Build an Eval Suite for an Agent Before You Trust It
Create a structured evaluation set with test cases, scoring rubric, and pass thresholds so you measure an agent instead of vibe-checking it.
Replace "it seems to work" with repeatable evals that catch regressions when you change the prompt, model, or tools.
At a glance
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Prompt objective
Replace "it seems to work" with repeatable evals that catch regressions when you change the prompt, model, or tools.
Real use case
Every time the team tweaks the system prompt, something else quietly breaks. They need an eval suite they can run before shipping any change.
Customize these fields first
Replace the placeholders with your own context before you run the prompt. That usually improves the first output more than adding more instructions later.
Prompt
Act as an AI evaluation engineer. Build an evaluation suite for the agent described below. Agent purpose: [PURPOSE] Most important behaviors: [WHAT MUST IT GET RIGHT] Failure modes you fear most: [E.G. HALLUCINATION, WRONG TOOL, UNSAFE ACTION] Produce: 1. 12-20 test cases as a table: input, what a good output looks like, and which behavior/failure mode it targets. Include happy paths, edge cases, adversarial inputs, and out-of-scope requests. 2. A scoring rubric: for each case, define PASS criteria objectively (exact match, contains, must-not-contain, tool-called, escalated). 3. An LLM-as-judge prompt for the cases that need qualitative scoring, with a clear rubric and 1-5 scale anchored by examples. 4. Aggregate metrics to track (overall pass rate, per-category pass rate, regression flags). 5. A go/no-go threshold for shipping a change. Make the cases specific to this agent, not generic. Output the test table in a format easy to load into a test runner.
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How to use this prompt
- 1Replace the key placeholders first: PURPOSE, WHAT MUST IT GET RIGHT, E.G. HALLUCINATION, WRONG TOOL, UNSAFE ACTION.
- 2Replace any bracketed placeholders like [this] with your own context.
- 3Add extra background information when you want more tailored results.
- 4Combine multiple prompts in one conversation when you need a richer output.
- 5Save your best-performing prompts so they are easy to reuse later.
Next best step
Open the guide first, then branch only if you still need more.
A guide for technical builders choosing between prompts, coding workflows, and agent-based implementation.
If this prompt is close but not quite right, generate variants next. If the job is recurring, move into the course library after the guide.
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Every prompt here is free. The course teaches the thinking behind them.
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