tracedocs — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited tracedocs (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.
Turn any codebase into an evidence-grounded documentation package (overview, operation, deployment, learning, architecture, API/data, troubleshooting, maintenance) plus a machine-readable index.json for AI agents. Every operational/deployment claim cites a source file and a confidence label (Verified / Inferred / Unknown / Needs confirmation); it never invents deployment steps and records gaps instead.
Full skill, references, templates, and a validated sample output: https://github.com/wxggzz/tracedocs (MIT).
index.json)signals, tests).
confidence labels.
index.json manifest; never inventsdeployment steps.
documented).
Use tracedocs to generate evidence-grounded study docs for this repository. Write the output to study-docs/.User: "Document ./my-app with tracedocs"
The skill scans the repo and writes a study-docs/ package (00-10 manuals + index.json + _evidence/), citing each operational claim's source and labelling its confidence - and explicitly noting anything it cannot verify (for example, "no deployment configuration found in the repo").
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.