Trust and health report

generative-ai-docs - trust report

Sourced, dated trust signals - maintenance label posture, repository provenance, and security scan status. Not a composite safety grade.

GraphCanon updated today · GitHub synced today

Maintenance

Recency and activity heuristics from public GitHub metadata (maintenance label, momentum); methodology: github_public_v1.

Slowing36% signal

last push 166d ago

Provenance

Repository identity and fork provenance (github_public_v1).

Security scan

Dependency advisory security scan when a lockfile is present. Not a full code audit.

Status
No lockfile
Last scan
today
Scanner
none

Method and caveats:these are sourced, dated heuristics from public GitHub data and optional dependency scans. A status like "no criticals found on 2026-07-11" is not a guarantee of safety. Read the full trust methodology · JSON report at /api/graphcanon/tools/google-generative-ai-docs/trust.

Common questions

Is generative-ai-docs maintained?
GraphCanon rates generative-ai-docs "Slowing" (36% maintenance signal from public GitHub metadata, computed today). Last push was 166 days ago. This is a recency heuristic, not a guarantee the project will stay maintained.
Is generative-ai-docs safe to use?
Last scanned today (none profile). Status: No lockfile. Absence of findings in our scan is not a security guarantee - see trust methodology for scope limits. GraphCanon does not certify generative-ai-docs as safe - review maintenance, provenance, and scan findings on this page before adopting.
Is generative-ai-docs a fork?
No. generative-ai-docs is not flagged as a fork in GitHub metadata at the time of the last refresh.
Does generative-ai-docs have known security vulnerabilities?
Last scanned today (none profile). Status: No lockfile. Absence of findings in our scan is not a security guarantee - see trust methodology for scope limits.
How often is the generative-ai-docs trust report updated?
Trust signals refresh on GitHub ingest/refresh cycles and optional dependency/MCP scans. This report was computed today (methodology github_public_v1).
What does GraphCanon never claim about generative-ai-docs?
We never publish a composite safety grade, pen-test endorsement, or "verified secure" label for generative-ai-docs. Signals are sourced heuristics with explicit limits - see trust methodology.
How does GraphCanon assess trust for generative-ai-docs?
Signals are sourced from public GitHub metadata and optional dependency/MCP manifest scans, each tagged with methodology version and computed date. GraphCanon does not publish a composite safety grade. Read trust methodology for full scope and limits.