Agentic Eval

Implements self-critique loops where Claude generates output, evaluates it against your criteria, then refines based on its own feedback. Includes evaluator-optimizer patterns, test-driven code refinement, and LLM-as-judge scoring with JSON-structured critiques. Most useful for quality-critical tasks like code generation, reports, or analysis where you have clear success metrics. The reflection patterns prevent single-shot mediocrity by forcing iterative improvement, though you'll want to set iteration limits to avoid endless loops. Works best when your evaluation criteria are specific rather than subjective.

skills.sh installs: 10.3K
GitHub stars: 41K
last updated: Aug 21, 2026

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Install

$ npx -y skills add github/awesome-copilot --skill agentic-eval --agent claude-code

Installs into .claude/skills of the current project.

Files

Agentic Evaluation Patterns

Patterns for self-improvement through iterative evaluation and refinement.

Overview

Evaluation patterns enable agents to assess and improve their own outputs, moving beyond single-shot generation to iterative refinement loops.

Generate → Evaluate → Critique → Refine → Output
    ↑                              │
    └──────────────────────────────┘

When to Use

Quality-critical generation: Code, reports, analysis requiring high accuracy
Tasks with clear evaluation criteria: Defined success metrics exist
Content requiring specific standards: Style guides, compliance, formatting