Skill comparison

Compare agent skills before installing.

Put high-signal skills side by side and inspect quality, adoption, freshness, install readiness, use-case fit, and warnings in one place.

Comparing 4 skills

Use this as a shortlist, then open the skill detail page before adopting.

Add more skills

Decision summary

Superset is the strongest overall pick here because it has a 100/100 readiness score and fits Coding agents.

Strongest overall

Superset

Use this as a leading candidate, then validate the README and install path in your own agent stack.

Fastest prototype

Superset

Best first install candidate based on install readiness and adoption.

Freshest repo

Superset

Most recent maintenance signal among this shortlist.

Signal	release Cut a brooks-lint release: set the version in package.json, propagate it across all four plugin manifests and every version-bearing text file (README badges, docs site metadata), write the CHANGELOG entry, validate, then commit, push, tag, and publish the GitHub release. Triggers when the maintainer asks to "release", "cut a release", "ship a new version", or "bump and publish" brooks-lint. Do NOT trigger for: propagating an already-decided version without releasing (use `npm run bump` directly), CHANGELOG edits alone, or questions about the release process that don't ask to perform it.	Airflow Apache Airflow - A platform to programmatically author, schedule, and monitor workflows	Scientific Agent Skills Turn any AI agent into an AI Scientist. The #1 Agent Skills library for science, used by 160,000+ scientists worldwide. 140 ready-to-use skills plus 100+ scientific databases covering biology, chemistry, medicine, and drug discovery. Compatible with Cursor, Claude Code, Codex, Pi, Antigravity, and the open Agent Skills standard.	Superset Apache Superset is a Data Visualization and Data Exploration Platform
Quality	78/100 Strong	100/100 Excellent	100/100 Excellent	100/100 Excellent
Decision verdict	89/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack.	100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack.	100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack.	100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack.
Adoption	1.4K stars Verified outcomes are shown on each skill page	47K stars Verified outcomes are shown on each skill page	33K stars