eval-framework

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Evaluate AI agent reliability with pass@k metrics

AuthorCheggin
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Evaluates AI agent reliability by focusing testing on changes that affect behavior, reducing wasted compute and surfacing flaky or brittle interactions early.

Core Features & Use Cases

  • Diff-driven eval execution: runs only evals impacted by a git diff to minimize CI time.
  • Pass@k and pass^k analytics: measures partial and full success rates with per-eval diagnostics.
  • CI integration: hooks and dashboards to detect regressions and track performance across releases.
  • Real-world use cases include validating agent safety, stability after feature changes, and regression testing of capabilities.

Quick Start

Run the evaluation suite against your agent changes to measure pass@k metrics.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: eval-framework
Download link: https://github.com/Cheggin/request-for-startups/archive/main.zip#eval-framework

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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