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skill-checker

验证、审查并根据Anthropic官方最佳实践《构建Claude技能完整指南》改进Claude技能。当用户说'检查我的技能'、'审查这个技能'、'验证我的SKILL.md'、'我的技能好吗'、'技能审核'、'技能审查'、'校对我的技能'、'给我的技能打分',或者上传一个技能文件夹或SKILL.md以获取反馈时使用。此外,当用户提到技能质量、技能触发问题、技能调试,或希望在发布或分享前确保技能遵循Anthropic的官方指南时也应触发。

person作者: jakexiaohubgithub

Skill Checker

A comprehensive skill validation and review tool based on Anthropic's official "Complete Guide to Building Skills for Claude." This skill runs a multi-dimensional audit on any skill folder or SKILL.md and produces an actionable scorecard with specific fix recommendations.

When to use

Run this skill whenever a user:

  • Uploads or references a skill they want reviewed
  • Asks "is this skill good?" or "check my skill"
  • Wants to validate before publishing/distributing
  • Is debugging triggering, execution, or quality issues
  • Wants to improve an existing skill

How it works

The review runs in three phases:

  1. Structural validation — file naming, folder layout, YAML correctness
  2. Content quality audit — description effectiveness, instruction clarity, progressive disclosure, patterns used
  3. Scorecard & recommendations — graded rubric across all dimensions with prioritized fixes

Phase 1: Structural Validation

Read the skill folder and check every item below. Report pass/fail for each.

1.1 File & Folder Naming

  • [ ] Folder name uses kebab-case (e.g., my-cool-skill)
  • [ ] No spaces in folder name
  • [ ] No underscores in folder name
  • [ ] No capital letters in folder name
  • [ ] Folder name does NOT contain "claude" or "anthropic" (reserved)
  • [ ] Main file is exactly SKILL.md (case-sensitive — not skill.md, SKILL.MD, etc.)
  • [ ] No README.md inside the skill folder (all docs belong in SKILL.md or references/)

1.2 YAML Frontmatter

  • [ ] Frontmatter is delimited by --- on both the opening and closing lines
  • [ ] name field is present
  • [ ] name field uses kebab-case, no spaces, no capitals
  • [ ] name field matches the folder name
  • [ ] description field is present
  • [ ] description is under 1024 characters
  • [ ] No XML angle brackets (< or >) anywhere in frontmatter (security restriction)
  • [ ] No unclosed quotes in YAML values
  • [ ] Optional fields (if present) are valid:
    • license: recognized license identifier (e.g., MIT, Apache-2.0)
    • compatibility: 1–500 characters, describes environment requirements
    • metadata: valid key-value pairs (suggested: author, version, mcp-server)

1.3 Folder Structure

  • [ ] Contains SKILL.md at root (required)
  • [ ] Optional directories follow convention: scripts/, references/, assets/
  • [ ] No unexpected top-level files that should be in subdirectories
  • [ ] If scripts/ exists, files are executable code (Python, Bash, etc.)
  • [ ] If references/ exists, files are documentation (.md, .txt, etc.)
  • [ ] If assets/ exists, files are templates, fonts, icons, etc.

Phase 2: Content Quality Audit

2.1 Description Field (Critical — this is the primary triggering mechanism)

The description must answer two questions: WHAT the skill does and WHEN to use it.

Check for:

  • [ ] Describes what the skill does (capability)
  • [ ] Describes when to use it (trigger conditions / user phrases)
  • [ ] Includes specific trigger phrases users would actually say
  • [ ] Mentions relevant file types if applicable
  • [ ] Is specific enough to avoid over-triggering on unrelated queries
  • [ ] Is broad enough to trigger on paraphrased requests (not just one exact phrase)
  • [ ] Includes negative triggers if there's risk of confusion with other skills (e.g., "Do NOT use for simple data exploration")

Grade the description:

  • Excellent: Specific, actionable, includes 3+ trigger phrases, mentions file types, clear scope
  • Good: Answers WHAT and WHEN, has trigger phrases, reasonable scope
  • Needs work: Vague ("Helps with projects"), missing triggers, too generic, or too technical without user-facing language
  • Failing: Missing entirely, one-word, or no trigger conditions

Red flags:

  • "Helps with X" without specifying what the user would say
  • Pure technical description with no user-facing trigger phrases
  • Overloaded description trying to cover too many unrelated things

2.2 Progressive Disclosure

Skills should use a three-level loading system to minimize token usage:

  • Level 1 — YAML frontmatter (~100 words): Always in context. Just enough for Claude to decide when to use it.
  • Level 2 — SKILL.md body (<500 lines ideal): Loaded when the skill triggers. Contains full instructions.
  • Level 3 — Linked files (references/, scripts/, assets/): Loaded only as needed.

Check for:

  • [ ] SKILL.md body is under 500 lines (ideal) or has clear hierarchy with pointers if longer
  • [ ] Detailed documentation is in references/, not inline in SKILL.md
  • [ ] SKILL.md references external files clearly with guidance on WHEN to read them
  • [ ] Large reference files (>300 lines) include a table of contents
  • [ ] Domain-specific variants are organized into separate reference files (e.g., references/aws.md, references/gcp.md) rather than all inlined

Grade:

  • Excellent: Clean separation across all three levels, SKILL.md is lean, references are well-organized
  • Good: Reasonable separation, maybe a bit long but manageable
  • Needs work: Everything crammed into SKILL.md, no use of references/
  • Failing: SKILL.md is 1000+ lines with no external files, or instructions are buried and hard to find

2.3 Instruction Quality

Check for clarity and actionability:

  • [ ] Instructions use imperative form ("Run X", "Check Y" — not "You might want to consider running X")
  • [ ] Critical instructions appear at the top, not buried deep
  • [ ] Steps are numbered and sequenced when order matters
  • [ ] Specific commands/scripts are given, not vague ("validate the data" → "Run python scripts/validate.py --input {filename}")
  • [ ] Error handling is included (what to do when things go wrong)
  • [ ] Examples are provided for common scenarios
  • [ ] Explains the why behind instructions, not just the what (this helps the model generalize)
  • [ ] Avoids excessive ALWAYS/NEVER/MUST in all-caps (reframe as reasoning when possible)
  • [ ] Output format is defined (template, structure, or example of expected result)

Check for composability:

  • [ ] Skill works well alongside other skills (doesn't assume it's the only capability)
  • [ ] No conflicts with common built-in Claude capabilities

Check for portability:

  • [ ] Works across Claude.ai, Claude Code, and API without modification
  • [ ] Any environment-specific dependencies are noted in compatibility field

2.4 Workflow Pattern Assessment

Identify which pattern(s) the skill uses and whether it applies them well:

Pattern 1: Sequential Workflow Orchestration

  • Explicit step ordering with dependencies between steps
  • Validation at each stage
  • Rollback instructions for failures

Pattern 2: Multi-MCP Coordination

  • Clear phase separation between different MCP services
  • Data passing between MCPs is documented
  • Validation before moving to next phase
  • Centralized error handling

Pattern 3: Iterative Refinement

  • Explicit quality criteria defined
  • Validation scripts or checks between iterations
  • Clear stopping criteria (when to stop iterating)

Pattern 4: Context-Aware Tool Selection

  • Clear decision criteria for choosing between tools
  • Fallback options documented
  • Transparency about choices (tells user why a path was chosen)

Pattern 5: Domain-Specific Intelligence

  • Domain expertise embedded in logic (not just tool access)
  • Compliance/governance checks before action
  • Comprehensive audit trail / documentation

Grade the pattern usage:

  • Excellent: Pattern is clearly identified and well-executed, with validation gates and error handling
  • Good: Pattern is present and functional, minor gaps
  • Needs work: Pattern is implicit or incomplete
  • N/A: Skill is simple enough that no formal pattern is needed

2.5 Use Case Definition

  • [ ] 2–3 concrete use cases are identifiable from the skill
  • [ ] Each use case has a clear trigger, steps, and expected result
  • [ ] Edge cases are addressed
  • [ ] Success criteria are defined (even if qualitative)

2.6 Category Classification

Classify the skill into one of the three standard categories:

  1. Document & Asset Creation — consistent output (docs, presentations, code, designs)
  2. Workflow Automation — multi-step processes with methodology
  3. MCP Enhancement — workflow guidance on top of MCP tool access

Note: Skills can span categories. Identify the primary and any secondary categories.


Phase 3: Scorecard & Recommendations

Scoring Rubric

Score each dimension 1–5:

| Dimension | 1 (Failing) | 3 (Adequate) | 5 (Excellent) | |---|---|---|---| | Structure | Missing SKILL.md or broken YAML | Valid structure, minor issues | Perfect folder layout, all conventions followed | | Description | Missing or vague | Answers WHAT and WHEN | Specific triggers, file types, negative triggers, pushiness | | Progressive Disclosure | Everything in one giant file | Some separation | Clean 3-level hierarchy, lean SKILL.md | | Instruction Clarity | Vague, no examples | Clear steps, some examples | Imperative, examples, error handling, explains WHY | | Error Handling | None | Basic error messages | Comprehensive troubleshooting, rollback, common issues | | Composability | Conflicts with other skills | Works in isolation | Explicitly designed for multi-skill environments | | Testing Readiness | No testable outputs | Some verifiable outputs | Clear success criteria, assertions possible |

Output Format

Present the results as:

# Skill Review: [skill-name]

## Overall Score: X/35 ([rating])

### Structural Validation
✅ / ❌ [each check with pass/fail]

### Content Quality
| Dimension | Score | Notes |
|---|---|---|
| Description | X/5 | [specific feedback] |
| Progressive Disclosure | X/5 | [specific feedback] |
| Instruction Clarity | X/5 | [specific feedback] |
| Error Handling | X/5 | [specific feedback] |
| Composability | X/5 | [specific feedback] |
| Testing Readiness | X/5 | [specific feedback] |

### Pattern Analysis
Primary pattern: [pattern name]
Pattern execution: [grade]

### Category
Primary: [category]
Secondary: [category, if applicable]

### Top 3 Fixes (Prioritized)
1. **[Priority: High/Medium/Low]** — [specific, actionable fix]
2. **[Priority: High/Medium/Low]** — [specific, actionable fix]
3. **[Priority: High/Medium/Low]** — [specific, actionable fix]

### Description Rewrite (if score < 4)
Suggested improved description:
[rewritten description]

Rating Scale

  • 30–35: Production-ready. Minor polish only.
  • 22–29: Good foundation. Address the top fixes and it's ready.
  • 15–21: Needs significant work. Focus on structural and description issues first.
  • Below 15: Fundamental rework needed. Start with the Fundamentals chapter of the guide.

Quick-Check Mode

If the user just wants a fast pass (e.g., "quick check my skill"), skip the full audit and run only:

  1. YAML frontmatter validation (all required fields, no forbidden content)
  2. Description quality check (WHAT + WHEN + trigger phrases)
  3. Top 3 issues with fixes

This should take under 2 minutes and give the user enough to act on immediately.


Validation Script

If the skill folder is available on the filesystem, run the automated structural checks:

python scripts/validate_skill.py <path-to-skill-folder>

This script checks file naming, YAML parsing, folder structure, description length, and forbidden content. It outputs a JSON report that feeds into the scorecard.


Troubleshooting Common Issues (Reference for Reviewer)

Skill won't upload

  • File not named exactly SKILL.md
  • YAML missing --- delimiters
  • Unclosed quotes in YAML
  • Name has spaces or capitals

Skill doesn't trigger

  • Description too generic ("Helps with projects")
  • Missing trigger phrases
  • Missing relevant file type mentions
  • Test: Ask Claude "When would you use the [skill name] skill?" — if Claude can't answer clearly, the description needs work

Skill triggers too often

  • Add negative triggers ("Do NOT use for...")
  • Be more specific about scope
  • Clarify what adjacent skills handle instead

Instructions not followed

  • Instructions too verbose (keep SKILL.md lean)
  • Critical instructions buried deep (move them up)
  • Ambiguous language ("process appropriately" → give explicit steps)
  • Missing explanation of WHY (model can't generalize without reasoning)
  • Consider bundling validation scripts for critical checks (code is deterministic; language isn't)

Performance/context issues

  • SKILL.md over 500 lines without progressive disclosure
  • Too many skills enabled simultaneously (>20–50)
  • All content loaded inline instead of referenced