Show HN: SkillPreflight – score AI agent skills before installing them SkillPreflight, a new open-source command-line tool, scores AI agent skills on a 100-point scale across security, permission restraint, token efficiency, lightweight footprint, maintainability, reliability, and compatibility before installation. The tool, run via npx, scans local directories or GitHub repositories for skills used in Codex, Claude Code, Cursor, and Gemini CLI, and supports JSON policy files to exclude files and ignore rules. It aims to help users avoid unsafe or bloated third-party skills by providing pre-install safety checks. SkillPreflight is a pre-install safety, token, and maintainability scorecard for AI agent skills. It helps users decide whether a Codex, Claude Code, Cursor, Gemini CLI, or other agent skill is safe and lightweight enough to install. If SkillPreflight helps you vet a third-party skill, consider starring the repository so more users can discover safer pre-install checks. Run without installing: npx skill-preflight scan ./my-skill Scan a GitHub repository before installing it: npx skill-preflight scan https://github.com/user/some-skill Scan one skill inside a large repository by pasting its GitHub directory or SKILL.md URL: npx skill-preflight scan https://github.com/user/skills/tree/main/skills/my-skill npx skill-preflight scan https://github.com/user/skills/blob/main/skills/my-skill/SKILL.md Scan common local skill directories: npx skill-preflight scan --installed For repositories containing many skills, show a compact list of the 20 lowest-scoring skills: npx skill-preflight scan https://github.com/user/skill-collection --summary --top 20 Apply a local policy when scanning a repository: npx skill-preflight scan . --config skill-preflight.json npm install npm run build npm test npm run dev -- scan examples/risky-skill SkillPreflight uses a 100-point score: | Category | Points | What it checks | |---|---|---| | Security | 35 | Dangerous commands, secret access, exfiltration, prompt injection, remote script execution | | Permission restraint | 15 | Over-broad activation, unnecessary shell/network/file access | | Token efficiency | 15 | Oversized SKILL.md , repeated content, poor progressive disclosure | | Lightweight footprint | 10 | File count, total size, dependencies, large assets | | Maintainability | 10 | README, license, frontmatter, examples, documentation hygiene | | Reliability | 10 | Tests, fixtures, deterministic workflow, error handling | | Compatibility | 5 | Hardcoded local paths, OS-specific assumptions, fragile shell usage | Repeated locations for the same rule remain visible, but each rule ID deducts points only once per skill. This keeps large repositories from receiving a lower score merely because the same issue appears in several files. When one skill directory contains other skills, SkillPreflight reports each SKILL.md as a separate skill and excludes child-skill files from the parent score. skill-preflight scan