llm-evaluation
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
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Installation for Agentic Skill
View all platforms →skilz install varunisrani/skills-claude/llm-evaluation skilz install varunisrani/skills-claude/llm-evaluation --agent opencode skilz install varunisrani/skills-claude/llm-evaluation --agent codex skilz install varunisrani/skills-claude/llm-evaluation --agent gemini
First time? Install Skilz: pip install skilz
Works with 22+ AI coding agents
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Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/varunisrani/skills-claude cp -r skills-claude/claude_code_skills/all-skills/llm-evaluation ~/.claude/skills/ Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- varunisrani (GitHub)
- Repository
- skills-claude
- Type
- Non-Technical
- Meta-Domain
- general
- Primary Domain
- general
- Sub-Domain
- evaluation llm
- Market Score
- 22.1
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