skills/galaxy-dawn/claude-scholar/skill-quality-reviewer

skill-quality-reviewer

SKILL.md

Skill Quality Reviewer

Overview

A meta-skill for evaluating the quality of Claude Skills. Perform comprehensive analysis across four key dimensions—description quality (25%), content organization (30%), writing style (20%), and structural integrity (25%)—to generate weighted scores, letter grades, and actionable improvement plans.

Use this skill to validate skills before sharing, identify improvement opportunities, or ensure compliance with skill development best practices.

When to Use This Skill

Invoke this skill when:

  • Analyzing a skill's quality before distribution
  • Reviewing skill documentation for best practices
  • Evaluating adherence to skill development standards
  • Generating improvement recommendations for existing skills
  • Validating skill structure and completeness

Trigger phrases:

  • "Analyze skill quality for ./my-skill"
  • "Evaluate this skill: ~/.claude/skills/api-helper"
  • "Review skill quality of git-workflow"
  • "Check my skill for best practices"
  • "Generate quality report for this skill"

Analysis Workflow

Step 1: Load the Skill

Accept skill path as input. Verify the path exists and contains SKILL.md. Read the complete skill directory structure.

# Example invocation
ls -la ~/.claude/skills/target-skill/

Validate:

  • SKILL.md exists
  • Directory is readable
  • Path points to a valid skill

Step 2: Parse YAML Frontmatter

Extract and validate the YAML frontmatter from SKILL.md.

Required fields:

  • name - Skill identifier
  • description - Trigger description with phrases

Check for:

  • Valid YAML syntax
  • No prohibited fields
  • Proper formatting

Step 3: Evaluate Description Quality (25%)

Assess the quality and effectiveness of the frontmatter description.

Scoring breakdown:

Criterion Points Evaluation
Trigger phrases clarity 25 3-5 specific user phrases present
Third-person format 25 Uses "This skill should be used when..."
Description length 25 100-300 characters optimal
Specific scenarios 25 Concrete use cases, not vague

Red flags:

  • Vague triggers like "helps with tasks"
  • Second-person descriptions ("Use this when you...")
  • Missing or generic descriptions
  • No actionable trigger phrases

Reference: references/examples-good.md for exemplary descriptions

Step 4: Evaluate Content Organization (30%)

Assess adherence to progressive disclosure principles.

Scoring breakdown:

Criterion Points Evaluation
Progressive disclosure 30 SKILL.md lean, details in references/
SKILL.md length 25 Under 5,000 words (1,500-2,000 ideal)
References/ usage 25 Detailed content properly moved
Logical organization 20 Clear sections, good flow

Check:

  • SKILL.md body is concise and focused
  • Detailed content moved to references/
  • Examples and templates in appropriate directories
  • No information duplication across files

Reference: references/scoring-criteria.md for detailed rubrics

Step 5: Evaluate Writing Style (20%)

Verify adherence to skill writing conventions.

Scoring breakdown:

Criterion Points Evaluation
Imperative form 40 Verb-first instructions throughout
No second person 30 Avoids "you", "your", "should"
Objective language 30 Factual, instructional tone

Check for:

  • Imperative verbs: "Create the file", "Validate input", "Check structure"
  • Absence of: "You should", "You can", "You need to"
  • Objective, instructional language
  • Consistent style throughout

Good examples:

Create the skill directory structure.
Validate the YAML frontmatter.
Check for required fields.

Bad examples:

You should create the directory.
You need to validate the frontmatter.
Check if the fields are there.

Step 6: Evaluate Structural Integrity (25%)

Verify the skill's physical structure and completeness.

Scoring breakdown:

Criterion Points Evaluation
YAML frontmatter 30 All required fields present
Directory structure 30 Proper organization
Resource references 40 All referenced files exist

Validate:

  • YAML frontmatter contains name and description
  • Directory structure follows conventions:
    skill-name/
    ├── SKILL.md
    ├── references/ (optional)
    ├── examples/ (optional)
    └── scripts/ (optional)
    
  • All files referenced in SKILL.md actually exist
  • Examples are complete and working
  • Scripts are executable

Step 7: Calculate Weighted Score

Compute the overall quality score using weighted dimensions.

Formula:

Overall Score = (Description × 0.25) + (Organization × 0.30) +
                (Style × 0.20) + (Structure × 0.25)

Letter grade mapping:

Score Range Grade Meaning
97-100 A+ Exemplary
93-96 A Excellent
90-92 A- Very Good
87-89 B+ Good
83-86 B Above Average
80-82 B- Solid
77-79 C+ Acceptable
73-76 C Satisfactory
70-72 C- Minimal Acceptable
67-69 D+ Below Standard
63-66 D Poor
60-62 D- Very Poor
0-59 F Fail

Step 8: Generate Reports

Create two output documents in the current working directory.

1. Quality Report (quality-report-{skill-name}.md)

  • Executive summary with overall score and grade
  • Dimension-by-dimension breakdown
  • Strengths and weaknesses for each dimension
  • Grade breakdown table
  • Link to improvement plan

2. Improvement Plan (improvement-plan-{skill-name}.md)

  • Prioritized improvement list (High/Medium/Low)
  • Specific file locations and line numbers for issues
  • Current vs. suggested content comparisons
  • Estimated impact on scores
  • Time estimates for fixes
  • Expected score improvement

Output Templates

Quality Report Template

# Skill Quality Report: {skill-name}

## Executive Summary
- **Overall Score**: X/100 ({Grade})
- **Evaluated**: {Date}
- **Skill Path**: {path}

## Dimension Scores

### 1. Description Quality (25%)
**Score**: X/100

**Strengths**:
- ✅ {specific strength}

**Weaknesses**:
- ❌ {specific weakness}

**Recommendations**:
1. {actionable recommendation}

[Repeat for other dimensions...]

## Grade Breakdown
| Dimension | Score | Weight | Contribution |
|-----------|-------|--------|--------------|
| Description | X/100 | 25% | X.X |
| Organization | X/100 | 30% | X.X |
| Style | X/100 | 20% | X.X |
| Structure | X/100 | 25% | X.X |
| **Overall** | **X/100** | **100%** | **X.X ({Grade})** |

## Next Steps
See `improvement-plan-{skill-name}.md` for detailed improvement suggestions.

Improvement Plan Template

# Skill Improvement Plan: {skill-name}

## Priority Summary
- **High Priority**: {count} items
- **Medium Priority**: {count} items
- **Low Priority**: {count} items

## High Priority Improvements

### 1. [Issue Title]
**File**: SKILL.md:line:line
**Dimension**: Description Quality
**Impact**: +X points

**Current**:
```yaml
{current content}

Suggested:

{suggested content}

Reason: {why this improves quality}

[Continue with all issues...]

Quick Wins (Easy Fixes)

  1. {quick fix}
  2. {quick fix}

Estimated Time to Complete

  • High Priority: X hours
  • Medium Priority: X hours
  • Low Priority: X hours
  • Total: X hours

Expected Score Improvement

  • Current: X/100 ({Grade})
  • After High Priority: X/100 ({Grade})
  • After All: X/100 ({Grade})

## Additional Resources

### Reference Files

For detailed evaluation criteria and examples, consult:

- **`references/scoring-criteria.md`** - Comprehensive scoring rubrics for each dimension
- **`references/examples-good.md`** - Exemplary skills demonstrating best practices
- **`references/examples-bad.md`** - Common anti-patterns to avoid

### Scripts

- **`scripts/extract-yaml.sh`** - Utility for extracting YAML frontmatter from SKILL.md

### Related Skills

- **`skill-development`** - Comprehensive guide for creating skills
- **`code-review-excellence`** - Best practices for code review

## Best Practices

### When Analyzing Skills

1. **Be objective and specific** - Base scores on observable criteria, not opinions
2. **Provide actionable feedback** - Each recommendation should be concrete and implementable
3. **Include examples** - Show current vs. suggested content for clarity
4. **Estimate impact** - Help users understand which changes matter most
5. **Be constructive** - Frame feedback as opportunities for improvement

### Common Quality Issues

**Description Quality:**
- Vague or generic trigger phrases
- Second-person descriptions
- Missing concrete use cases

**Content Organization:**
- SKILL.md too long (>5,000 words)
- Detailed content not moved to references/
- Poor information hierarchy

**Writing Style:**
- Second-person language ("you", "your")
- Mixed imperative and descriptive styles
- Subjective or conversational tone

**Structural Integrity:**
- Missing required YAML fields
- Referenced files don't exist
- Incomplete examples or broken scripts

### Grade Benchmarks

**A grade (90-100)**: Exemplary skills serving as templates for others
- All dimensions score 85+
- Clear, specific descriptions
- Excellent progressive disclosure
- Consistent imperative style
- Complete, well-organized structure

**B grade (80-89)**: High-quality skills with minor improvements needed
- Most dimensions score 75+
- Good descriptions and organization
- Generally follows best practices
- May have minor style inconsistencies

**C grade (70-79)**: Acceptable skills requiring moderate improvements
- Key areas meet minimum standards
- Some weaknesses in organization or style
- Functional but not exemplary

**D/F grade (below 70)**: Skills needing significant work
- Multiple dimensions below 70
- Major structural or style issues
- Requires comprehensive revision

## Usage Examples

**Example 1: Analyze a local skill**

User: "Analyze skill quality for ~/.claude/skills/git-workflow"

[Claude executes the 8-step workflow and generates:]

  • quality-report-git-workflow.md
  • improvement-plan-git-workflow.md

**Example 2: Review before sharing**

User: "Review my new skill before I publish it"

[Claude analyzes the skill and provides:]

  • Detailed quality assessment
  • Specific improvement recommendations
  • Expected score after implementing fixes

**Example 3: Quality check for existing skill**

User: "Check skill quality of api-helper"

[Claude evaluates and reports:]

  • Current grade and score
  • Top improvement opportunities
  • Quick wins for easy score gains
Weekly Installs
19
GitHub Stars
1.4K
First Seen
Feb 23, 2026
Installed on
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