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Agent Skill Infrastructure

Quality tools for Agent Skills. Not a marketplace. Not a platform. A testing and scoring toolkit that works wherever you do.

CI PyPI Python 3.12+ License: MIT


What It Is

Three modules. One toolkit. From local CLI to automated CI.

skill-quality    →  Score your SKILL.md (keyword → LLM → GitHub Models)
skill-test       →  Run behavior tests against evals.json
skill-version    →  Track changes, detect regressions, roll back

What It Is Not

We don't sell skills. We don't host a marketplace. We're not a content platform. We test, score, and version the skills you already have.


Quick Start

pip install agent-skill-infra
skill-quality /path/to/skill/SKILL.md

Too simple? Good. That's the point.

How to use it — three ways

Channel Setup Best for
CLI pip install agent-skill-infra Local dev, pre-commit hooks
GitHub Issue Open a test-request issue Zero-setup testing, community submissions
CI uses: Liber1917/agent-skill-infra/.github/workflows/issue-test.yml (coming) PR gates, automated reviews

skill-quality — Quality Scoring

Three evaluation tiers, automatically selected:

# Tier 1: Fast keyword-based (no API needed, instant)
skill-quality skills/my-skill/SKILL.md

# Tier 2: Anthropic Claude (semantic evaluation, language-aware)
skill-quality skills/my-skill/SKILL.md --llm

# Tier 3: GitHub Models (free, zero-config, gpt-4o-mini)
skill-quality skills/my-skill/SKILL.md --gh-models

# Options
skill-quality skills/my-skill/SKILL.md --lint      # agent-skill-linter
skill-quality skills/my-skill/SKILL.md --security   # cisco-scanner
skill-quality skills/my-skill/SKILL.md --output json

What you get: Score (0–100%), 8-dimension breakdown, and actionable improvement suggestions — not just a number.

skill-test — Behavior Testing

Run evals.json test suites. Five judge types. No Agent runtime required.

skill-test run tests/fixtures/evals.json

# With mock adapter (offline, no runtime)
skill-test run tests/fixtures/evals.json --adapter mock

# Update snapshot baselines
skill-test run tests/fixtures/evals.json --update-snapshots

Judge types: keyword, schema, llm (Claude), flow, snapshot

skill-version — Version Awareness

Catch drift before it breaks things.

skill-version diff /path/to/skill --old-ref HEAD~3 --new-ref HEAD
skill-version check /path/to/skill --security
skill-version rollback /path/to/skill --target-ref HEAD~1 --yes
skill-version baseline store /path/to/skill case-1 output.txt
skill-version baseline detect /path/to/skill case-1 output.txt

Design Philosophy

No hardcoded benchmarks. The keyword-based checker is a fallback, not the product. Real evaluation happens through LLMs — Anthropic when you have a key, GitHub Models when you don't.

Scoring is useless without suggestions. Every quality report includes per-dimension findings and concrete "do this next" improvements. A number alone isn't a tool.

The tool adapts to the skill, not vice versa. Chinese descriptions, mixed-language triggers, single SKILL.md repos — we detect and score them all. No required JSON schema. No mandatory structure.

Free tier for everyone. GitHub Models (gpt-4o-mini) via the --gh-models flag costs nothing. Zero API keys. Automated in CI via GITHUB_TOKEN.


Development

git clone https://github.com/Liber1917/agent-skill-infra.git
cd agent-skill-infra
uv sync

uv run pytest          # 221 tests
uv run ruff check .     # lint
uv run pyright          # type check

License

MIT

About

Agent Skill Infrastructure: quality check, behavior test runner, version awareness

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