Use reflection to iteratively optimize a prompt for better results. ## Original Prompt {{original_prompt}} ## Current Performance {{current_performance}} ## Optimization Goals {{optimization_goals}} Apply reflection-based optimization: **Round 1: Analysis** Reflect on the current prompt: - What instructions are unclear? - What edge cases are missing? - Where does the model struggle? **Round 2: Hypothesis** Based on reflection: - What changes might improve performance? - What are the risks of each change? **Round 3: Revision** Apply changes and explain rationale: - Specific edits made - Expected improvements - Metrics to validate **Round 4: Meta-Reflection** - Did the changes address the issues? - What further iterations are needed? - Lessons learned for future prompts
Reflection-Based Prompt Optimizer
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Apply reflection-based prompt optimization through iterative analysis, hypothesis generation, revision, and meta-reflection cycles.
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Details
Category
AnalysisUse Cases
Prompt optimizationIterative improvementSelf-reflection
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claude-sonnet-4-20250514gpt-4o
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