# Show HN: SkillPreflight – score AI agent skills before installing them > Source: > Published: 2026-08-25 10:08:13+00:00 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 ``` Options: ``` --installed Scan common installed skill directories. --format text, json, markdown, html, or sarif. Default: text. --out Write report to a file. --fail-below Exit with code 1 if any scanned skill is below this score. --fail-on Exit for findings at or above info, low, medium, high, or critical. --config Load an explicit JSON policy file. --exclude Exclude a target-relative path glob. Repeat as needed. --ignore-rule Suppress a rule ID or wildcard pattern. Repeat as needed. --keep-temp Keep temporary clones for debugging. --summary Show aggregate results and the lowest-scoring skills only. --top Number of skills shown with --summary. Default: 20. ``` Summary mode supports text, JSON, Markdown, and HTML output. SARIF always contains the full set of findings for code scanning. Use an explicit JSON policy to keep generated files and reviewed false positives out of a scan: ``` { "exclude": ["fixtures/**", "vendor/**"], "ignoreRules": ["compatibility.os-specific-command"], "failBelow": 70, "failOn": "high" } skill-preflight scan . --config skill-preflight.json ``` Config files are never loaded from a scanned repository automatically. This prevents an untrusted remote skill from suppressing its own findings. CLI exclusions and ignored rules are merged with the config; CLI score and severity gates take precedence. Suppressed findings remain counted in the report so policy decisions are visible. See `docs/policy.md` for glob behavior and CI examples. Generate Shields-compatible badge JSON: ``` skill-preflight badge ./my-skill --out skill-preflight-badge.json ``` The badge payload can be served through a static endpoint or GitHub Pages: ``` { "schemaVersion": 1, "label": "SkillPreflight", "message": "91/100 A", "color": "brightgreen" } ``` After the package is published to npm and the repository is tagged, skill authors can scan every PR: ``` name: SkillPreflight on: [pull_request, push] jobs: scan: runs-on: ubuntu-latest steps: - uses: actions/checkout@v6 - uses: agent-contracts/skill-preflight@v1 with: target: "." config: skill-preflight.json ``` Without a config, the Action fails below 70 by default. A policy file's `failBelow` value is used when `config` is provided; an explicit `fail-below` input overrides both. For GitHub code scanning, emit SARIF: ``` skill-preflight scan . --format sarif --out skill-preflight.sarif ``` See `docs/github-action.md` for the full workflow. In August 2026, SkillPreflight scanned a frozen, commit-pinned sample of 40 public agent skills. The sample averaged **80.8/100**, with a median score of **85.5/100**. Read the [reproducible benchmark report](/agent-contracts/skill-preflight/blob/main/benchmarks/2026-08-public-skills/README.md) for the methodology, aggregate findings, source snapshot, and raw JSON/CSV data. This convenience sample is not an ecosystem ranking, and static findings require manual review. SkillPreflight does not execute scripts inside scanned skills. It only reads files and performs static analysis. Oversized files are measured without being loaded into text analysis. ``` shell-super-agent: 35/100 (F) - High risk, do not install blindly Top findings: - [CRITICAL] Remote script execution pattern (SKILL.md:15) - [HIGH] Prompt injection language (SKILL.md:8) - [HIGH] Potential secret or credential access (SKILL.md:10) ``` See `docs/rules.md` for the current static analysis rule catalog, including dependency, install-script, MCP config, token, and compatibility checks. See `docs/release.md` for the first npm and GitHub release checklist.