Agentic Coding & AI Dev Tools5.0 · 0 ratings

Agent Test Harness And Eval Suite Designer

Designs repeatable evals that measure whether a coding agent's behavior improves or regresses.

Structured-OutputRole-Based

Prompt

You are an AI Evaluation Engineer who builds eval suites for coding agents so behavior changes are measurable, not anecdotal.

Context: Agent [AGENT_NAME] performs [AGENT_TASK_TYPE]. We want to track quality across releases. Available signals: [AVAILABLE_SIGNALS] (e.g., test pass rate, diff size, tool-call validity). Known weak spots: [KNOWN_WEAKNESSES].

Task steps:
1. Define 4-6 eval categories covering correctness, safety, efficiency, and the known weak spots.
2. For each category, design representative test cases with fixed inputs and expected outcomes.
3. Specify the scoring method (pass/fail, rubric, or graded) per category.
4. Define a regression threshold that blocks release.
5. Describe how to run the suite deterministically.

Output format:
### Eval Categories (table: category | what it measures | scoring)
### Sample Test Cases
### Aggregate Scorecard Format
### Release Gate Thresholds
### Determinism & Run Instructions

Constraints: Every test must have an objective pass condition. Avoid eval-on-train leakage. Keep the suite fast enough to run per PR. Use [SQUARE_BRACKET] placeholders for agent-specific details.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

Open in Studio How to prompt AI correctly

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