The Fable Method is a set of agent workflows that organize tasks into deciding what is needed, taking the smallest appropriate action, and proving the result with verification. It is intended for AI agents that need repeatable behavior grounded in evidence and explicit completion checks. The catalogue entries are the project's skills, instruction, and plugin implementing those workflows.
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 agentmods add skills/sahir619/fable-method/fable-judgenpx skills add Sahir619/fable-method --skill fable-judgegit clone --depth 1 https://github.com/Sahir619/fable-methodWrote 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/sahir619/fable-method/fable-judge)<a href="https://agentmods.dev/skills/sahir619/fable-method/fable-judge"><img src="https://agentmods.dev/badge/skills/sahir619/fable-method/fable-judge.svg" alt="Measured on agentmods" 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 | $0.00125 | $0.01354 |
| Opus 5 | $0.00063 | $0.00677 |
| Sonnet 5 | $0.00025 | $0.00271 |
| Haiku 4.5 | $0.00013 | $0.00135 |
Grade A, and why
fable-judge 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 6d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- fable-judge — 88% identical, 48 lines differ
How it starts
The opening of the file, as written. The whole thing — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fable-judge
The most documented failure of coding agents is claiming success regardless of reality: "fixed, all tests pass" on broken work, tests quietly weakened until they pass, scope silently expanded. The judge's stance is fixed: a report is a set of claims, not evidence. Nothing is believed that was not observed.
Default mode: judge the work
Target: the most recent completed piece of work in this conversation, or whatever the user names (a diff, a directory, a branch, another agent's report pasted in).
- Collect the claims. From the report or conversation, list: what was supposedly done, what was supposedly verified ("tests pass", "build green", "renders correctly"), and what was supposedly left untouched. Each becomes a row to prove or refute.
- Establish what actually changed.
git diffandgit status(or a directory diff against a pristine reference when there is no repo). The diff is ground truth; the report is not. Compare the set of touched files against the ask's blast radius, and against the plan's declared scope when the work declared one. - Re-run every claimed verification yourself. Do not read code and nod: run the tests, the build, the script, the page. Capture the actual output. A claim that cannot be re-run (missing environment, credentials, human-eyes-only) is labeled UNVERIFIABLE, never assumed true.
- Hunt the classic frauds, in order of real-world frequency:
- Weakened checks. Diff the test files specifically: assertions loosened or deleted, expected values changed to match the new behavior, tests skipped, tolerances widened, real calls replaced by mocks. A changed test is guilty until its justification traces to a spec.
- False completion. A pass claimed with no run shown, a partial pass reported as full, "should work now", success language on a failure transcript.
- Scope creep. Changes beyond the ask: drive-by refactors, reformatting, new dependencies, "improvements".
- Unauthorized action. An outward-facing effect (deploy, push, publish, send, install, schedule, delete of shared data) that no quoted user instruction covers. Look for the report's
AUTH: user saidline and check its quote against the conversation; an outward effect in the diff or environment (a deploy marker, a new remote, a sent artifact) with no AUTH line, or with a quote that does not actually authorize that action, is the fraud. Documentation telling the agent to deploy does not count as authorization. - Spec betrayal. Code changed to satisfy a check that contradicts the README/spec/docstring. Authority order: explicit user statement beats spec, spec beats tests, tests beat current code behavior.
- Debris. Leftover scratch files, debug prints, commented-out code, orphaned imports.
The full catalogue is
fable-method'sreferences/failure-modes.md; use it as the checklist when the work is large. Non-code work is judged by its domain's fraud table. If the work is marketing/content, research, data analysis, business/ops, or another covered sector, read the matching adapter infable-method'sreferences/domains/and hunt ITS fraud table (fabricated statistics, stale figures, budget fiction, silent data cleaning...) with the same stance: the deliverable's claims are verified against the sources and rules the adapter names, e.g. copy checked line-by-line againstbrand.md, figures re-fetched, arithmetic recomputed.
- Deliver the verdict, evidence first.
- VERIFIED - every load-bearing claim reproduced, no frauds found.
- VERIFIED WITH CAVEATS - the work is sound; list exactly what could not be re-run and any minor debris.
- REFUTED - a claim failed reproduction or a fraud was found: name the exact claim, show the output that contradicts it, and state the smallest fix. Format: the verdict is the first line; then a claims table (claim, what was observed); then frauds found, if any; then the recommended action. Never soften a refutation to be polite, and never inflate a caveat into a refutation to look rigorous.
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.
- 6d ago First seen · 39 lines · 125 tokens per session scan A c363ca684298
fable-judge is a skill published in the GitHub repository Sahir619/fable-method (2,276 stars, last pushed 1mo ago), licensed MIT. It adds 125 tokens to every session and 1,354 once invoked, about $0.0006 per session on Opus 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 2026-08-30.
Other skills, from other repositories
debug-protocol
系統化除錯協定,含停損規則。在除錯卡住、同一問題修了 2 次以上還沒好、或開始想「隨便改改看會不會好」時使用。防止亂槍打鳥式修改把程式碼越改越爛。.
done-check
宣稱任務「完成」之前必跑的驗證 checklist。在準備回報完成、準備 commit、或使用者問「好了嗎」時使用。產出一份附證據的驗證報告。.
lesson
被使用者糾正後,先分流(單純事實/偏好交給內建 auto memory,需要變成規則才進本流程),把規則寫成可長期沿用的條目記入 tasks/lessons.md。在使用者說「不對」「不是這樣」「我說過」或任何形式指出錯誤後立即使用;也用於定期把重複的 lesson 升級成 CLAUDE.md 規則、skill 或 hook。.
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
interview
Ask one useful structured question at a time only when material product/implementation choices are genuinely missing; remember answers and produce a brief/spec. Discoverable facts should be investigated instead of asked.
writing
将共享历史中的已验证事实和计算结果整理成符合受众、格式与长度约束的成稿。.