Supply Chain Risk Auditor

Generates a supply-chain risk report for a project's direct dependencies (npm, PyPI, Go), plus an advisory sweep of everything its lockfile resolves. Two deterministic scripts do the measuring; your job is the judgment they refuse to automate.

Why the scripts do the measuring, not you

Every figure in this report is a claim about somebody else's project, and hand-collected figures were measured wrong before this skill was rebuilt around scripts: GitHub contributor counts said five-plus people maintain lodash where npm's ACL says one, and gh saw zero downloads for a package that moves 164 million a week. Do not estimate maintainer counts, downloads, staleness, or CVE history from gh, web search, or memory — run the collector, and quote what it measured.

The scripts enforce two rules worth knowing before you read their output:

• Unavailable data is never evidence of risk. Every criterion resolves to assessed-clean, assessed-flagged, or unassessable-with-a-reason.
• An absent measurement is never a clean verdict. A run that measured nothing exits non-zero instead of printing a report that finds nothing.

Workflow

1. Confirm the target directory has manifests: package.json, pyproject.toml, requirements*.txt, or go.mod. If none exist, say so and stop — do not audit an ecosystem this collector does not parse by hand. Lockfiles read for exact versions and the transitive sweep: package-lock.json/npm-shrinkwrap.json, uv.lock, and a go 1.17+ go.mod. yarn.lock, pnpm-lock.yaml, and poetry.lock are not read — the report says so when they are present, and versions fall back to pins or the latest release.

2. Check gh auth status. Unauthenticated GitHub allows 60 requests/hour against 5,000, and the collector makes several per dependency; expect repository criteria to come back unassessable without it. Say so rather than fixing it silently.

3. Collect, then render. Put outputs somewhere outside the audited repository unless asked otherwise:

   uv run {baseDir}/scripts/collect.py <project-dir> --json <out-dir>/findings.json
   uv run {baseDir}/scripts/render.py <out-dir>/findings.json --out <out-dir>/report.md
   

   Expect a few minutes for ~50 dependencies — several HTTP requests per dependency, more with many Go modules, and slower without authenticated gh. If collect.py exits non-zero, it is refusing to report — relay its message verbatim instead of retrying or working around it.

4. Read report.md and findings.json. The report is the deliverable; the JSON carries the datum behind every verdict when you need to cite one.

5. Add what the collector cannot, clearly separated from what it measured:

   • A short narrative for this reader: what to act on first, and why.
   • Upgrade paths for advisory findings — check whether the fix is a patch or a major version away.
   • Replacement candidates for abandoned or archived dependencies. Verify a candidate exists in the registry before naming it, and label these as judgment, not measurement.
   • For flagged install scripts: whether npm ci --ignore-scripts is viable for this project's build.

Style for what you add

Write added prose the way a security report reads, and apply the same register to the report addendum and the final reply alike — replies get pasted into tickets and reports verbatim. State the finding, the datum behind it, and the action.

• Impersonal and declarative: no first or second person ("I ran the collector", "you should upgrade"), no contractions, no exclamation points.
• Active voice, with the subject matter as the actor: "upgrading to 1.19.0 clears all 25 advisories", not "it is recommended that axios be upgraded".
• Objective: no intensifiers or subjective framing ("very", "significant", "fortunately"), and no guesses about why the project chose what it chose.
• Tense: past for what the audit did, present for the state of the dependencies, future for the consequences of acting or not.
• Constructive: a recommendation names the action and its cost, never a culprit.

If the report-writing:writing-style skill is available in the session, follow it — it is the full version of this register.

The rendered report carries facts only. The interpretive rules below are instructions to you, not content for the reader — do not copy them into the deliverable as caveats or framing.

Reading the report

• Unassessable is not risk. PyPI publishes no maintainer ACL and Go has no registry; those rows say what could not be known, not what is wrong.
• The coverage table bounds every claim. "No advisories" means "none among what was assessed" — check the assessed count before repeating a clean verdict.
• Quote figures verbatim. Do not re-derive, round, or embellish the report's numbers; every one is reproducible from the artifact.
• Absence from the findings is not endorsement. A dependency with no findings was measured against these criteria only.

Rationalizations to reject

• "gh can give me maintainer counts faster than the collector." Measured wrong — repo contributors and registry publish rights are different populations.
• "No findings, so the dependencies are safe." Read the coverage table; on PyPI and Go, half the criteria are structurally unassessable.
• "The unassessable rows would just confuse the reader; I'll drop them." They are the boundary of every claim in the report. Dropping them turns partial coverage into a clean bill of health, which is the failure this skill was rebuilt to prevent.
• "The version is probably close enough." A range checked at latest-release and a lockfile-resolved version are different claims; the report labels which one it makes. Keep the label.

When not to use

• License compliance auditing.
• Scanning the target's own source for vulnerabilities or secrets — this skill never reads dependency source, only registry, advisory, and repository metadata.
• Judging whether the project installs or builds. The audit is designed to work from nothing more than the dependency list — manifests and lockfiles — and never installs, builds, or executes anything. Broken installs and import-time breakage are out of scope, and worth saying so if the user seems to expect them.
• Ecosystems other than npm, PyPI, and Go; say the ecosystem is unsupported rather than improvising an audit for it.