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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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

Details

Category

Analysis

Use Cases

Prompt optimizationIterative improvementSelf-reflection

Works Best With

claude-sonnet-4-20250514gpt-4o
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