llm-evaluation

Name: llm-evaluation
Rating: 1.1 (1 reviews)
Author: Microck

22.1

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

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Claude Code (CLI) Fast

skilz install Microck/ordinary-claude-skills/llm-evaluation

OpenCode (CLI) Fast

skilz install Microck/ordinary-claude-skills/llm-evaluation --agent opencode

OpenAI Codex (CLI) Native

skilz install Microck/ordinary-claude-skills/llm-evaluation --agent codex

Gemini CLI (Project) Project

skilz install Microck/ordinary-claude-skills/llm-evaluation --agent gemini

First time? Install Skilz: pip install skilz

Works with 22+ AI coding agents

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For Claude Desktop Easy

Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

Manual Installation

1. Clone the repository:

git clone https://github.com/Microck/ordinary-claude-skills

2. Copy the agent skill directory:

cp -r ordinary-claude-skills/skills_categorized/machine-learning/llm-evaluation ~/.claude/skills/

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Need detailed installation help? Check our platform-specific guides:

Claude Desktop Guide Claude Code Guide Troubleshooting

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Agentic Skill Details

Owner: Microck (GitHub)
Repository: ordinary-claude-skills
Type: Non-Technical
Meta-Domain: general
Primary Domain: general
Sub-Domain: evaluation llm
Market Score: 22.1

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