maestro
Provides audit trail and state management for AI-assisted code work, reducing compliance risk and enabling teams to demonstrate agent decisions to auditors o…
Agent harness for codebases. Gives Claude Code, Codex, and CI a shared task system, verdict ledger, and state store so agent work is traceable and auditable.
- Ask Claude to audit code changes across repositories while maintaining a complete trace of all decisions
- Generate compliance reports showing exactly which security checks passed and failed during code reviews
- Automate multi-agent code analysis tasks with full audit trails for regulatory compliance verification
Provides audit trail and state management for AI-assisted code work, reducing compliance risk and enabling teams to demonstrate agent decisions to auditors or regulators.
Security and compliance teams requiring traceable AI code modifications with full decision ledgers.
https://github.com/ReinaMacCredy/maestro
By ReinaMacCredy
How to Get It
claude plugins install ReinaMacCredy/maestro
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Audit code changes across repositories while maintaining a complete trace of all decisions
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Hacker News
- Maestro: A Linux-compatible kernel in Rust — Hacker News · 745 pts
- Maestro: Netflix's Workflow Orchestrator — Hacker News · 307 pts
- Keyboard Maestro 11 — Hacker News · 200 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 199 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 199 GitHub stars; contributors unknown; last commit 0d ago; license MIT.