coder_eval
Validates AI coding agent quality before production use through standardized benchmarks, reducing deployment risk and enabling data-driven model selection ac…
Evaluate & benchmark AI coding agents and Claude Code skills — sandboxed, reproducible YAML eval suites for Claude Code, Codex & Gemini, with A/B experiments and CI gates.
- Benchmark Claude's coding performance against other AI models with reproducible test suites.
- Run A/B experiments to compare different Claude Code configurations and measure improvements.
- Set up CI/CD gates that automatically block deployments if Claude Code skills fall below standards.
Validates AI coding agent quality before production use through standardized benchmarks, reducing deployment risk and enabling data-driven model selection across Claude, Codex, and Gemini implementations.
Engineering teams evaluating AI coding assistants for internal adoption or integrating multiple LLM providers with quantified performance requirements.
https://github.com/UiPath/coder_eval
By UiPath
How to Get It
claude plugins install UiPath/coder_eval
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 benchmark Claude's coding performance against other AI models with reproducible test suites
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Hacker News
- Bleezer coder: 1/3 of his time spent evaluating incorrect APIs or fixing open so — Hacker News · 6 pts
- Show HN: ViewCoder – Interview coder with confidence and insight — Hacker News · 2 pts
- Coder_eval – an evaluation framework for CLI and Skill builders — Hacker News · 1 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): 106 GitHub stars; contributors unknown; last commit -1d ago; license Apache-2.0.
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): 106 GitHub stars; contributors unknown; last commit -1d ago; license Apache-2.0.