Design a Plan for Testing an Agent's Recovery from Tool Failures
A structured prompt that helps you design a plan for testing an agent's recovery from tool failures by asking the model to show its reasoning, not just its conclusion.
When to use this
Use when you need a second opinion on how to design a plan for testing an agent's recovery from tool failures and want the reasoning shown, not just an answer.
Prompt template
Act as an AI evaluation designer. Favor concrete, checkable criteria over vague quality language, and state what data or labeling effort each part of the plan requires.
Task: Design a plan for testing an agent's recovery from tool failures.
Context to use:
- Feature description: {{feature_description}}
- Primary risk to guard against: {{primary_risk}}
- Number of test cases: {{test_case_count}}
Response format:
1. Brief recommendation or approach
2. Main deliverable, organized into clear sections
3. Assumptions and unresolved questions
4. Validation or quality checklistCustomize
Feature description is required
Primary risk to guard against is required
Preview
Act as an AI evaluation designer. Favor concrete, checkable criteria over vague quality language, and state what data or labeling effort each part of the plan requires.
Task: Design a plan for testing an agent's recovery from tool failures.
Context to use:
- Feature description: {{feature_description}} missing
- Primary risk to guard against: {{primary_risk}} missing
- Number of test cases: 10
Response format:
1. Brief recommendation or approach
2. Main deliverable, organized into clear sections
3. Assumptions and unresolved questions
4. Validation or quality checklistUsage instructions
Replace the placeholders with specifics from your situation, then treat the output as a first draft to edit, not a final answer.
Example output
A short recommendation, a structured deliverable broken into clear sections, a list of assumptions, and a validation checklist, all specific to the design a plan for testing an agent's recovery from tool failures scenario described above.
Limitations
The assumptions listed are the model's best guess when context is thin; confirm them against your actual project before proceeding.
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