llm-evaluation — Skills — getagentictools

What it does

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

llm evaluation

Source

Repository: https://github.com/wshobson/agents

llm-evaluation FAQ

What does the llm-evaluation skill do?

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. Measuring LLM application performance systematically Comparing different models or prompts

How do I install llm-evaluation?

Run: npx -y skills add https://github.com/wshobson/agents --skill llm-evaluation --agent claude-code — the source lives at github.com/wshobson/agents.

Maintain llm-evaluation?

Let people know it's listed here — add the badge (live metrics, light/dark aware) or a plain link to your README or docs.

[![llm-evaluation on getagentictools](https://getagentictools.com/badge/skills/wshobson-agents-llm-evaluation.svg)](https://getagentictools.com/skills/wshobson-agents-llm-evaluation?ref=badge)

npx agentictools info skills/wshobson-agents-llm-evaluation

The second line is the CLI lookup for this page — handy in READMEs and docs.