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.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install agentgptsmith-monadframework-llm-evaluation
Repository
Skill path: .claude/skills/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.
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Full Stack, Data / AI, Testing.
Target audience: Development teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: agentgptsmith.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install llm-evaluation into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/agentgptsmith/MonadFramework before adding llm-evaluation to shared team environments
- Use llm-evaluation for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.