h overnight autonomous validation supports using Fable 5 for long autopilot cycles when quota allows.

## Practical usage guidance

Anthropic published a field guide (July 6, 2026) on how to work effectively with Fable:

> "Claude Fable is the first model where the quality of the work is bottlenecked by your ability to clarify its unknowns."

Fable executes instructions more literally and completely than prior models — the gap is no longer model capability, it's your specification quality. See [[Finding Your Unknowns Framework]] for a pre-flight protocol.

## Related

- [[Claude Blog - Field Guide to Claude Fable]] — Practical prompting guide: 4-quadrant unknowns model + 8 elicitation techniques
- [[Finding Your Unknowns Framework]] — Concept page distilling the field guide framework
- [[X AI Signal Sweep - 2026-06-09]] — Practitioner capability reports (Karpathy, Mollick, Shipper, Willison)
- [[Frontier Model Qualitative Step Change]] — Pattern for evaluating major model jumps
- [[AgentsView]] — Cost accounting when pricing databases lag launch
- [[Managed Agents]] — Opus 4.8 tool-description guidance (applicable to Fable 5 behavioral profile)
- [[Anthropic Skills Repo]] — Source of the migration guide and API reference
- [[Claude Blog - Cognition Claude Fable 5]] — Cognition's production validation: 3× Frontier Code improvement, 8h overnight autonomous runs
- [[Frontier Code Evaluation]] — Evaluation methodology concept from Cognition's approach

+Pair a lower-cost worker model with a capable advisor model for cost-effective quality:

+> "Sonnet 5 with Fable 5 advisor achieves within 10% of Fable 5's score at 63% of the cost."

+Worker handles execution → Advisor reviews outputs → Worker re-executes with correction signals. Use when you need Fable-level quality gates without Fable cost per execution step.

+See [[Claude Blog - Claude Models Explained]] for the full model-selection framework.


## Concepts & Reference Docs
- [[Test Isolation for Runtime Activity Logs]]

## Concepts & Reference Docs
- [[Context Engineering for Claude 5]] — 5 practice shifts for Fable/Mythos-era models: judgment > rules, progressive disclosure, deferred tool loading, eliminate redundancy, auto-memory. 80%+ system prompt reduction with no eval loss.
- [[Test Isolation for Runtime Activity Logs]]


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

## Concepts & Reference Docs
- [[Test Isolation for Runtime Activity Logs]]

## Concepts & Reference Docs
- [[Context Engineering for Claude 5]] — 5 practice shifts for Fable/Mythos-era models: judgment > rules, progressive disclosure, deferred tool loading, eliminate redundancy, auto-memory. 80%+ system prompt reduction with no eval loss.
- [[Test Isolation for Runtime Activity Logs]]

- [[Claude CwC - The Prompting Playbook]] — Margot van Laar (Anthropic), CwC London 2026. Eval-first, XML structure, delete legacy patches, tools > instructions, Generator→Evaluator→Repairer loop.

+- [[Context Engineering for Claude 5]] — 5 practice shifts for Fable/Mythos-era models: judgment > rules, progressive disclosure, deferred tool loading, eliminate redundancy, auto-memory. 80%+ system prompt reduction with no eval loss.

- [[Test Isolation for Runtime Activity Logs]] — Prevent orchestration tests from polluting live alert/error/state feeds by redirecting module-level runtime paths to `tmp_path`, then prove production logs are unchanged by the suite.

- [[LaunchAgent Quarantine and Tailscale Recovery]] — Recover a reboot-stalled local site by clearing the LaunchAgent quarantine and re-bootstrapping it, then separately reconnecting Tailscale and verifying both local and public routes.

- [[Orthogonal Visual Channels on Map Lines]] — Don't recolor a line to encode a boolean when color already carries a scalar; add a near-black dotted overlay (Mapbox: short dash + round cap, dasharray units are line-widths so zoom-scaling is free). Plus a puppeteer pattern for E2E-verifying map layers via the app's own custom events.


## Sources
- [[AI Daily Brief - The 4 AI Team Members Execs Should Hire Right Now]]

## Sources
- [[Claude Blog - Context Engineering for Claude 5]] — July 24, 2026. Thariq Shihipar. 80%+ system prompt reduction, zero eval loss. Five practice shifts for Fable-era context: judgment > rules, tool interface design, progressive disclosure, eliminate redundancy, auto-memory.
- [[Claude Blog - Claude Models Explained]] — July 24, 2026. Model family guide: Fable/Mythos/Opus/Sonnet/Haiku. Advisor Strategy (Sonnet 5 + Fable 5 advisor = 90% quality at 63% cost). Four-question selection framework. Custom evals over benchmarks.
- [[Claude Blog - Product Designer Claude Design]] — July 24, 2026. Nate Parrott (Anthropic). HTML as the prototyping medium, workflow best practices, brand system upload, GitHub + MCP integration. Claude Opus 5 vision improvements.
- [[AI Daily Brief - The 4 AI Team Members Execs Should Hire Right Now]]


## Sources
- [[AI Daily Brief - The 4 AI Team Members Execs Should Hire Right Now]]

## Sources
- [[Claude Blog - Context Engineering for Claude 5]] — July 24, 2026. Thariq Shihipar. 80%+ system prompt reduction, zero eval loss. Five practice shifts for Fable-era context: judgment > rules, tool interface design, progressive disclosure, eliminate redundancy, auto-memory.
- [[Claude Blog - Claude Models Explained]] — July 24, 2026. Model family guide: Fable/Mythos/Opus/Sonnet/Haiku. Advisor Strategy (Sonnet 5 + Fable 5 advisor = 90% quality at 63% cost). Four-question selection framework. Custom evals over benchmarks.
- [[Claude Blog - Product Designer Claude Design]] — July 24, 2026. Nate Parrott (Anthropic). HTML as the prototyping medium, workflow best practices, brand system upload, GitHub + MCP integration. Claude Opus 5 vision improvements.
- [[AI Daily Brief - The 4 AI Team Members Execs Should Hire Right Now]]

- [[Max Junestrand]] — Founder/CEO of Legora. Building AI-native OS for legal teams on Claude.

+- [[Claude Blog - Context Engineering for Claude 5]] — July 24, 2026. Thariq Shihipar. 80%+ system prompt reduction, zero eval loss. Five practice shifts for Fable-era context: judgment > rules, tool interface design, progressive disclosure, eliminate redundancy, auto-memory.

+- [[Claude Blog - Claude Models Explained]] — July 24, 2026. Model family guide: Fable/Mythos/Opus/Sonnet/Haiku. Advisor Strategy (Sonnet 5 + Fable 5 advisor = 90% quality at 63% cost). Four-question selection framework. Custom evals over benchmarks.

+- [[Claude Blog - Product Designer Claude Design]] — July 24, 2026. Nate Parrott (Anthropic). HTML as the prototyping medium, workflow best practices, brand system upload, GitHub + MCP integration. Claude Opus 5 vision improvements.

- [[AI Daily Brief - The 4 AI Team Members Execs Should Hire Right Now]] — May 25, 2026. Framework for 4 agent roles leaders should implement.

- [[Instagram - hegetfunds - Claude Code Team of Developers]] — May 6, 2026. Using plugins/skills to assign specialist developer roles in Claude Code.

- [[Authority Hacker - Claude Code Setup Roast]] — May 21, 2026. 5-month setup audit: CLAUDE.md, folder structure, drift problem.


Now prepend to the Ingest Log.


1	# Ingest Log
2
3	Chronological record of everything added to this wiki.
4
5	---
6
7	## 2026-07-22 (Anthropic GitHub sweep #37)
8

# Ingest Log

Chronological record of everything added to this wiki.

---

## 2026-07-22 (Anthropic GitHub sweep #37)


---

## 2026-07-22 (Anthropic GitHub sweep #37)

---

## 2026-07-24 (Claude blog check — 3 posts)

- **[[Claude Blog - Context Engineering for Claude 5]]** (new source page) — Thariq Shihipar (Anthropic MTS). Landmark post: Anthropic removed 80%+ of Claude Code's system prompt for Fable/Mythos-era models with zero degradation on coding evals. Five practice shifts: (1) judgment > rigid rules, (2) tool interface design > examples, (3) progressive disclosure > upfront loading, (4) eliminate redundant instructions, (5) auto-memory > manual CLAUDE.md maintenance. New deferred loading pattern: tool schemas stored separately and accessed via ToolSearch only when the agent needs them, not pre-loaded into every context window. New `claude doctor` command for auditing over-specified skills/CLAUDE.md files. New concept: **[[Context Engineering for Claude 5]]**. Directly applicable to all of James's CLAUDE.md files and NanoClaw agent system prompts.

- **[[Claude Blog - Claude Models Explained]]** (new source page) — Anthropic. Official model family guide: Fable (most capable), Opus, Sonnet, Haiku. Four-question selection framework (difficulty, latency, access, unit economics). Key new concept: **Advisor Strategy** — pair Sonnet 5 as worker + Fable 5 as advisor for 90% of Fable quality at 63% of cost. Start with capable models, not cheap ones; more capable models often cost less per completed task. Updated [[Claude Fable 5 and Mythos 5]] with advisor strategy.

- **[[Claude Blog - Product Designer Claude Design]]** (new source page) — Nate Parrott (Anthropic product designer). HTML as the prototyping medium ("Claude is really good with HTML"). Workflow: brand system upload, GitHub component context, parallel prompt queuing, wireframe-first iteration. Claude Opus 5 vision improvements for reading charts/diagrams. Engineering org content; relevant for StageHand design workflow.

## 2026-07-22 (Anthropic GitHub sweep #37)


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

---

## 2026-07-22 (Anthropic GitHub sweep #37)

---

## 2026-07-24 (Claude blog check — 3 posts)

- **[[Claude Blog - Context Engineering for Claude 5]]** (new source page) — Thariq Shihipar (Anthropic MTS). Landmark post: Anthropic removed 80%+ of Claude Code's system prompt for Fable/Mythos-era models with zero degradation on coding evals. Five practice shifts: (1) judgment > rigid rules, (2) tool interface design > examples, (3) progressive disclosure > upfront loading, (4) eliminate redundant instructions, (5) auto-memory > manual CLAUDE.md maintenance. New deferred loading pattern: tool schemas stored separately and accessed via ToolSearch only when the agent needs them, not pre-loaded into every context window. New `claude doctor` command for auditing over-specified skills/CLAUDE.md files. New concept: **[[Context Engineering for Claude 5]]**. Directly applicable to all of James's CLAUDE.md files and NanoClaw agent system prompts.

- **[[Claude Blog - Claude Models Explained]]** (new source page) — Anthropic. Official model family guide: Fable (most capable), Opus, Sonnet, Haiku. Four-question selection framework (difficulty, latency, access, unit economics). Key new concept: **Advisor Strategy** — pair Sonnet 5 as worker + Fable 5 as advisor for 90% of Fable quality at 63% of cost. Start with capable models, not cheap ones; more capable models often cost less per completed task. Updated [[Claude Fable 5 and Mythos 5]] with advisor strategy.

- **[[Claude Blog - Product Designer Claude Design]]** (new source page) — Nate Parrott (Anthropic product designer). HTML as the prototyping medium ("Claude is really good with HTML"). Workflow: brand system upload, GitHub component context, parallel prompt queuing, wireframe-first iteration. Claude Opus 5 vision improvements for reading charts/diagrams. Engineering org content; relevant for StageHand design workflow.

## 2026-07-22 (Anthropic GitHub sweep #37)

+## 2026-07-24 (Claude blog check — 3 posts)

+- **[[Claude Blog - Context Engineering for Claude 5]]** (new source page) — Thariq Shihipar (Anthropic MTS). Landmark post: Anthropic removed 80%+ of Claude Code's system prompt for Fable/Mythos-era models with zero degradation on coding evals. Five practice shifts: (1) judgment > rigid rules, (2) tool interface design > examples, (3) progressive disclosure > upfront loading, (4) eliminate redundant instructions, (5) auto-memory > manual CLAUDE.md maintenance. New deferred loading pattern: tool schemas stored separately and accessed via ToolSearch only when the agent needs them, not pre-loaded into every context window. New `claude doctor` command for auditing over-specified skills/CLAUDE.md files. New concept: **[[Context Engineering for Claude 5]]**. Directly applicable to all of James's CLAUDE.md files and NanoClaw agent system prompts.

+- **[[Claude Blog - Claude Models Explained]]** (new source page) — Anthropic. Official model family guide: Fable (most capable), Opus, Sonnet, Haiku. Four-question selection framework (difficulty, latency, access, unit economics). Key new concept: **Advisor Strategy** — pair Sonnet 5 as worker + Fable 5 as advisor for 90% of Fable quality at 63% of cost. Start with capable models, not cheap ones; more capable models often cost less per completed task. Updated [[Claude Fable 5 and Mythos 5]] with advisor strategy.

+- **[[Claude Blog - Product Designer Claude Design]]** (new source page) — Nate Parrott (Anthropic product designer). HTML as the prototyping medium ("Claude is really good with HTML"). Workflow: brand system upload, GitHub component context, parallel prompt queuing, wireframe-first iteration. Claude Opus 5 vision improvements for reading charts/diagrams. Engineering org content; relevant for StageHand design workflow.

- All 30 updated repos already documented. Batch-update pattern (30 repos in ~3.5h) indicates a coordinated release/CI event, not new content. One genuinely new repo: `anthropics/k12-teacher-skills` (K-12 lesson planning + differentiation skills, eval rubrics, co-developed with Learning Commons — "Claude for Teachers" product). Out of scope for James's stack; skipped. No new skill commits.


Now I need to message James on telegram-mg-17796 with a concise bullet list of what was new and what was ingested.

Let me also think about whether there's anything to update in CLAUDE.local.md. The context engineering post mentions that CLAUDE.md files should be audited using `claude doctor` for Fable-era models. This seems like a useful note to add to CLAUDE.local.md for future reference. But actually the instruction says to update CLAUDE.local.md "if any new monitoring tasks or sources should be noted there" - and there's nothing new to monitor here. Skip.
Time to send that Telegram message to James.


Now send the Telegram summary to James.


Claude blog check — 3 new posts, all relevant, all ingested:

**1. Context Engineering for Claude 5** *(Thariq Shihipar — the big one)*
Anthropic removed 80%+ of Claude Code's system prompt for Fable/Mythos models with zero quality loss. Five practice shifts: judgment > rules, tool interface design > examples, progressive disclosure > upfront loading, eliminate redundancy, auto-memory > manual CLAUDE.md. New `claude doctor` command for auditing over-specified files. New concept page created.
→ https://jamess-mac-studio.tail02a1a0.ts.net/second-brain/#Context%20Engineering%20for%20Claude%205

**2. Claude Models Explained** *(Official Anthropic)*
Model family guide + the "Advisor Strategy": Sonnet 5 (worker) + Fable 5 (advisor) = 90% of Fable quality at 63% of cost. Four-question selection framework. Start with capable models, not cheap ones — they often cost less per completed task due to fewer retries.
→ https://jamess-mac-studio.tail02a1a0.ts.net/second-brain/#Claude%20Blog%20-%20Claude%20Models%20Explained

**3. Product Designer Claude Design** *(Nate Parrott, Anthropic)*
Workflow guide from the designer who built Claude Design. HTML as the prototyping medium, brand system upload pattern, parallel prompt queuing. Engineering org content; useful for StageHand design workflow.
→ https://jamess-mac-studio.tail02a1a0.ts.net/second-brain/#Claude%20Blog%20-%20Product%20Designer%20Claude%20Design


Message sent to telegram-mg-17796 (id: 3455)


<message to="telegram-mg-17796">Claude blog check — 3 new posts, all relevant, all ingested:

**1. Context Engineering for Claude 5** *(Thariq Shihipar — the big one)*
Anthropic removed 80%+ of Claude Code's system prompt for Fable/Mythos models with zero quality loss. Five practice shifts: judgment > rules, tool interface design > examples, progressive disclosure > upfront loading, eliminate redundancy, auto-memory > manual CLAUDE.md. New `claude doctor` command for auditing over-specified files. New concept page created.
→ https://jamess-mac-studio.tail02a1a0.ts.net/second-brain/#Context%20Engineering%20for%20Claude%205

**2. Claude Models Explained** *(Official Anthropic)*
Model family guide + the "Advisor Strategy": Sonnet 5 (worker) + Fable 5 (advisor) = 90% of Fable quality at 63% of cost. Four-question selection framework. Start with capable models, not cheap ones — they often cost less per completed task due to fewer retries.
→ https://jamess-mac-studio.tail02a1a0.ts.net/second-brain/#Claude%20Blog%20-%20Claude%20Models%20Explained

**3. Product Designer Claude Design** *(Nate Parrott, Anthropic)*
Workflow guide from the designer who built Claude Design. HTML as the prototyping medium, brand system upload pattern, parallel prompt queuing. Engineering org content; useful for StageHand design workflow.
→ https://jamess-mac-studio.tail02a1a0.ts.net/second-brain/#Claude%20Blog%20-%20Product%20Designer%20Claude%20Design</message>

Done. Three posts ingested:

- **3 source pages** created in `wiki/sources/`
- **1 concept page** created — `Context Engineering for Claude 5` (the most actionable one — directly relevant to every CLAUDE.md and agent system prompt in James's stack)
- **Claude Fable 5 and Mythos 5** tool page updated with the Advisor Strategy
- `Home.md` and `Wiki Ingest Log.md` updated

The context engineering post is the standout — Thariq's five shifts suggest James's current CLAUDE.md files are over-specified for Fable-era models. Running `claude doctor` across projects would be a natural next step.


<context timezone="America/Chicago" />
<task from="telegram-mg-17796" time="Jul 24, 2026, 8:00 AM">Script output:
{
  "updatedRepos": [
    {
      "name": "anthropics/claude-code",
      "updated": "2026-07-25T07:59:25Z",
      "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/code-migration-kit-with-claude-code",
      "updated": "2026-07-25T07:59:24Z",
      "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/skills",
      "updated": "2026-07-25T07:57:48Z",
      "desc": "Public repository for Agent Skills",
      "url": "https://github.com/anthropics/skills"
    },
    {
      "name": "anthropics/html-effectiveness",
      "updated": "2026-07-25T07:56:42Z",
      "desc": "HTML effectiveness examples",
      "url": "https://github.com/anthropics/html-effectiveness"
    },
    {
      "name": "anthropics/claude-for-legal",
      "updated": "2026-07-25T07:53:00Z",
      "desc": "A suite of plugins for legal workflows",
      "url": "https://github.com/anthropics/claude-for-legal"
    },
    {
      "name": "anthropics/defending-code-reference-harness",
      "updated": "2026-07-25T07:51:06Z",
      "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/financial-services",
      "updated": "2026-07-25T07:50:30Z",
      "desc": null,
      "url": "https://github.com/anthropics/financial-services"
    },
    {
      "name": "anthropics/knowledge-work-plugins",
      "updated": "2026-07-25T07:50:29Z",
      "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/prompt-eng-interactive-tutorial",
      "updated": "2026-07-25T07:50:17Z",
      "desc": "Anthropic's Interactive Prompt Engineering Tutorial",
      "url": "https://github.com/anthropics/prompt-eng-interactive-tutorial"
    },
    {
      "name": "anthropics/claudes-c-compiler",
      "updated": "2026-07-25T07:46:00Z",
      "desc": "Claude Opus 4.6 wrote a dependency-free C compiler in Rust, with backends targeting x86 (64- and 32-bit), ARM, and RISC-V, capable of compiling a booting Linux kernel.",
      "url": "https://github.com/anthropics/claudes-c-compiler"
    },
    {
      "name": "anthropics/claude-cookbooks",
      "updated": "2026-07-25T07:21:25Z",
      "desc": "A collection of notebooks/recipes showcasing some fun and effective ways of using Claude.",
      "url": "https://github.com/anthropics/claude-cookbooks"
    },
    {
      "name": "anthropics/claude-desktop-buddy",
      "updated": "2026-07-25T07:18:09Z",
      "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"
    },
    {
      "name": "anthropics/claude-agent-sdk-demos",
      "updated": "2026-07-25T06:59:40Z",
      "desc": "Claude Code SDK Demos",
      "url": "https://github.com/anthropics/claude-agent-sdk-demos"
    },
    {
      "name": "anthropics/claude-agent-sdk-typescript",
      "updated": "2026-07-25T06:50:19Z",
      "desc": null,
      "url": "https://github.com/anthropics/claude-agent-sdk-typescript"
    },
    {
      "name": "anthropics/claude-code-base-action",
      "updated": "2026-07-25T06:50:03Z",
      "desc": "This repo is a mirror of the contents of base-action in https://github.com/anthropics/claude-code-action.",
      "url": "https://github.com/anthropics/claude-code-base-action"
    },
    {
      "name": "anthropics/claude-code-action",
      "updated": "2026-07-25T06:49:34Z",
      "desc": null,
      "url": "https://github.com/anthropics/claude-code-action"
    },
    {
      "name": "anthropics/claude-agent-sdk-python",
      "updated": "2026-07-25T06:49:22Z",
      "desc": null,
      "url": "https://github.com/anthropics/claude-agent-sdk-python"
    },
    {
      "name": "anthropics/courses",
      "updated": "2026-07-25T06:47:42Z",
      "desc": "Anthropic's educational courses",
      "url": "https://github.com/anthropics/courses"
    },
    {
      "name": "anthropics/claude-code-security-review",
      "updated": "2026-07-25T06:46:58Z",
      "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/anthropic-sdk-python",
      "updated": "2026-07-25T06:30:16Z",
      "desc": null,
      "url": "https://github.com/anthropics/anthropic-sdk-python"
    },
    {
      "name": "anthropics/claude-quickstarts",
      "updated": "2026-07-25T06:29:23Z",
      "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/claude-plugins-official",
      "updated": "2026-07-25T06:16:20Z",
      "desc": "Official, Anthropic-managed directory of high quality Claude Code Plugins.",
      "url": "https://github.com/anthropics/claude-plugins-official"
    },
    {
      "name": "anthropics/launch-your-agent",
      "updated": "2026-07-25T06:00:22Z",
      "desc": "Claude Code skills that take a founder from idea to a live Claude Managed Agent: interview, scope a v0, launch in their own account, grade it, iterate, and schedule it",
      "url": "https://github.com/anthropics/launch-your-agent"
    },
    {
      "name": "anthropics/k12-teacher-skills",
      "updated": "2026-07-25T05:45:33Z",
      "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": "2026-07-25T05:40:10Z",
      "desc": "The CLI for the Claude API",
      "url": "https://github.com/anthropics/anthropic-cli"
    },
    {
      "name": "anthropics/jacobian-lens",
      "updated": "2026-07-25T03:17:50Z",
      "desc": " Companion code for the global workspace interpretability paper",
      "url": "https://github.com/anthropics/jacobian-lens"
    },
    {
      "name": "anthropics/claude-plugins-community",
      "updated": "2026-07-25T01:54:04Z",
      "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/original_performance_takehome",
      "updated": "2026-07-25T01:43:20Z",
      "desc": "Anthropic's original performance take-home, now open for you to try!",
      "url": "https://github.com/anthropics/original_performance_takehome"
    },
    {
      "name": "anthropics/cwc-long-running-agents",
      "updated": "2026-07-24T23:40:32Z",
      "desc": null,
      "url": "https://github.com/anthropics/cwc-long-running-agents"
    },
    {
      "name": "anthropics/anthropic-sdk-ruby",
      "updated": "2026-07-24T20:01:45Z",
      "desc": null,
      "url": "https://github.com/anthropics/anthropic-sdk-ruby"
    }
  ],
  "newSkillCommits": [
    {
      "message": "Update claude-api skill: Claude Opus 5 (#1476)\n\n* Update claude-api skill: Claude Opus 5\n\n- Add Claude Opus 5 (`claude-opus-5`) as the default model across all\n  SDK examples, model tables, pricing, and migration guidance.\n- Add an Opus 5 migration section covering the API changes that come\n  with it, and move Opus 4.8 into the previous-generation slot.\n- Drop the Opus 4.7 fast-mode guidance, which no longer applies.\n- Scope the server-side fallbacks beta header to the current version.\n\n* Update claude-api skill: Opus 5 fast-follow corrections\n\n- Server-side refusal fallbacks are available on Claude Platform on AWS,\n  not just the Claude API. Correct the availability statements in\n  SKILL.md, the migration guide, and the platform-availability table.\n- Simplify the effort guidance: start at `high` (the API default) and\n  sweep down, rather than starting at `xhigh` for coding work.\n- Add a time-to-first-token section with the prompt instruction that\n  reduces pre-answer thinking on latency-sensitive routes.\n- Replace the two separate thinking-disabled mitigations with the single\n  combined instruction that covers both failure modes.",
      "date": "2026-07-24T20:12:34Z",
      "url": "https://github.com/anthropics/skills/commit/b29e7cf65e5cb78a5ac33d582270551bc74a14eb"
    }
  ]
}

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>


There's a lot to process here. Let me evaluate relevance for each item:

**updatedRepos** - most of these are already documented in the wiki. Let me check which ones might have new content:
1. `anthropics/claude-code` - already documented as [[Claude Code]]. Worth checking for major updates.
2. `anthropics/code-migration-kit-with-claude-code` - already documented as [[Claude Code Migration Kit]]
3. `anthropics/skills` - already tracked, has a new skill commit (Claude Opus 5)
4. `anthropics/html-effectiveness` - already documented as [[HTML Effectiveness Examples]]
5. `anthropics/claude-for-legal` - already documented as [[Claude for Legal]]
6. `anthropics/defending-code-reference-harness` - already documented
7. `anthropics/financial-services` - already documented as [[Claude for Financial Services]]
8. `anthropics/knowledge-work-plugins` - already documented as [[Knowledge Work Plugins]]
9. `anthropics/prompt-eng-interactive-tutorial` - already documented
10. `anthropics/claudes-c-compiler` - already documented
11. `anthropics/claude-cookbooks` - already documented
12. `anthropics/claude-desktop-buddy` - already documented
13. `anthropics/claude-agent-sdk-demos` - already documented

Most of these repos are already tracked in the wiki, so I'm mainly looking for which ones have meaningful updates worth documenting. dy documented. The Ruby SDK probably isn't super relevant for James's needs. There's a major update to the claude-api skill with Claude Opus 5 becoming the default model, which involves updating model references, adjusting effort guidance, and simplifying thinking-disabled mitigations. I need to prioritize updating the claude-api documentation and potentially the Claude Fable 5 page with these changes.

Looking at what's actually new and worth acting on, the Claude Opus 5 update is clearly the most critical, followed by checking whether the cwc-long-running-agents repo needs fuller documentation beyond what's already captured in the existing workshop and agent primitives pages. Most of these repos were updated around the same time anyway.

From the commit message itself, I can see that Claude Opus 5 is now the default model, with Opus 4.8 moved to previous-generation status and Opus 4.7 designated as the fast variant.

The release also includes server-side refusal fallbacks now available on Claude Platform on AWS, updated effort guidance starting at `high` rather than `xhigh` for coding tasks, and a new time-to-first-token section with instructions to reduce extended thinking on latency-sensitive routes. These changes consolidate what were previously two separate thinking-disabled mitigations into a single combined instruction.

Since all 30 repositories updated simultaneously, this is clearly another coordinated release event like the one from July 22, 2026. I need to pull the full SKILL.md details from the claude-api skill, then update the Claude Opus 5 tool page, the model landscape pages, Home.md, and the Wiki Ingest Log.


The most important signal here is the skill commit: **Claude Opus 5** just became the default model with API changes. Let me fetch the full skill details while evaluating the repo sweep.


Bash

gh api repos/anthropics/skills/contents/claude-api/SKILL.md --jq '.content' | base64 -d 2>/dev/null | head -200

Fetch claude-api SKILL.md for Opus 5 details


/bin/bash: line 1: gh: command not found


gh api repos/anthropics/cwc-long-running-agents/readme --jq '.content' | base64 -d 2>/dev/null | head -120

Fetch cwc-long-running-agents README


WebFetch

Prompt: Extract all content about Claude Opus 5: model ID, API changes, effort guidance, time-to-first-token section, server-side fallbacks, thinking configuration, migration from Opus 4.8, and any new features or behavioral differences. Also extract the current model table and default model recommendations.


Request failed with status code 404

Error: Request failed with status code 404


Prompt: Extract the README content: what this repo is about, what it contains, key concepts or primitives documented, who it's for.


# cwc-long-running-agents Repository Overview

## What It Is
This repository provides **example primitives and patterns for building long-running Claude agents**, based on Anthropic's engineering blog posts on agent harness design. It's a reference implementation showing how to structure agents that maintain quality over extended runs.

**Key note:** These are example ingredients, not a turnkey harness. Built as a take-home for the Long-Running Agents station at Code with Claude 2026—not maintained and not accepting contributions.

## Core Contents

### The Three Quality Loop Primitives

1. **Default-FAIL Contract** (`hooks/track-read.sh` + `hooks/verify-gate.sh`)
   - Every criterion starts `false`; agents can't mark tasks passing without opening evidence first
   - Uses a `test-results.json` file to track completion
   - A `PreToolUse` hook denies writes to results unless evidence has been read

2. **Fresh-Context Evaluator** (`agents/evaluator.md`)
   - Separate agent with no Write/Edit tools grades work independently
   - Reviews diffs and screenshots from a context that never saw the build
   - Returns `PASS` or `NEEDS_WORK` with specific findings
   - Closes the build → evaluate → rebuild loop

3. **Agent-Maintained Handoff**
   - Agent writes progress to `PROGRESS.md` and commits to git
   - Next session picks up cleanly without memory loss
   - `commit-on-stop.sh` catches uncommitted work at session end

### Operator Control Hooks

- **`kill-switch.sh`**: Halts tool calls while `AGENT_STOP` file exists
- **`steer.sh`**: Surfaces `STEER.md` contents for mid-run redirection

## Two Ways to Run the Loop

### 1. Built-in `/goal` Command
```
/goal every feature in PROGRESS.md is implemented, committed, and its tests pass
```
- Works in Claude Code interactive, `-p` headless mode, and Remote Control
- Automatic checking after each turn

### 2. Custom Loop with Your Evaluator
```bash
while grep -q '"passes": false' test-results.json; do
  claude -p "Read PROGRESS.md and build the next unfinished feature..."
  VERDICT=$(claude --agent evaluator -p "Review the most recent commit...")
  [ "$(echo "$VERDICT" | head -1)" = "PASS" ] || echo "$VERDICT" > NEXT_FINDINGS.md
done
```

## Who It's For

- **Claude Code users** wanting custom long-running agent harnesses
- **Agent SDK developers** (patterns translate to `PreToolUse`/`Stop` callbacks)
- **Headless/automation users** building wrapper scripts around `claude -p`
- Teams building QA loops where agents evaluate their own work

## How to Use

**Option 1 - Cherry-pick:** Each primitive is standalone; copy what fits your needs.

**Option 2 - Full setup:**
```bash
cp -r claude-code-config/.claude /path/to/your/project/
chmod +x /path/to/your/project/.claude/hooks/*.sh
```

Then adapt `RESULTS_FILE`, evidence-file patterns, and point to your actual results file.

## Key Concepts

- **Evidence-based evaluation**: Agents must observe evidence before claiming success
- **Separation of concerns**: Builder and evaluator operate in separate contexts
- **Observable progress**: Everything lands on disk (`PROGRESS.md`, git log, screenshots, evidence reads)
- **Context-aware handoffs**: Structured notes enable clean multi-session runs


The claude-api SKILL.md gave a 404 (maybe it's in a different location). Let me try to fetch the specific commit to get the diff content, or try a different path.

For cwc-long-running-agents: this is already documented as [[Long-Running Agent Primitives]]. Let me check if the existing page covers what this repo actually contains. Looking at Home.md:

`[[Long-Running Agent Primitives]] — 3 core primitives (Default-FAIL, Fresh-context evaluator, Handoff) + 2 operator hooks (kill switch, STEER.md).
</current_rewritten_thinking>

The next thinking to rewrite:
<next_thinking>
From Anthropic's own patterns.`

Yes, this is already documented! The primitives match exactly (Default-FAIL, Fresh-context evaluator, agent-maintained handoff + kill switch + steer). So the cwc-long-running-agents repo just adds the code backing the patterns we already documented. I could update the existing page with the repo URL and concrete implementation details (track-read.sh, verify-gate.sh, etc.), but it's not a NEW discovery.

For Opus 5, let me try another path for the SKILL.md or look for it via the commit.
</next_thinking>

The cwc-long-running-agents repo is already covered by the existing Long-Running Agent Primitives documentation—the primitives match exactly, so this is just the implementation backing what we've already documented. I could enhance that page with the repo URL and specific implementation details like the shell scripts, but it's not a new discovery. Now I need to track down the Opus 5 SKILL.md file through a different path or commit.


Prompt: Extract: current default model (especially Claude Opus 5 details), model table, effort guidance, time-to-first-token instructions, server-side fallback availability, thinking configuration changes, migration guidance from Opus 4.8 to Opus 5. Return as much detail as possible.


Request failed with status code 404


Prompt: Extract the full diff content of the commit. What specific changes were made to the SKILL.md? Include all new sections, changed model IDs, new API parameters, effort guidance changes, and time-to-first-token section. Include the actual text added, not just descriptions.


# Claude Opus 5 Update - SKILL.md Changes

Based on the commit, here are the specific changes made to `skills/claude-api/SKILL.md`:

## Model Updates
- **Default model changed** from Claude Opus 4.8 to Claude Opus 5 (`claude-opus-5`) across all SDK examples
- Added Claude Opus 5 to model tables and pricing documentation
- Moved Opus 4.8 into the "previous-generation" slot

## Extended Thinking Changes

### New Thinking Behavior for Claude Opus 5
Added a new note about Claude Opus 5's default thinking behavior:

> **Claude Opus 5:** thinking is on by default — omitting `thinking` runs adaptive (equivalent to `{"type": "adaptive"}`), unlike Opus 4.8/4.7 where omitting it meant no thinking. `{"type": "disabled"}` is accepted only at effort `high` or lower; pairing it with `xhigh`/`max` returns a 400.

### Updated Model Coverage
Changed from:
> **Fable 5, Opus 4.8, Opus 4.7, Opus 4.6, and Sonnet 4.6:** Use adaptive thinking...

To:
> **Fable 5, Claude Opus 5, Opus 4.8, Opus 4.7, Opus 4.6, and Sonnet 4.6:** Use adaptive thinking...

### Removed Opus 4.7 Fast-Mode Guidance
Dropped the previous guidance specific to Opus 4.7 fast-mode, which no longer applies.

## Server-Side Refusal Fallbacks

### Scoped Beta Header to Current Version
Updated availability scope from broad to specific:
- The header must be exactly `server-side-fallback-2026-06-01` **for the array form**
- The newer `fallbacks: "default"` scalar form uses `server-side-fallback-2026-07-01` instead
- Pairing either header with the wrong form returns a 400

### Platform Availability Corrections
- Server-side refusal fallbacks are available on **Claude Platform on AWS**, not just the Claude API
- Corrected availability statements in SKILL.md, migration guide, and platform-availability table

## Effort Guidance Simplification
Changed from sweeping down starting at `xhigh` (for coding work) to:
- Start at `high` (the API default)
- Sweep down from there as needed

## New Section: Time-to-First-Token

Added guidance for reducing pre-answer thinking on latency-sensitive routes with specific prompt instructions.

## Thinking-Disabled Mitigations

Consolidated separate thinking-disabled mitigations into a single combined instruction that covers both failure modes.


Good. Now I have the key details for Claude Opus 5. Let me fetch the actual skill file to get more specifics, including the time-to-first-token prompt and the combined thinking-disabled mitigation instruction.


Prompt: Extract the full text of the SKILL.md file. I need: (1) the complete model table with all model IDs and characteristics, (2) the exact time-to-first-token prompt instruction text, (3) the combined thinking-disabled mitigation instruction, (4) the server-side fallback beta header versions and forms, (5) the complete effort guidance section, (6) the Opus 5 migration section, (7) any new pricing information.


The SKILL.md doesn't seem to be accessible directly. Let me try to access the skills repo page itself to find the right path.


Prompt: List all files in the claude-api directory. What is the main skill file called and what are its contents?


Let me try accessing the skills repo root to see the structure.


Prompt: What directories exist in this repo? List all top-level folders and files. Is there a claude-api folder? What's in it?


# Top-Level Directories and Files

Based on the repository structure shown, the top-level folders and files are:

**Folders:**
- `.claude-plugin/`
- `skills/`
- `spec/`
- `template/`

**Files:**
- `.gitignore`
- `README.md`
- `THIRD_PARTY_NOTICES.md`

## Is there a claude-api folder?

**No**, there is no `claude-api` folder at the top level of this repository.

## What's in the key directories:

- **`skills/`** - Contains skill examples organized by categories: Creative & Design, Development & Technical, Enterprise & Communication, and Document Skills
- **`spec/`** - Contains the Agent Skills specification
- **`template/`** - Contains a skill template for creating custom skills
- **`.claude-plugin/`** - Plugin configuration (likely for Claude Code plugin marketplace registration)

The repository is focused on demonstrating and providing skills that Claude can use, along with documentation and templates for creating custom skills.


Hmm, the `claude-api` folder doesn't exist in the skills repo anymore. Maybe the skill commit was merged into a different location, or the skills repo structure changed. Looking at the commit message, it says `skills/claude-api/SKILL.md` - this might be a different structure than what's currently in the repo, or it might have been refactored.

Actually, looking at the Home.md, it says:
`[[Anthropic Skills Repo]] — Reference implementations of the Claude Agent Skills system. Template for building custom skills.`

But the commit was to `anthropics/skills`.

The commit hash approach already gave me enough information about the changes though, so I have the key details I need. The repository seems to be private or inaccessible, so I'm going to stop chasing down those additional details and work with what I've already extracted from the commit message. I have the core facts I need about the model changes and thinking behavior, so I can move forward with writing the documentation.

Beyond what I already noted, there are several other key details: thinking can only be disabled at `high` effort or lower, not with `xhigh` or `max`; the effort guidance recommends starting at `high` as the API default and adjusting downward; there are two forms of server-side fallbacks with different dates; there's a new section on reducing pre-answer thinking for latency-sensitive routes; and these refusal fallbacks are now available on Claude Platform on AWS as well.

I need to create a new tool page for Claude Opus 5 as the default model.

For the wiki updates, I'm adding Opus 5 to the model landscape section, updating the home page tools list, and logging the dated entry. The cwc-long-running-agents repo already has documentation through the Long-Running Agent Primitives page, but I should add the actual repo URL and implementation details like the shell scripts. The 30-repo sweep appears to be part of a coordinated release event, and while those repos were previously documented, I'm noting this simultaneous update pattern.

Now I'm planning the specific actions: create the Opus 5 tool page, reference it from the Fable 5 page, update the Long-Running Agent Primitives with the repo details, refresh Home.md, log the ingest entry, and notify James. I'm also checking whether there's an existing claude-api skill page that needs updating, though the ingest log doesn't show one yet.


I have enough from the commit. The coordinated 30-repo update is a release event tied to **Claude Opus 5** — the only genuinely new content is the skill commit and the `cwc-long-running-agents` repo (which backs the [[Long-Running Agent Primitives]] page already in the wiki). Let me write the pages now.