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testing
Agent Execution and Robustness Testing
Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.
Linked challenge: Perplexity-Powered Growth Intelligence Agent with OpenAI Agents SDK
Format
Text-first
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1
Sections
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Linked challenge
Perplexity-Powered Growth Intelligence Agent with OpenAI Agents SDK
Prompt source
Original prompt text with formatting preserved for inspection.
1 lines
1 sections
No variables
0 checklist items
Execute your agent with various `initial_goal` prompts (e.g., 'Find growth strategies for a sustainable fashion e-commerce brand targeting Gen Z', 'Identify untapped market segments for a cloud-based project management tool'). Monitor its execution flow, tool calls, and intermediate thoughts. Debug any issues related to API rate limits, parsing errors, or logical inconsistencies. Evaluate the precision of its opportunity identification (Precision@k) and the completeness of its citations. Ensure the agent can handle ambiguous prompts and still generate meaningful results. Test for resilience and error handling.
Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Preserve the rubric, target behavior, and pass-fail criteria as the baseline for evaluation.
Tune next
Adjust fixtures, mocks, and thresholds to the system under test instead of weakening the assertions.
Verify after
Make sure the prompt catches regressions instead of just mirroring the happy-path examples.