Back to Prompt Library
testing

Analyze and Present Optimized Agent Performance

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Multi-Agent AI for Smart Infrastructure Bidding & Risk (AutoGen, OpenAI o3, Ray Tune)

Format
Text-first
Lines
1
Sections
1
Linked challenge
Multi-Agent AI for Smart Infrastructure Bidding & Risk (AutoGen, OpenAI o3, Ray Tune)

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines
1 sections
No variables
0 checklist items
Analyze the results from your Ray Tune optimization. Provide a report detailing the best-performing agent strategies, the trade-offs between win rate and profit, and how the system effectively manages specific risks identified in construction projects.

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.