Trust and health report
learn-ai-engineering - trust report
Sourced, dated trust signals - maintenance label posture, repository provenance, and security scan status. Not a composite safety grade.
GraphCanon updated 3d · GitHub synced 3d
Maintenance
Recency and activity heuristics from public GitHub metadata (maintenance label, momentum); methodology: github_public_v1.
last push 193d ago
+100 stars (30d) · 0 open issues (30d)
Provenance
Repository identity and fork provenance (github_public_v1).
- GitHub repo id: 964477695
- Not a fork
- Personal account
- Computed 3d
Security intelligence
Source-by-source security scan results from public intelligence providers. Missing, partial, or failed queries are shown explicitly and are not treated as clean.
OSV dependency advisories
No lockfile (source not queried)- Last query
- 1mo
- Scanner
- osv@v1
OpenSSF Scorecard
Not queried- Scanner
- openssf-scorecard@v1
Weekly public scans omit some checks at scale.
View source evidenceMethod and caveats: these are sourced, dated heuristics from public GitHub data and external security intelligence providers. A status like "no published findings from this source" is not a guarantee of safety. Read the full trust methodology · JSON report at /api/graphcanon/tools/ashishps1-learn-ai-engineering/trust.
Common questions
- Is learn-ai-engineering maintained?
- GraphCanon rates learn-ai-engineering "Slowing" (36% maintenance signal from public GitHub metadata, computed 3d). Last push was 193 days ago. This is a recency heuristic, not a guarantee the project will stay maintained.
- Is learn-ai-engineering safe to use?
- Last scanned 1mo (mcp_manifest profile). Status: No MCP manifest. Absence of findings in our scan is not a security guarantee - see trust methodology for scope limits. GraphCanon does not certify learn-ai-engineering as safe - review maintenance, provenance, and scan findings on this page before adopting.
- Is learn-ai-engineering a fork?
- No. learn-ai-engineering is not flagged as a fork in GitHub metadata at the time of the last refresh.
- Does learn-ai-engineering have known security vulnerabilities?
- Last scanned 1mo (mcp_manifest profile). Status: No MCP manifest. Absence of findings in our scan is not a security guarantee - see trust methodology for scope limits.
- How often is the learn-ai-engineering trust report updated?
- Trust signals refresh on GitHub ingest/refresh cycles and optional dependency/MCP scans. This report was computed 3d (methodology github_public_v1).
- What does GraphCanon never claim about learn-ai-engineering?
- We never publish a composite safety grade, pen-test endorsement, or "verified secure" label for learn-ai-engineering. Signals are sourced heuristics with explicit limits - see trust methodology.
- How does GraphCanon assess trust for learn-ai-engineering?
- 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.