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name: skill-tester description: > Validate and score Claude Code skill packages for quality, completeness, and best-practice compliance. Tests Python scripts, checks YAML frontmatter, and generates reports. Use when creating, validating, or auditing skill packages. license: MIT + Commons Clause metadata: version: 1.1.0 author: borghei category: engineering domain: meta-skills tier: POWERFUL updated: 2026-06-17

Skill Tester

Validate skill packages for structure compliance, test Python scripts for syntax and stdlib-only imports, and score quality across four dimensions (documentation, code quality, completeness, usability) with letter grades and improvement recommendations. Supports BASIC, STANDARD, and POWERFUL tier classification.

Core Capabilities

• Structure validation — check required files, directory layout, YAML frontmatter, and required SKILL.md sections against tier thresholds.
• Script testing — AST syntax checks, stdlib-only import analysis, argparse and __main__-guard detection, runtime --help and sample-data execution.
• Quality scoring — four equally weighted dimensions producing an overall score, letter grade (A+ through F), and a prioritized improvement roadmap.
• Tier classification — BASIC / STANDARD / POWERFUL requirements for SKILL.md depth, script count/LOC, argparse, output formats, and error handling.
• Dual output — human-readable reports and --json for CI/CD gating with meaningful exit codes.

When to Use

• Creating a new skill and validating it before publishing.
• Auditing an existing skill's structure, scripts, and quality.
• Embedding a quality gate into a CI/CD pipeline.

Clarify First

Before validating, confirm these inputs. If any is unknown or vague, ASK — do not assume:

• Target skill path — the skill directory to validate, test, and score (the subject of all three tools)
• Target tier — BASIC / STANDARD / POWERFUL (--tier; sets the required sections, script count, and structural thresholds)
• Pass bar — the minimum quality score / whether failures gate CI (--minimum-score, exit codes)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Quick Start

# Validate skill structure and documentation
python skill_validator.py engineering/my-skill --tier POWERFUL --json

# Test all Python scripts in a skill
python script_tester.py engineering/my-skill --timeout 30

# Score quality with improvement roadmap
python quality_scorer.py engineering/my-skill --detailed --minimum-score 75

Tools

Tool	Purpose	Command
skill_validator.py	Validate structure, frontmatter, required sections, and scripts against tier rules	python scripts/skill_validator.py engineering/my-skill --tier POWERFUL --json
script_tester.py	Static + runtime tests of scripts (syntax, imports, argparse, --help, samples)	python scripts/script_tester.py engineering/my-skill --timeout 60 --json
quality_scorer.py	Score four quality dimensions with letter grade and improvement roadmap	python scripts/quality_scorer.py engineering/my-skill --detailed --minimum-score 75 --json

See references/tool-reference.md for full parameter tables, output formats, and exit codes.

References

Load the reference that matches the task — keep this file lean and pull detail on demand:

• references/workflows-and-cicd.md — the three core validation workflows, the tier-requirements and quality-scoring tables, CI/CD integration, anti-patterns, troubleshooting, and success criteria. Read when running a validation pass or wiring a CI gate.
• references/tool-reference.md — full parameter tables, output formats, and exit codes for the three Python tools. Read when scripting the tools or interpreting JSON output.
• references/skill-structure-specification.md — the authoritative specification for skill directory structure, required files, and frontmatter. Read when defining what "valid structure" means.
• references/tier-requirements-matrix.md — the full BASIC/STANDARD/POWERFUL requirements matrix with detailed criteria per tier. Read when classifying or upgrading a skill's tier.
• references/quality-scoring-rubric.md — the detailed scoring rubric with per-component weights and grading bands. Read when interpreting or tuning quality scores.

Scope & Limitations

Covers:

• Structural validation of skill directories against tier-specific requirements (BASIC, STANDARD, POWERFUL)
• Static analysis of Python scripts including syntax checking, import validation, argparse detection, and main guard verification
• Multi-dimensional quality scoring across documentation, code quality, completeness, and usability
• Dual output formatting (JSON for CI/CD pipelines, human-readable for developer consumption)

Does NOT cover:

• Functional correctness of script logic or algorithm accuracy — the tester verifies structure and conventions, not business logic
• Performance benchmarking or memory profiling of scripts — see engineering/performance-profiler for runtime analysis
• Security vulnerability scanning of script code — see engineering/skill-security-auditor for dependency and code security audits
• Cross-skill dependency resolution or integration testing — skills are validated in isolation without verifying inter-skill compatibility

Integration Points

Skill	Integration	Data Flow
engineering/skill-security-auditor	Run security audit after validation passes	skill_validator.py confirms structure compliance, then skill-security-auditor scans for vulnerabilities in the same skill path
engineering/ci-cd-pipeline-builder	Embed skill-tester as a quality gate stage	Pipeline builder generates workflow YAML that invokes skill_validator.py, script_tester.py, and quality_scorer.py sequentially
engineering/changelog-generator	Feed quality score deltas into changelog entries	Compare quality_scorer.py JSON output between releases to surface quality improvements or regressions
engineering/pr-review-expert	Attach validation report to pull request reviews	skill_validator.py --json output is posted as a PR comment for reviewer context
engineering/performance-profiler	Complement structural testing with runtime profiling	After script_tester.py confirms execution succeeds, performance-profiler measures execution time and resource usage
engineering/tech-debt-tracker	Track quality score trends over time	Periodic quality_scorer.py --json output is ingested to detect score degradation and flag technical debt