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skills-eval

npx machina-cli add skill athola/claude-night-market/skills-eval --openclaw
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SKILL.md
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Skills Evaluation and Improvement

Table of Contents

  1. Overview
  2. Quick Start
  3. Evaluation Workflow
  4. Evaluation and Optimization
  5. Resources

Overview

This framework audits Claude skills against quality standards to improve performance and reduce token consumption. Automated tools analyze skill structure, measure context usage, and identify specific technical improvements. Run verification commands after each audit to confirm fixes work correctly.

The skills-auditor provides structural analysis, while the improvement-suggester ranks fixes by impact. Compliance is verified through the compliance-checker. Runtime efficiency is monitored by tool-performance-analyzer and token-usage-tracker.

Quick Start

Basic Audit

Run a full audit of all skills or target a specific file to identify structural issues.

# Audit all skills
make audit-all

# Audit specific skill
make audit-skill TARGET=path/to/skill/SKILL.md

Analysis and Optimization

Use skill_analyzer.py for complexity checks and token_estimator.py to verify the context budget.

make analyze-skill TARGET=path/to/skill/SKILL.md
make estimate-tokens TARGET=path/to/skill/SKILL.md

Improvements

Generate a prioritized plan and verify standards compliance using improvement_suggester.py and compliance_checker.py.

make improve-skill TARGET=path/to/skill/SKILL.md
make check-compliance TARGET=path/to/skill/SKILL.md

Evaluation Workflow

Start with make audit-all to inventory skills and identify high-priority targets. For each skill requiring attention, run analysis with analyze-skill to map complexity. Generate an improvement plan, apply fixes, and run check-compliance to verify the skill meets project standards. Finalize by checking the token budget for efficiency.

Evaluation and Optimization

Quality assessments use the skills-auditor and improvement-suggester to generate detailed reports. Performance analysis focuses on token efficiency through the token-usage-tracker and tool performance via tool-performance-analyzer. For standards compliance, the compliance-checker automates common fixes for structural issues.

Scoring and Prioritization

We evaluate skills across five dimensions: structure compliance, content quality, token efficiency, activation reliability, and tool integration. Scores above 90 represent production-ready skills, while scores below 50 indicate critical issues requiring immediate attention.

Improvements are prioritized by impact. Critical issues include security vulnerabilities or broken functionality. High-priority items cover structural flaws that hinder discoverability. Medium and low priorities focus on best practices and minor optimizations.

Structural Patterns

Deprecated: skills/shared/modules/ directories. Shared modules must be relocated into the consuming skill's own modules/ directory. The evaluator flags any remaining skills/shared/ as a structural warning.

Current: Each skill owns its modules at skills/<skill-name>/modules/. Cross-skill references use relative paths (e.g., ../skill-authoring/modules/anti-rationalization.md).

Resources

Shared Modules: Cross-Skill Patterns

Skill-Specific Modules

  • Trigger Isolation Analysis: See modules/trigger-isolation-analysis.md
  • Skill Authoring Best Practices: See modules/skill-authoring-best-practices.md
  • Authoring Checklist: See modules/authoring-checklist.md
  • Evaluation Workflows: See modules/evaluation-workflows.md
  • Quality Metrics: See modules/quality-metrics.md
  • Advanced Tool Use Analysis: See modules/advanced-tool-use-analysis.md
  • Evaluation Framework: See modules/evaluation-framework.md
  • Integration Patterns: See modules/integration.md
  • Troubleshooting: See modules/troubleshooting.md
  • Pressure Testing: See modules/pressure-testing.md
  • Integration Testing: See modules/integration-testing.md
  • Multi-Metric Evaluation: See modules/multi-metric-evaluation-methodology.md
  • Performance Benchmarking: See modules/performance-benchmarking.md

Tools and Automation

  • Tools: Executable analysis utilities in scripts/ directory.
  • Automation: Setup and validation scripts in scripts/automation/.

Source

git clone https://github.com/athola/claude-night-market/blob/master/plugins/abstract/skills/skills-eval/SKILL.mdView on GitHub

Overview

Skills-eval audits Claude skills against established quality standards to improve performance and reduce token consumption. It leverages automated tools to assess structure, metadata quality, token efficiency, and tool integration, guiding improvement planning before production.

How This Skill Works

Run an audit (make audit-all or make audit-skill) with skills-auditor to map structure and context usage. The improvement-suggester ranks fixes by impact, while compliance-checker and token-usage-tracker verify changes and monitor runtime efficiency, culminating in a production-ready skill.

When to Use It

  • Reviewing skill quality during QA or pre-release
  • Preparing skills for production and shipping
  • Auditing existing skills to identify token waste and performance gaps
  • Generating improvement plans and validation for modular-design or integration tests
  • Compliance reporting and performance benchmarking

Quick Start

  1. Step 1: Run a full audit with make audit-all or audit-skill TARGET=path/to/skill/SKILL.md
  2. Step 2: Analyze complexity and estimate tokens with make analyze-skill TARGET=path/to/skill/SKILL.md and make estimate-tokens TARGET=path/to/skill/SKILL.md
  3. Step 3: Generate an improvement plan and verify with make improve-skill TARGET=path/to/skill/SKILL.md and make check-compliance TARGET=path/to/skill/SKILL.md

Best Practices

  • Run a full audit with make audit-all before any release
  • Use analyze-skill and estimate-tokens to understand complexity and token budgets
  • Prioritize fixes with improvement-suggester based on impact
  • Verify fixes with check-compliance and token-usage-tracker
  • Re-audit and document results, including performance metrics

Example Use Cases

  • Audited a large Claude skill and cut token usage by reorganizing context and modularizing prompts.
  • Applied top fixes from improvement-suggester and achieved higher structure compliance.
  • Validated integration with tools and SDK using the compliance-checker.
  • Generated a compliance report and fixed structural issues flagged by the auditor.
  • Benchmarked performance with tool-performance-analyzer and token-usage-tracker after fixes.

Frequently Asked Questions

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