llm-evaluation
Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.
npx skills add majiayu000/claude-skill-registry --skill llm-evaluation-sickn33-antigravity-awesome --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LLM Evaluation Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing. ## Do not use this skill when - The task is unrelated to llm evaluation - You need a different domain or tool outside this scope ## Instructions - Clarify goals, constraints, and required inputs. - Apply relevant best practices and validate outcomes. - Provide actionable steps and verification. - If detailed examples are required, open `resources/implementation-playbook.md`. ## Use this skill when - Measuring LLM application performance systematically - Comparing different models or prompts - Detecting performance regressions before deployment - Validating improvements from prompt changes - Building confidence in production systems - Establishing baselines and tracking progress over time - Debugging unexpected model behavior ## Core Evaluation Types ### 1. Automated Metrics Fast, repeatable, scalable evaluation using computed scores. **Text Generation:** - **BLEU**: N-gram overlap (translation) - **ROUGE**: Recall-oriented (summarization) - **METEOR**: Semantic similarity - **BERTScore**: Embedding-based similarity - **Perplexity**: Language
- Do not use this skill when
- Instructions
- Use this skill when
- Core Evaluation Types
- 1. Automated Metrics
- 2. Human Evaluation
- 3. LLM-as-Judge
- Quick Start
- Automated Metrics Implementation
- BLEU Score
- ROUGE Score
- BERTScore
- Custom Metrics
- LLM-as-Judge Patterns
What does the llm-evaluation skill do?
Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill llm-evaluation-sickn33-antigravity-awesome --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.