soft_comparative_step_task_memory_prompt: |
  You are an expert AI analyst comparing higher-scoring and lower-scoring step sequences to extract performance insights.

  Your task is to identify the key differences between higher and lower performing approaches at the step level.
  Focus on what made the higher-scoring approach more effective, even when both approaches may have had partial success.

  SOFT COMPARATIVE ANALYSIS FRAMEWORK:
  ● PERFORMANCE FACTORS: Identify what specifically contributed to the higher score
  ● APPROACH DIFFERENCES: Compare methodologies and execution strategies
  ● EFFICIENCY ANALYSIS: Analyze why one approach was more efficient or effective
  ● OPTIMIZATION INSIGHTS: Extract lessons for improving performance

  EXTRACTION PRINCIPLES:
  ● Focus on INCREMENTAL IMPROVEMENTS and performance optimization
  ● Extract QUALITY INDICATORS that differentiate better vs good approaches
  ● Identify REFINEMENT STRATEGIES that lead to higher scores
  ● Frame insights as PERFORMANCE ENHANCEMENT guidelines

  # Higher-Scoring Step Sequence (Score: {higher_score})
  {higher_steps}

  # Lower-Scoring Step Sequence (Score: {lower_score})
  {lower_steps}


  OUTPUT FORMAT:
  Generate 1-2 performance improvement insights as JSON objects:
  ```json
  [
    {{
      "when_to_use": "Specific scenarios where this performance insight applies",
      "experience": "Detailed analysis of what made the higher-scoring approach more effective",
      "tags": ["performance_optimization", "score_improvement", "relevant_keywords"],
      "confidence": 0.7,
      "step_type": "reasoning|action|observation|decision",
      "tools_used": ["list", "of", "tools"]
    }}
  ]
  ```

hard_comparative_step_task_memory_prompt: |
  You are an expert AI analyst comparing successful and failed step sequences to extract differential insights.

  Your task is to identify the key differences between success and failure patterns at the step level.
  Focus on critical decision points, technique variations, and approach differences.

  COMPARATIVE ANALYSIS FRAMEWORK:
  ● DECISION CONTRAST: Compare critical decisions made in success vs failure cases
  ● TECHNIQUE VARIATIONS: Identify different approaches and their outcomes
  ● TIMING DIFFERENCES: Analyze when certain actions were taken and their impact
  ● SUCCESS FACTORS: Extract what specifically made the difference

  EXTRACTION PRINCIPLES:
  ● Frame comparisons as PRINCIPLES as well as case-specific SOLUTIONS
  ● Identify PATTERNS that differentiate effective vs ineffective approaches
  ● Extract RULES that can guide future similar situations
  ● Focus on UNDERLYING MECHANISMS rather than surface-level differences

  # Successful Step Sequence
  {success_steps}

  # Failed Step Sequence
  {failure_steps}

  # Similarity Score: {similarity_score}

  OUTPUT FORMAT:
  Generate 1-2 comparative insights as JSON objects:
  ```json
  [
    {{
      "when_to_use": "Specific scenarios where this comparative insight applies",
      "experience": "Detailed comparison highlighting why success approach works better",
      "tags": ["comparative_analysis", "success_factors", "relevant_keywords"],
      "confidence": 0.8,
      "step_type": "reasoning|action|observation|decision"
    }}
  ]
  ```