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skill-review

skill-review

github.com/richtaborAgent workflows7361 installsUpdated 30w ago
Repository

About skill-review

skill-review is a review skill for checking agent skills against the Agent Skills standard and best practices. It assesses structure, metadata, descriptions, and content organization, with both quick checks and a detailed review process.

Key features

  1. 01Check skill directory structure and required files
  2. 02Validate YAML metadata and description quality
  3. 03Assess progressive disclosure and content length
  4. 04Identify common anti-patterns and organize findings

Use cases

  1. 01Check a new skill draft before publishing
  2. 02Review the structure and description of one skill
  3. 03Audit multiple skills in a skills directory

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/richtabor/agent-skills --skill skill-review

After installing, type/skill-reviewin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

README.md
references/
best-practices.md
checklist.md

Details

From the project README

Skill Review

Overview

Validates agent skills against the Agent Skills standard and compiled best practices. Reviews structure, frontmatter, description quality, progressive disclosure, and common anti-patterns.

When to Use

  • User asks to review or validate a skill
  • User is creating a new skill and wants feedback
  • User asks "is this skill well-written?"
  • User mentions skill quality, best practices, or improvement

Review Process

Phase 1: Load References

Before reviewing, read:

  • references/best-practices.md — Comprehensive guidelines
  • references/checklist.md — Quick validation checklist
Phase 2: Identify Target

Determine what to review:

  • Single skill: Review skills/<name>/SKILL.md and its structure
  • All skills: Audit entire skills/ directory
  • New skill draft: Review provided content before creation
Phase 3: Structural Audit

Check the skill directory structure:

skill-name/
├── SKILL.md              # Required
├── references/           # Optional - loaded docs
├── scripts/              # Optional - executable code
└── assets/               # Optional - output files (not loaded)

Verify:

  • SKILL.md exists
  • Directory name matches name in frontmatter
  • References are one level deep (no nested chains)
  • Scripts use forward slashes (no Windows paths)
  • No extraneous files (README.md, CHANGELOG.md, etc.)
  • Script paths in SKILL.md body (scripts/foo.py) exist in directory
  • If scripts use external binaries, dependencies are documented
Phase 4: Frontmatter Validation

Check YAML frontmatter:

---
name: skill-name          # Required: lowercase, hyphens, ≤64 chars
description: >-           # Required: ≤1024 chars, third-person
  What it does. When to use it.
---

Validate:

  • name: Lowercase with hyphens only ([a-z0-9-])
  • name: ≤64 characters
  • name: No "anthropic" or "claude" in name
  • description: Non-empty, ≤1024 characters
  • description: Third-person voice (not "I can" or "You can")
  • description: Includes what it does AND when to trigger
  • description: Contains specific trigger phrases
Phase 5: Description Quality

The description is the triggering mechanism. Evaluate:

Good descriptions include:

  • Specific actions: "Extract text and tables from PDF files"
  • Trigger phrases: "Use when analyzing Excel files, spreadsheets, or .xlsx"
  • Synonyms users might say: "tabular data, CSV, workbooks"

Bad descriptions:

  • Vague: "Helps with documents"
  • Generic: "Processes data"
  • Missing triggers: "Analyzes spreadsheets" (no "when to use")
Phase 6: Body Analysis

Review SKILL.md body content:

Length:

  • Under 500 lines (check with wc -l)
  • If longer, split into reference files

Progressive Disclosure:

  • Quick start or overview near top
  • Details moved to references/
  • Long reference files (>100 lines) have TOC

Token Efficiency:

  • No obvious explanations (Claude already knows)
  • Examples over lengthy prose
  • Each line justifies its token cost

Degrees of Freedom:

  • High freedom for context-dependent tasks
  • Low freedom for fragile/error-prone tasks
  • Defaults provided when multiple options exist
Phase 7: Anti-Pattern Check

Scan for common issues:

Anti-PatternLook For
Windows pathsscripts\file.py instead of scripts/file.py
Nested referencesA.md → B.md → C.md chains
Time-sensitive info"If before August 2025..."
Magic numbersUnexplained values
Too many options"You can use X, or Y, or Z..." without default
Inconsistent termsMixing "endpoint"/"URL"/"route"
User-facing docsREADME, CHANGELOG, installation guides
First/second person descriptions"I can help" or "You can use"
Phase 8: Report Findings

Present findings using this format:

## Skill Review: [skill-name]

### Summary
[1-2 sentence overall assessment]

### Structure
[✓/✗] Directory organization
[✓/✗] File presence
[✓/✗] Reference depth

### Frontmatter
[✓/✗] name validation
[✓/✗] description validation

### Description Quality
**Score**: [Strong / Adequate / Needs Work]
**Issues**: [List specific problems]
**Suggested rewrite** (if needed):
```yaml
description: >-
  [Improved description]
Body Analysis

Line count: [X] lines Token efficiency: [Good / Could trim] Progressive disclosure: [✓/✗]

Anti-Patterns Found
  • [Issue 1] — Location: file:line
  • [Issue 2] — Location: file:line
Recommendations
  1. [Actionable fix]
  2. [Actionable fix]

## Quick Review Mode

For rapid validation, run through the checklist in `references/checklist.md` and report only failures.

## Resources

### references/best-practices.md
Comprehensive guide covering architecture, design principles, writing effective descriptions, bundled resources, workflow patterns, and advanced patterns from production skills.

### references/checklist.md
Quick-reference validation checklist for fast reviews.

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