Methodology

How we score Skills

Every Skill on this site has a composite 0–100 score. The number is derived from 9 verifiable inputs — no hand-curated quality dial, no hidden weights. The current rubric is version 1.0.

Inputs

The 9 inputs

InputWeightSource
Install count20Verified installs across skills.sh, npm, and GitHub releases (log-normalized).
Provenance15Anthropic > verified org > community. Community skills with high adoption get a partial boost.
GitHub stars15Stars on the source repo (log-normalized).
Recency10Days since the last commit. Skills updated in the last 14 days score full marks.
Compatibility10Number of agents (out of 5: Claude Code, Cursor, Codex, Gemini, Antigravity) the skill is verified to work with.
Documentation depth10README, docs URL, "best for", and "not ideal for" all present.
Install ergonomics10One-command install scores full; plugin install scores partial; manual install scores low.
License5OSI-approved permissive licenses score full; closed but verifiable scores half.
Verification freshness5How recently we tested that the install command still works.

Why

Design choices

Composite over single-axis. Other directories rank by install count alone, which rewards age over quality. We use 9 inputs so recency, provenance, and ergonomics also count.

No aggregateRating in JSON-LD. We do not collect user reviews and so do not publish a fake aggregate. The composite score is a quality signal, not a five-star average.

Provenance has weight, not a veto. Anthropic and verified-org skills get an automatic boost, but a community skill with high adoption can still outrank them — Superpowers (40k+ stars) is the canonical example.

Verification freshness matters. Five points of the score reflect when we last verified the install command works. A skill we have not retested in months loses points until we do.

Worked example

Example: frontend-design

Frontend-design earns full marks on install count (277K+), provenance (Anthropic), compatibility (5/5 agents), license (MIT), and install ergonomics (one-command). Stars and recency are at 90% (a few weeks since last commit). Documentation is at 90% (a clear README and SKILL.md, no formal "not ideal for" section). Final score: 92.