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 2 skills

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

Decision summary

Strongest overall

Code Review

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

Fastest prototype

Code Review

Best first install candidate based on install readiness and adoption.

Freshest repo

lintlang-audit

Most recent maintenance signal among this shortlist.

Signal	lintlang-audit Audit a named AI agent config, system prompt, tool-definition or instruction file (YAML, JSON, Markdown, text, or Python) with the released LintLang CLI, on request. Use when the user asks to audit, lint, scan or review such a file for ambiguous tool descriptions, missing stop conditions, schema/description mismatches, or prompts embedded in Python, and names the file. Deterministic offline static analysis, no model call and no network call. Do not use for general code review, for prose documentation, or when no file has been named.	Code Review Review a branch or diff against repository standards and the originating spec in two independent analysis passes.
Quality	62/100 Promising	100/100 Excellent
Decision verdict	61/100 Prototype first Prototype with this skill first; keep a fallback candidate ready.	100/100 Production-ready Use this as a leading candidate, then validate the README and install path in your own agent stack.
Adoption	127 stars Verified outcomes are shown on each skill page	169K stars Verified outcomes are shown on each skill page
Freshness	Sep 30, 2026	Jul 13, 2026
Use-case fit	Coding agents Security and compliance Research agents	Coding agents