Eval set for an AI task
OfficialOfficial · updated Nov 4, 2026 · v1.0.0
Builds a 20-to-50-case eval set for an AI task: normal, edge, and adversarial cases, expected results or rubrics, pass criteria, and a re-run routine.
Sign up free to add this skill to your pod
You come back here after you sign in, and add it with one click.
When to use it
- You're about to launch or change a prompt, chatbot, or AI workflow
- Users report bad answers and you need to know if a fix worked
What you give it
- The task and what good output is
- Real example inputs
- Known failures
- The current prompt or setup
What you get
A spreadsheet-ready table of test cases with expected results, pass criteria, a baseline, and a ship rule.
Changelog
- v1.0.0 · Nov 4, 2026 · First release.
Sources
- Define success criteria and build evaluations - Claude Docs (2026-11-04)
- Evaluation best practices - OpenAI (2026-11-04)
- Skill authoring best practices - Claude Docs (2026-11-04)
Related skills
- Review an AI draft before use Reviews an AI-generated draft before use: claims to verify, possibly invented sources, tone and policy issues, gaps against the request, and a fix list.
- Context brief for an AI assistant Writes instructions for an AI assistant or agent: role, audience, can and can't, sources of truth, tools, format, examples, edge cases, and handoff.
- Prepare documents for AI search Prepares documents for an AI assistant that searches them: inventory, owners, stale copies removed, permissions, chunk-friendly sections, metadata, test questions.
- A/B test plan Writes an A/B test brief: hypothesis, primary and guardrail metrics, MDE, sample size and duration with the math, stop rules, and a decision rule set in advance.