Trust and health report
ai-berkshire - 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.
last push 0d ago
Provenance
Repository identity and fork provenance (github_public_v1).
- GitHub repo id: 1203777920
- Not a fork
- Personal account
- Computed today
Security scan
Manifest-only review of declared MCP transports and auth fields. Not a full code audit.
- Status
- No MCP manifest
- 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/xbtlin-ai-berkshire/trust.
Common questions
- Is ai-berkshire maintained?
- GraphCanon rates ai-berkshire "Very active" (96% maintenance signal from public GitHub metadata, computed today). Last push was 0 days ago. This is a recency heuristic, not a guarantee the project will stay maintained.
- Is ai-berkshire safe to use?
- Last scanned today (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 ai-berkshire as safe - review maintenance, provenance, and scan findings on this page before adopting.
- Is ai-berkshire a fork?
- No. ai-berkshire is not flagged as a fork in GitHub metadata at the time of the last refresh.
- Does ai-berkshire have known security vulnerabilities?
- Last scanned today (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 ai-berkshire 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 ai-berkshire?
- We never publish a composite safety grade, pen-test endorsement, or "verified secure" label for ai-berkshire. Signals are sourced heuristics with explicit limits - see trust methodology.
- How does GraphCanon assess trust for ai-berkshire?
- 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.