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Fable Audit

Community
Junhan2
fable-audit

Read-only gap check. Finds which of the 16 sections of Anthropic's Fable 5.1 prompting guide your CLAUDE.md, rules files, and agent system prompts are missing, which of your rules push against a section, and what the plugin already covers; the Opus 5 / Opus 5.5 / Sonnet 5.5 / Haiku 5.5 model notes are listed unscored. Changes nothing; it prints suggested wording to add and stops. For dated, stale or contradictory text to remove, use Claude Code's /doctor prompt-audit instead. Use /fable-setup to apply changes, /fable-status to see what is in effect. Triggers: "/fable-audit", "가이드 대조", "가이드에서 빠진 것", "check against the Fable guide", "which guide sections am I missing", "what does the prompting guide say that my rules lack".

Overview

PublisherJunhan2
Repositoryoh-my-fable
Skill namefable-audit
Stars
57
Forks
7
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Junhan2 on GitHub. Read the source before you install it.

Installation

Install the Fable Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Junhan2/oh-my-fable/tree/main/skills/fable-audit
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Junhan2/oh-my-fable.git /tmp/oh-my-fable
mkdir -p .claude/skills
cp -r /tmp/oh-my-fable/skills/fable-audit .claude/skills/fable-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fable Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Fable Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Fable Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

fable-audit · which guide sections your prompts are missing

This skill answers "which sections of the prompting guides are missing from my rules": gaps to add, and rules that push against a section. Claude Code's own /doctor prompt-audit (2.1.283+) answers the other question, "what in my rules is dated, stale or contradictory": old-model workarounds, stale paths and commands, instruction files that disagree, to remove. The two are complementary; run both when tidying a setup, and don't duplicate the other's job here (a line that is merely old or verbose is not a finding for this audit unless it conflicts with a section).

Checklist: ${CLAUDE_PLUGIN_ROOT}/skills/fable-audit/references/guide-sections.md (16 sections, verdict rules, conflict signals, suggested wording). Read it before judging anything; do not audit from memory.

This skill never writes. No Edit, no Write, no settings change, not even a "small obvious fix". A user's rule that contradicts the guide is often deliberate. Print the finding and the suggested wording; the user decides, and /fable-setup applies. If asked mid-run to fix something, say that /fable-audit is read-only and name the command that does it.

Arguments

No argument audits this machine's active prompt surface. Otherwise: <path> one file or directory (an agent's system prompt, a project's rules folder) · global (~/.claude only) · project (the current directory only) · plugin (the plugin's own rule texts, for maintainers) · section <n|slug> (one section, in depth: fetch that section's anchor URL from the checklist header for the live wording, then every place it is or isn't satisfied).

Step 1 · Collect (one batch of reads, silent)

Default set:

  • ./CLAUDE.md, ./.claude/CLAUDE.md, ~/.claude/CLAUDE.md (honour CLAUDE_CONFIG_DIR)
  • every *.md in ~/.claude/rules/ and ./.claude/rules/
  • ~/.claude/settings.json, ./.claude/settings.json, and CLAUDE_CODE_EFFORT_LEVEL (sections 1 and 14)
  • the plugin's active rule text: ${CLAUDE_PLUGIN_ROOT}/hooks/always-on.md, plus autonomy-unattended.md (two paragraphs) and subagent.md. Read ~/.claude/oh-my-fable.json first; if the plugin is disabled or absent, skip these and say so in the header line, because then nothing is covered for free.
  • when a path argument names a directory of agent prompts, each file in it is one audited surface

List the files you actually read, with a count. Never claim a section is missing from files you did not open; scope every negative to the paths in that list.

Step 2 · Judge each of the 16 sections

For each section apply the verdict rules in the checklist file:

✅ present · 🟡 partial (say exactly what is missing) · ❌ absent · ⚠️ a rule contradicts the guide · ⚪ not applicable to this surface (harness- or setting-owned, or the work never hits it)

Two rules that decide most of the value of this audit:

  • Quote the evidence. Every ✅, 🟡 and ⚠️ names the file and quotes the clause it rests on. A verdict with no quote is a guess; mark it 🟡 and say you could not confirm it.
  • Same meaning counts. The guide's wording is not required. A rule that achieves the section's effect in the user's own words is ✅. Only a rule that pushes the opposite way is ⚠️.

Sections 8 and 9 are scored in halves and by item; see the checklist.

Then apply the model notes at the end of the checklist. A note gets a verdict only when the surface names its model (model: in agent frontmatter, or the user said which model it runs on); otherwise print it once as "if this surface runs on " with no symbol. Notes are never part of the score.

Step 3 · Report (one table, then three short lists)

Fable 5.1 guide audit · <surface> · N files
[table: # | section | verdict | where it is, or what is missing]
Score: X/Y prompt-scope sections (✅ counts 1, 🟡 counts 0.5). Setting: <effort finding>.

Y is the count of prompt-scope sections that apply to this surface — never 16 flat, and say which ones you excluded and why. Then:

  1. Conflicts (⚠️) first, most consequential first. For each: the clause, why it now works against the model, and the narrowest edit that keeps what the rule was protecting. Never propose deleting a rule outright when narrowing it preserves the original intent (the checklist calls this out for section 15).
  2. Gaps worth closing, ranked by how often the surface hits them, not by section order. For each, the exact line to add and the file it belongs in. Prefer one agent's system prompt over a global rule when only that agent is affected.
  3. Already covered by the plugin, one line, so the user doesn't re-add what the hook delivers.
  4. Model notes (unscored), one line each, only the ones that apply to this surface.

Ask in the user's language; keep the section names in English so they match the guide's anchors.

Step 4 · Close

One line naming what to do next: /fable-setup for delivery, mode and effort; hand edits for a user's own CLAUDE.md; /fable-status to confirm what is live. Then one more line: "For dated, stale or contradictory text to remove, run /doctor prompt-audit (Claude Code 2.1.283 or later); this audit only finds what is missing." Then one status line: DONE, DONE_WITH_CONCERNS (say which files could not be read), or NEEDS_CONTEXT (say which path you need).

Notes

  • The checklist is a snapshot of the guide as of 2026-09-29; the model notes as of 2026-09-29 (Opus 5, Opus 5.5, Sonnet 5.5 guides) and 2026-10-11 (Haiku 5.5 guide). If the live guide has more or differently named sections, say so in the header line rather than silently auditing an old list.
  • Auditing a Claude Code machine is the common case, so sections 4, 14 and 16 usually resolve to ⚪ or a setting finding. That is a correct result, not a thin one.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Fable Audit AI skill do?

Read-only gap check. Finds which of the 16 sections of Anthropic's Fable 5.1 prompting guide your CLAUDE.md, rules files, and agent system prompts are missing, which of your rules push against a section, and what the plugin already covers; the Opus 5 / Opus 5.5 / Sonnet 5.5 / Haiku 5.5 model notes are listed unscored. Changes nothing; it prints suggested wording to add and stops. For dated, stale or contradictory text to remove, use Claude Code's /doctor prompt-audit instead. Use /fable-setup to apply changes, /fable-status to see what is in effect. Triggers: "/fable-audit", "가이드 대조", "가이드에...

Why use Fable Audit on TypingMind?

Because you install it once and use it with any model. Fable Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Fable Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Junhan2/oh-my-fable/tree/main/skills/fable-audit. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Fable Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Fable Audit?

As many as you like. As long as a model supports skills, you can use Fable Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Fable Audit AI skill free?

Yes. It is published on GitHub by Junhan2 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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