Agent skill · Testing & QA

evaluation

This skill should be used when the user asks to "evaluate agent performance", "build test framework", "measure agent quality", "create evaluation rubrics", or mentions LLM-as-judge, multi-dimensional evaluation, agent testing, or quality gates for agent pipelines.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill context-eng-evaluation --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 10 KB
Bundled scripts: none
Path: skills/ai-llm/context-eng-evaluation/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Evaluation Methods for Agent Systems Evaluation of agent systems requires different approaches than traditional software or even standard language model applications. Agents make dynamic decisions, are non-deterministic between runs, and often lack single correct answers. Effective evaluation must account for these characteristics while providing actionable feedback. A robust evaluation framework enables continuous improvement, catches regressions, and validates that context engineering choices achieve intended effects. ## When to Activate Activate this skill when: - Testing agent performance systematically - Validating context engineering choices - Measuring improvements over time - Catching regressions before deployment - Building quality gates for agent pipelines - Comparing different agent configurations - Evaluating production systems continuously ## Core Concepts Agent evaluation requires outcome-focused approaches that account for non-determinism and multiple valid paths. Multi-dimensional rubrics capture various quality aspects: factual accuracy, completeness, citation accuracy, source quality, and tool efficiency. LLM-as-judge provides scalable evaluation while human eva

What's inside
Steps it walks through
  1. When to Activate
  2. Core Concepts
  3. Detailed Topics
  4. Evaluation Challenges
  5. Evaluation Rubric Design
  6. Evaluation Methodologies
  7. Test Set Design
  8. Context Engineering Evaluation
  9. Continuous Evaluation
  10. Practical Guidance
  11. Building Evaluation Frameworks
  12. Avoiding Evaluation Pitfalls
  13. Examples
  14. Guidelines
Ships with 1 file
  • metadata.json
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About this skill
What does the evaluation skill do?

This skill should be used when the user asks to "evaluate agent performance", "build test framework", "measure agent quality", "create evaluation rubrics", or mentions LLM-as-judge, multi-dimensional evaluation, agent testing, or quality gates for agent pipelines.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill context-eng-evaluation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going