fake-star-audit — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited fake-star-audit (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
This skill audits a GitHub repository's stargazers for signs of fake-star injection and returns an explainable risk verdict. It wraps audit.py, a single-file, zero-dependency, anonymous-API tool (no token, no file writes).
Trigger when the user asks anything like:
owner/repo fake-starred?" / "are these stars real?"audit.py lives at the repository root (one directory above this skill). Run:
python3 /path/to/fake-star-audit/audit.py --repo <owner>/<name> --jsonapi.github.com.https://github.com/a/b,pass --repo a/b.
Key fields:
risk_verdict: LOW / MEDIUM / HIGH.axes: the 5 detection axes, each with flag (bool) and evidence (string,annotated by which window — earliest = bootstrap window, latest = recent drip).
extended_signals: booleans like fork_star_inverted, single_repo_mass_injection,trusted_org_parasitism (any hard one forces HIGH).
warnings: caveats (e.g. repo too large to page to newest stars).Verdict logic: HIGH = 3+ axes or a hard signal; MEDIUM = 2 axes or 1 axis + a signal; LOW = 0–1 axes and no hard signals. It is conservative by design.
Give a short, plain-language summary, then the reason:
HIGH risk. 100 stars landed in the first 33 minutes after the repo was created, with near-sequential account IDs — a bootstrap-injection pattern, not organic growth.
Always cite the specific flagged axes / evidence. If the verdict is LOW, say so plainly ("stars look organic on the sampled windows") and mention it's a page-1 sample, not a full-history proof. Never present a verdict as definitive proof of fraud — it's a heuristic signal; point the user to the evidence.
rate_limited: the anonymous 60/h budget is spent; tell the user to retry inup to an hour.
not_found: repo is private or doesn't exist.pagination_capped / warnings mentioning size: very large repo; the recentwindow falls back to oldest stars — note this caveat in your answer.
This skill only audits public repositories using public data.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.