Complete AI Training
Sign inBecome a member

Your job's AI kit

Get your AI kit

Tell us who you are and what you do. We show you your kit right away and email you the link: skills, prompts, AI agents, MCP servers and courses for your job.

500+ jobs ready, and we make a kit for any other job. No payment needed to look.

Share

Skill · Development

Skill tester

Validate, test, and score the quality of skills within the claude-skills ecosystem. Comprehensive meta-skill: structure validation, Python script testing (syntax + imports + runtime + output format), multi-dimensional quality scoring with letter grades and tier classification (BASIC/STANDARD/POWERFUL). Use when authoring a new skill, auditing existing skills for tier promotion, setting up pre-commit hooks for skill quality, or integrating skill QA into CI.

Agency SkillsLicense: MITAdded Sep 29, 2026
Use it in my AI

How to use it

  1. Start your plan and connect your AI once
  2. Add the skill to your AI, one time only: press Copy skill and paste it into your AI's instructions: a project in ChatGPT, Claude or Grok, a Gem in Gemini, an agent in Microsoft 365 Copilot, or a rule in Cursor. It stays there for every new chat. In Kimi, paste it at the start of a new chat.
  3. Ask for the task in your own words, or say it directly:
Use the Skill tester skill to help me with this.
SKILL.md19 files in this skill

Skill Tester

Tier: POWERFUL · Category: Engineering Quality Assurance · Dependencies: None (Python stdlib only)

Meta-skill that validates, tests, and scores skills in this repository. Four tools, run from the repo root with full paths:

  1. scripts/skill_validator.py — structure + documentation compliance
  2. scripts/script_tester.py — Python script syntax/imports/runtime/output testing
  3. scripts/quality_scorer.py — multi-dimensional scoring with letter grade
  4. scripts/security_scorer.py — security posture scoring (also available via quality_scorer.py --include-security)
Scope note: this skill's tier line-count minimums measure legacy skills. For authoring new skills, engineering/write-a-skill (SKILL.md under ~100 lines, Matt Pocock doctrine) is the binding standard — do not pad a new skill to satisfy a tier minimum here.

Quick Start (exact, runnable from repo root)

# 1. Validate structure (exit non-zero on failure — usable as a gate)
python3 engineering/skills/skill-tester/scripts/skill_validator.py engineering/skills/self-eval --json

# 2. Test the skill's Python scripts (30s default timeout per script)
python3 engineering/skills/skill-tester/scripts/script_tester.py engineering/skills/self-eval --json

# 3. Score quality (fail CI below threshold with --minimum-score)
python3 engineering/skills/skill-tester/scripts/quality_scorer.py engineering/skills/self-eval --json --detailed --minimum-score 75

Consume the JSON: validator emits overall_score, compliance_level, per-check checks{}; scorer emits overall_score, letter_grade, tier_recommendation, dimensions, and an improvement_roadmap — work the roadmap top-down, then re-run until the target score is met.

For repo-wide auditing prefer scripts/audit_skills.py at the repo root (wraps the write-a-skill checklist runner across all skills).

What Each Tool Checks

skill_validator.py

  • SKILL.md frontmatter parsing, required sections, minimum line counts per tier (--tier BASIC|STANDARD|POWERFUL)
  • Required structure: SKILL.md, README.md, scripts/, references/, assets/, expected_outputs/
  • Python scripts: argparse present, stdlib-only imports

script_tester.py

  • AST-based syntax validation; import analysis (flags external dependencies)
  • Controlled execution with timeout protection (--timeout, default 30s)
  • --help functionality verification; sample-data runs compared against expected_outputs/

quality_scorer.py

Four dimensions, 25% each: Documentation (depth, examples, references), Code Quality (complexity, error handling, output consistency), Completeness (required dirs, sample data, expected outputs), Usability (help text, example clarity). Outputs 0-100 + A-F grade + tier recommendation.

Tier Classification

TierSKILL.mdScriptsCLI surface
BASIC≥ 100 lines1 (100-300 LOC)basic argparse
STANDARD≥ 200 lines1-2 (300-500 LOC)subcommands, JSON + text output
POWERFUL≥ 300 lines2-3 (500-800 LOC)multiple modes, CI integration

(Advisory for legacy skills; new skills follow write-a-skill — see scope note above.)

CI Integration

# GitHub Actions: gate changed skills
- name: "validate-changed-skills"
  run: |
    for skill in $changed_skills; do
      python3 engineering/skills/skill-tester/scripts/skill_validator.py "$skill" --json
      python3 engineering/skills/skill-tester/scripts/script_tester.py "$skill"
      python3 engineering/skills/skill-tester/scripts/quality_scorer.py "$skill" --minimum-score 75
    done

Pre-commit hook: run the validator on the staged skill directory and block the commit on non-zero exit.

Verification Loop

A skill "passes" when, in one run from repo root:

  1. skill_validator.py <skill> --json exits 0,
  2. script_tester.py <skill> reports all scripts passing, and
  3. quality_scorer.py <skill> --minimum-score <target> exits 0.

If any step fails, apply the top improvement_roadmap item and re-run all three — never report a partial pass.

Troubleshooting

  • Timeout errors → raise --timeout or optimize the script under test
  • Import failures → external deps detected; stdlib-only is the repo policy
  • Tier misclassification → check line counts/LOC against the tier table; remember the write-a-skill exception for new skills

References: references/ holds the structure specification, tier requirements matrix, and scoring rubric the tools implement.