supercov
Validates that AI-generated code meets baseline security, quality, and test coverage standards before production deployment—reducing the risk of agent-author…
Coverage, security and code quality for coding agents
- Audit code generated by AI agents for security vulnerabilities and compliance gaps
- Measure test coverage metrics across codebases created by automated coding tools
- Generate quality reports comparing security standards before and after agent-written code
Validates that AI-generated code meets baseline security, quality, and test coverage standards before production deployment—reducing the risk of agent-authored vulnerabilities reaching live systems.
Engineering teams adopting coding agents who need automated verification of generated code quality and security compliance.
https://github.com/supercorp-ai/supercov
By supercorp-ai
How to Get It
claude plugins install supercorp-ai/supercov
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:
Help me audit code generated by AI agents for security vulnerabilities and compliance gaps
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Hacker News
- Show HN: MC/DC coverage so coding agents could work overnight — Hacker News · 2 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 130 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): 130 GitHub stars; contributors unknown; last commit 0d ago; license MIT.