Agent skill · Data and AI
llm-evaluation
Test LLM apps with metrics, human review and LLM-as-judge.
Test LLM apps with metrics, human review and LLM-as-judge.
- Type
- Agent skill
- Group
- Agent skills
- Category
- Data and AI
- By
- @wshobson
- GitHub stars
- 41,906
- License
- MIT
More in Agent skills
Find out what you really want before building: ask, compare approaches, write and approve a design doc.
Read the session transcripts to show why an agent session went wrong, with file and line proof.
Give each independent problem to its own sub-agent and run them side by side.
Carry out a written plan yourself, task by task, with test proof and a ledger, then one final review.
When work is done and green, pick merge, PR or discard, then clean up the branch and worktree.
Handle review comments with checks, not blind yes: understand, verify, then fix or push back.
Read it from code
curl 'https://tools.flisk.si/api/tools/wshobson-llm-evaluation'