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Skill Review

  • 1k installs
  • 3.8k repo stars
  • Updated May 11, 2026
  • sanyuan0704/sanyuan-skills

Skill Review is a Claude Code skill that delivers specific, actionable feedback on structure, clarity, and token efficiency for custom Claude Code skills developers create before publishing.

About

Skill Review is a quality audit skill from sanyuan0704/sanyuan-skills for Claude Code skill authors. It analyzes skill structure, description quality, workflow design, token efficiency, and anti-patterns against documented best practices. The iron law requires every critique to state exactly what to change and why it matters for model behavior—never vague "could be improved" feedback. Trigger phrases include review skill, audit skill, skill quality, check my skill, evaluate skill, skill lint, validate skill, and improve this skill. Developers reach for Skill Review after drafting a SKILL.md and before sharing it with a team or publishing to a skill catalog, when they need a structured pass that catches weak descriptions, bloated prompts, and workflow gaps.

  • Follows a strict 3-step workflow: Load Target, Analyze, Report
  • Evaluates five core dimensions: structure compliance, description quality, workflow design, token efficiency, and anti-p
  • Delivers prioritized, concrete suggestions instead of vague advice
  • Always explains exactly what to change and why it improves model output quality
  • Accepts explicit path, current directory, or skill name as input

Skill Review by the numbers

  • 1,012 all-time installs (skills.sh)
  • +39 installs in the week ending Aug 5, 2026 (Skillselion tracking)
  • Ranked #1,042 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/sanyuan0704/sanyuan-skills --skill skill-review

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Listed on Skillselion
Installs1k
repo stars3.8k
Last updatedMay 11, 2026
Repositorysanyuan0704/sanyuan-skills

How do you review Claude Code skill quality?

Receive specific, actionable feedback that improves the structure, clarity, and token efficiency of any custom Claude Code skill they create.

Who is it for?

Developers authoring custom Claude Code skills who want a structured quality pass with concrete edits before publishing or sharing.

Skip if: Teams reviewing general application code, pull requests, or non-skill documentation unrelated to SKILL.md agent instruction files.

When should I use this skill?

User says review skill, audit skill, skill quality, check my skill, evaluate skill, skill lint, validate skill, or improve this skill.

What you get

Specific, actionable revision notes covering skill structure, triggers, workflow steps, and token-optimized prompt edits.

  • actionable skill revision checklist
  • token-optimized prompt edits

Files

SKILL.mdMarkdownGitHub ↗

Skill Review

IRON LAW: Be specific and actionable. Never say "could be improved" without stating exactly what to change and why it matters for model output quality.

Workflow

Skill Review Progress:

- [ ] Step 1: Load Target ⚠️ REQUIRED
  - [ ] 1.1 Identify skill path
  - [ ] 1.2 Read SKILL.md and inventory all files
- [ ] Step 2: Analyze ⚠️ REQUIRED
  - [ ] 2.1 Structure compliance
  - [ ] 2.2 Description quality
  - [ ] 2.3 Workflow design
  - [ ] 2.4 Token efficiency
  - [ ] 2.5 Anti-pattern detection
- [ ] Step 3: Report ⚠️ REQUIRED
  - [ ] 3.1 Strengths (what's done well)
  - [ ] 3.2 Suggestions (prioritized improvements)

Step 1: Load Target ⚠️ REQUIRED

Identify the skill to review. Accept:

  • Explicit path: /skill-review path/to/skill
  • Current directory context: if user is already in a skill folder
  • Skill name: search within the workspace for matching skill directory

Read the full SKILL.md and list all files in the skill directory. Count SKILL.md line count — this is a key metric.

Step 2: Analyze ⚠️ REQUIRED

Load references/review-criteria.md for detailed criteria. Evaluate the skill across five dimensions:

2.1 Structure Compliance

Questions to answer:

  • Does the directory follow the standard layout (SKILL.md, scripts/, references/, assets/)?
  • Is SKILL.md under 500 lines?
  • Does frontmatter contain only name and description (plus optional allowed-tools, license, metadata)?
  • Are there unnecessary files (README.md, CHANGELOG.md, LICENSE duplicates)?
  • Are references organized by domain with one level of nesting?

2.2 Description Quality

Questions to answer:

  • Does the description include concrete trigger keywords and phrases?
  • Does it use keyword bombing (multiple phrasings of the same intent)?
  • Is it self-contained — can a router understand what this skill does without reading the body?
  • Does it avoid putting "When to Use" info in the body instead of the description?
  • Would a user's natural language query match this description?

2.3 Workflow Design

Questions to answer:

  • Is there a trackable checklist with copy-paste-friendly format?
  • Are critical steps marked with ⚠️ REQUIRED or ⛔ BLOCKING?
  • Are there confirmation gates before destructive/generative operations?
  • Is the workflow linear and progressive, or does it jump around?
  • Are sub-steps used where complexity demands it?

2.4 Token Efficiency

Questions to answer:

  • Is there an Iron Law or core constraint at the top?
  • Does SKILL.md only contain what Claude doesn't already know?
  • Are references loaded progressively (on-demand) rather than all upfront?
  • Are instructions in imperative form (not "You should...")?
  • Are scripts executed rather than loaded into context?
  • Is there redundancy between SKILL.md and reference files?

2.5 Anti-Pattern Detection

Check for these known bad patterns:

  • Vague directives ("ensure good quality", "make it better")
  • Placeholder residue (TODO, FIXME, xxx, TBD)
  • Over-specification of things Claude already knows
  • No anti-patterns section (model has no guardrails against lazy defaults)
  • Missing pre-delivery checklist (no concrete verification criteria)
  • Giant monolithic SKILL.md with no reference extraction
  • Instructions that describe WHAT rather than constrain HOW

Step 3: Report ⚠️ REQUIRED

Output Format

Present the review in this order:

1. Strengths — What this skill does well. Be specific: quote the actual lines or patterns that work. Minimum 2 strengths, even for weak skills (find what's salvageable).

2. Suggestions — Improvements sorted by impact (highest first). Each suggestion must include:

  • What: the specific issue found
  • Where: file and location
  • Fix: concrete actionable change (show before/after when helpful)

Group suggestions by dimension only if there are many (5+). Otherwise present as a flat prioritized list.

Tone

  • Direct, constructive, collegial
  • Lead with genuine strengths — not filler praise
  • Suggestions are opportunities, not failures
  • If the skill is already solid, say so briefly and move on

Anti-Patterns for This Skill

  • Giving vague praise ("nice structure!") without quoting what specifically works
  • Listing problems without actionable fixes
  • Reviewing against personal taste rather than the documented principles
  • Suggesting over-engineering for simple skills
  • Flagging missing features that the skill intentionally omits (check if simplicity is the point)

Related skills

FAQ

What does Skill Review analyze in a Claude Code skill?

Skill Review analyzes skill structure, description quality, workflow design, token efficiency, and anti-patterns against best practices. Every finding must state exactly what to change and why it matters for model behavior.

When should developers run Skill Review?

Developers should run Skill Review when they want to review, audit, lint, evaluate, validate, or improve a custom Claude Code skill. Common triggers include phrases like review skill, audit skill, check my skill, or is this skill good.

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