audit-claude-md

Audit any project's CLAUDE.md (or AGENTS.md) against best practices and score its effectiveness. Use when reviewing a client's AI development setup, onboarding a new codebase, or improving your own CLAUDE.md. Triggers on requests like "audit my CLAUDE.md", "score my AI setup", "review my project context file", or "how good is my CLAUDE.md".

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

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Install skill "audit-claude-md" with this command: npx skills add skinnyandbald/fish-skills/skinnyandbald-fish-skills-audit-claude-md

CLAUDE.md Audit

Analyze and score a project's CLAUDE.md against research-informed best practices (ETH Zurich ICML 2026 + production AI-assisted development workflows). Emphasizes what agents CANNOT discover on their own: behavioral constraints, non-standard tools, and project-specific footguns.

Arguments: $ARGUMENTS

Instructions

Audit the CLAUDE.md (or AGENTS.md / .cursorrules) in the current project and score it against the rubric in references/scoring-rubric.md.

If a path is provided in $ARGUMENTS, audit that file instead.

Phase 1: Discover the AI Context Files

Search for all AI context files in the project:

  1. Check project root for: CLAUDE.md, AGENTS.md, .cursorrules
  2. Check for nested CLAUDE.md files in subdirectories (e.g., src/CLAUDE.md, docs/CLAUDE.md)
  3. Check for linked guide directories: docs/claude/, docs/ai/, .claude/
  4. Check for .claude/learnings/ directory
  5. Check for .claude/skills/, .claude/commands/, .claude/hooks/

Report what was found before scoring.

Phase 2: Read and Analyze

Read the main CLAUDE.md file. If it links to other files (e.g., docs/claude/tdd.md), read those too — they contribute to the score.

Count the total line count of the main file. Note whether detail lives in linked files or is crammed into one file.

Phase 3: Score Against Rubric

Read references/scoring-rubric.md and score each category.

Scoring rules:

  • Full points: Item is present, specific, and actionable
  • Partial points (half, rounded down): Item exists but is vague, incomplete, or generic
  • Zero points: Item is missing entirely

Be generous with partial credit — a vague section is better than no section.

Phase 4: Generate Report

Output the report in this format:

# CLAUDE.md Audit Report

**Project:** [project name from CLAUDE.md or directory name]
**Files found:** [list of AI context files discovered]
**Main file:** [path] ([line count] lines)
**Linked files:** [count and paths]

## Overall Score: [X]/103 — [Tier Name]

[1-2 sentence summary of the file's strengths and biggest gap]

---

## Foundations — [X]/12

[Table per rubric format]

**Top recommendation:** [...]

## Standards — [X]/14

[Table per rubric format]

**Top recommendation:** [...]

## Behavior Configuration — [X]/29

[Table per rubric format]

**Top recommendation:** [...]

## Architecture — [X]/22

[Table per rubric format]

**Top recommendation:** [...]

## Memory & Learning — [X]/10

[Table per rubric format]

**Top recommendation:** [...]

## Advanced — [X]/16

[Table per rubric format]

**Top recommendation:** [...]

---

## Priority Actions (Top 3)

1. **[Highest impact action]** — [why and what to do] (+[X] points)
2. **[Second action]** — [why and what to do] (+[X] points)
3. **[Third action]** — [why and what to do] (+[X] points)

**Potential score after fixes:** [X]/103 — [New Tier Name]

Phase 5: Offer Next Steps

After presenting the report, offer:

  1. Fix it now — Implement the top 3 recommendations directly
  2. Generate a template — Create a CLAUDE.md template pre-filled with the project's detected stack and conventions
  3. Compare to reference — Show what an elite CLAUDE.md looks like (read references/elite-example.md)
  4. Save report — Write the audit report to a file

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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