Individual skill
agent-eval-harness
Use to test whether an AI agent, prompt, or skill actually works before or after it ships — build a small eval set, score runs, and catch regressions when the prompt or model changes. Trigger when the user asks whether a prompt is good, wants to compare models or versions, sees inconsistent agent output, or is about to put an agent in front of customers.
agent-eval-harness/SKILL.md
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- Last checked
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- agent-skills Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude Repository topic
- claude-code Repository topic
- claude-skills Repository topic
- developer-tools Repository topic
- llm Repository topic
- prompt-engineering Repository topic
- sales-automation Repository topic
- testing Derived category
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# Agent Eval Harness
Prompts are edited by vibe and shipped on hope. Then a model version changes and nobody finds out until a customer does. An eval set is the cheapest insurance in AI work: twenty cases, one script, run it every time anything changes.
## Core Behavior
Build the smallest eval that would catch a real regression. Twenty cases you run every change beats two hundred you run once.
## Step 1 — Define Pass
Before writing cases, write the pass condition. Vague quality goals produce vague evals. Good conditions are checkable:
- Output is valid JSON matching this shape.
- The answer contains the correct figure from the source document.