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coder_eval

Skill Development Usable
Works inClaude Code
Usable Scanned — metadata only

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.

106 starsApache-2.0 (commercial OK)FreeQuick setup
Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

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.

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https://github.com/UiPath/coder_eval

By UiPath

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
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.

First thing to try

After installing, paste this into Claude:

Help me benchmark Claude's coding performance against other AI models with reproducible test suites
CostFree

Trust Signals Auto-scanned

Stars106Last updated2026-07-23LicenseApache-2.0 (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-07-23 · scanner v1

Community Pulse Growing

Discussed on Hacker News

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

Ease of Use
3/5
Versatility
3/5
Reliability
3/5
Security
3/5
Overall score3.00 / 5.00 UsableEvaluatedJul 2026
Scored from trust signals (evidence-eval-v1): 106 GitHub stars; contributors unknown; last commit -1d ago; license Apache-2.0.

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