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skill-evaluator

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SKILL.md
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Skill Evaluator (WIP)

Evaluates skills against Anthropic's official best practices for agent skill authoring. Produces structured evaluation reports with scores and actionable recommendations.

Quick Start

  1. Read the skill's SKILL.md and understand its purpose
  2. Run automated validation: scripts/validate_skill.py <skill-path>
  3. Perform manual evaluation against criteria below
  4. Generate evaluation report with scores and recommendations

Evaluation Workflow

Step 1: Automated Validation

Run the validation script first:

scripts/validate_skill.py <path/to/skill>

This checks:

  • SKILL.md exists with valid YAML frontmatter
  • Name follows conventions (lowercase, hyphens, max 64 chars)
  • Description is present and under 1024 chars
  • Body is under 500 lines
  • File references are one-level deep

Step 2: Manual Evaluation

Evaluate each dimension and assign a score (1-5):

A. Naming (Weight: 10%)

ScoreCriteria
5Gerund form (-ing), clear purpose, memorable
4Descriptive, follows conventions
3Acceptable but could be clearer
2Vague or misleading
1Violates naming rules

Rules: Max 64 chars, lowercase + numbers + hyphens only, no reserved words (anthropic, claude), no XML tags.

Good: processing-pdfs, analyzing-spreadsheets, building-dashboards Bad: pdf, my-skill, ClaudeHelper, anthropic-tools

B. Description (Weight: 20%)

ScoreCriteria
5Clear functionality + specific activation triggers + third person
4Good description with some triggers
3Adequate but missing triggers or vague
2Too brief or unclear purpose
1Missing or unhelpful

Must include: What the skill does AND when to use it. Good: "Extracts text from PDFs. Use when working with PDF documents for text extraction, form parsing, or content analysis." Bad: "A skill for PDFs." or "Helps with documents."

C. Content Quality (Weight: 30%)

ScoreCriteria
5Concise, assumes Claude intelligence, actionable instructions
4Generally good, minor verbosity
3Some unnecessary explanations or redundancy
2Overly verbose or confusing
1Bloated, explains obvious concepts

Ask: "Does Claude really need this explanation?" Remove anything Claude already knows.

D. Structure & Organization (Weight: 25%)

ScoreCriteria
5Excellent progressive disclosure, clear navigation, optimal length
4Good organization, appropriate file splits
3Acceptable but could be better organized
2Poor organization, missing references, or bloated SKILL.md
1No structure, everything dumped in SKILL.md

Check:

  • SKILL.md under 500 lines
  • References are one-level deep (no nested chains)
  • Long reference files (>100 lines) have table of contents
  • Uses forward slashes in all paths

E. Degrees of Freedom (Weight: 10%)

ScoreCriteria
5Perfect match: high freedom for flexible tasks, low for fragile operations
4Generally appropriate freedom levels
3Acceptable but could be better calibrated
2Mismatched: too rigid or too loose
1Completely wrong freedom level for the task type

Guideline:

  • High freedom (text): Multiple valid approaches, context-dependent
  • Medium freedom (parameterized): Preferred pattern exists, some variation OK
  • Low freedom (specific scripts): Fragile operations, exact sequence required

F. Anti-Pattern Check (Weight: 5%)

Deduct points for each anti-pattern found:

  • Too many options without clear recommendation (-1)
  • Time-sensitive information with date conditionals (-1)
  • Inconsistent terminology (-1)
  • Windows-style paths (backslashes) (-1)
  • Deeply nested references (more than one level) (-2)
  • Scripts that punt error handling to Claude (-1)
  • Magic numbers without justification (-1)

Step 3: Generate Report

Use this template:

# Skill Evaluation Report: [skill-name]

## Summary
- **Overall Score**: X.X/5.0
- **Recommendation**: [Ready for publication / Needs minor improvements / Needs major revision]

## Dimension Scores
| Dimension | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| Naming | X/5 | 10% | X.XX |
| Description | X/5 | 20% | X.XX |
| Content Quality | X/5 | 30% | X.XX |
| Structure | X/5 | 25% | X.XX |
| Degrees of Freedom | X/5 | 10% | X.XX |
| Anti-Patterns | X/5 | 5% | X.XX |
| **Total** | | 100% | **X.XX** |

## Strengths
- [List 2-3 things done well]

## Areas for Improvement
- [List specific issues with actionable fixes]

## Anti-Patterns Found
- [List any anti-patterns detected]

## Recommendations
1. [Priority 1 fix]
2. [Priority 2 fix]
3. [Priority 3 fix]

## Pre-Publication Checklist
- [ ] Description is specific with activation triggers
- [ ] SKILL.md under 500 lines
- [ ] One-level-deep file references
- [ ] Forward slashes in all paths
- [ ] No time-sensitive information
- [ ] Consistent terminology
- [ ] Concrete examples provided
- [ ] Scripts handle errors explicitly
- [ ] All configuration values justified
- [ ] Required packages listed
- [ ] Tested with Haiku, Sonnet, Opus

Score Interpretation

Score RangeRatingAction
4.5 - 5.0ExcellentReady for publication
4.0 - 4.4GoodMinor improvements recommended
3.0 - 3.9AcceptableSeveral improvements needed
2.0 - 2.9Needs WorkMajor revision required
1.0 - 1.9PoorFundamental redesign needed

References

Examples

See evaluations/ for example evaluation scenarios.

Source

git clone https://github.com/gotalab/skillport/blob/main/.skills/experimental/skill-evaluator/SKILL.mdView on GitHub

Overview

The Skill Evaluator audits a skill’s SKILL.md against Anthropic’s best-practice criteria, producing structured evaluation reports with scores and actionable recommendations. It analyzes naming, description quality, content organization, and potential anti-patterns to guide quality improvements. This helps teams maintain consistent, high-quality skill documentation and behavior.

How This Skill Works

It reads the skill’s SKILL.md, runs automated validation (per the referenced validation script), and then performs a manual evaluation across labeled dimensions (A–E) with weighted scores. The output is a formal evaluation report that includes scores and concrete recommendations for improvement.

When to Use It

  • When asked to review or audit a skill for quality and correctness
  • When validating that SKILL.md follows naming, structure, and length conventions
  • When identifying anti-patterns and improvement opportunities
  • When preparing formal evaluation reports with scores and recommendations
  • When ensuring references are one-level deep and total lines adhere to limits

Quick Start

  1. Step 1: Read the skill's SKILL.md and understand its purpose
  2. Step 2: Run automated validation: scripts/validate_skill.py <path/to/skill>
  3. Step 3: Perform manual evaluation against criteria below and generate the report

Best Practices

  • Run automated validation (scripts/validate_skill.py) before starting manual review
  • Enforce naming conventions: lowercase, hyphens, max 64 chars, avoid reserved words
  • Ensure the description explains what the skill does and when to use it (activation triggers)
  • Keep SKILL.md under 500 lines; ensure references are one-level deep; add a TOC if long
  • Provide clear scores and actionable recommendations in the evaluation report

Example Use Cases

  • Audited 'data-cleaning-scripts' skill; corrected naming, enhanced description triggers, and added TOC for long references
  • Validated 'report-generator' skill; trimmed content to fit limits and clarified when to use
  • Reviewed 'csv-analytics' skill; replaced vague wording with explicit actions and outcomes
  • Assessed 'quiz-generator' skill; ensured path references are safe and consolidated references to one level
  • Evaluated 'monitoring-dashboards' skill; produced actionable recommendations to improve structure and reduce redundancy

Frequently Asked Questions

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