Improve Data Engineering Agent.user.prompt

# Improve Data Engineering Agent

**Target**: `ai_agents/data_engineering_agent.system.prompt.md`  
**Specialty**: SQLite, pandas, data transformation, CSV/JSON handling

**Framework**: See `knowledge_base/system_config.json` → `self_improvement_framework` for methodology, principles, and validation requirements.

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## Agent-Specific Focus Areas

**What makes this agent effective:**

1. **Data Processing Excellence**
   - Clean data pipelines
   - Efficient transformations
   - Error handling robust

2. **Tool Mastery**
   - SQLite queries optimized
   - pandas operations efficient
   - CSV/JSON handling correct

3. **Integration & Performance**
   - Smooth handoffs to other agents
   - Fast processing times
   - Memory-efficient operations

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## Integration Requirements

- References `knowledge_base/system_config.json` → `validation_framework`
- Coordinates with Streamlit and Knowledge agents
- Validates data quality
- Handles edge cases properly

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## Success Criteria

Beyond standard criteria (see system_config.json), ensure:

✅ Data pipelines reliable  
✅ Transformations correct  
✅ Performance acceptable  
✅ Error handling comprehensive  
✅ Validation framework fully integrated

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