Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tienenwu/fables --skill thinking-kernelgit clone --depth 1 https://github.com/tienenwu/fablesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tienenwu/fables/thinking-kernel)<a href="https://agentmods.dev/skills/tienenwu/fables/thinking-kernel"><img src="https://agentmods.dev/badge/skills/tienenwu/fables/thinking-kernel/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tienenwu/fables/thinking-kernel"><img src="https://agentmods.dev/badge/skills/tienenwu/fables/thinking-kernel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00082 | $0.02045 |
| Opus 5.5 | $0.00033 | $0.00818 |
| Sonnet 5.5 | $0.00016 | $0.00409 |
| Haiku 4.5 | $0.00008 | $0.00204 |
Grade A, and why
thinking-kernel scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🌐 繁體中文（canonical） · English mirror
Thinking Kernel: Seven Moves That Generate Criteria
Positioning: each domain playbook (android/ios/flutter/frontend-web/backend-server) is the "crystallized judgment";
this file is the "moves that produce those judgments." When you hit a domain or situation no playbook covers, don't wing it —
run these seven moves and generate the criteria yourself. After generating, write them back into a playbook and add a matching quiz item in lockstep (rules and quizzes move together).
The full cross-domain derivation table and an unfamiliar-domain worked example are in references/derivations.md.
Move 1: Grading Evidence Strength — "Does this verification actually prove this claim?"
Procedure: ① List the difference axes between the "verification environment" and the "environment the claim lives in" (compile mode, machine, data volume, concurrency, environment flags, time). ② If the claim falls on some difference axis, that verification's evidence strength is zero on it. ③ Swap in a verification that covers that axis, or state outright "this point is unverified." Derivation example: debug green ↛ release safe (R8 only takes effect in release); passed on one machine ↛ rolling-deploy safe (old and new coexist during the deploy window); simulator ↛ signing/entitlement (the simulator does no real signing). Applying to a new domain: first ask "what difference axes does this domain have" — each axis automatically spawns a batch of "X can't prove Y" criteria.
Move 2: Constructing the Failure Scenario — "What input/state → what bad outcome?"
Procedure: For any rule, coding pattern, or review comment, force-construct one concrete failure chain: "when [input/state], it will [bad outcome]." Constructible → it's a real problem, severity set by the bad outcome; not constructible → downgrade to a nit or delete it. Derivation example: "only log after catch" → when upload fails the user sees a forever-spinning spinner (real problem); "the naming here isn't elegant enough" → no failure chain constructible → nit. index as list key → deleting a row misaligns the checked state onto the wrong row. Applying to a new domain: this is the QC gate for reviews and rule-writing — a comment that can't state a failure scenario is not allowed onto the list.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 87 lines · 82 tokens per session scan A 4bad48c7bc65
thinking-kernel is a skill published in the GitHub repository tienenwu/fables (4 stars, last pushed 2mo ago), licensed MIT. It adds 82 tokens to every session and 2,045 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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