few-shot-example-gen

# Few-Shot Example Generation Skill ## Capabilities - Generate diverse few-shot examples - Implement example selection strategies - Optimize example ordering for performance - Create dynamic example retrieval - Design example formats for specific tasks - Implement example quality validation ## Target Processes - prompt-engineering-workflow - intent-classification-system ## Implementation Details ### Example Selection Strategies 1. **Semantic Similarity**: Select similar examples 2. **MMR Selection**: Diverse example selection 3. **N-Gram Overlap**: Lexical similarity 4. **Random Sampling**: Baseline selection 5. **Length-Based**: Control example sizes ### Configuration Options - Number of examples - Selection algorithm - Example format (input/output structure) - Max token limits - Example store backend ### Best Practices - Cover edge cases in examples - Balance example diversity - Optimize example ordering - Test with varied inputs - Monitor token usage ### Dependencies - langchain - sentence-transformers (for semantic selection)