ReddRadar
Agent skill
few-shot-example-gen
Few-shot example generation and optimization for improved LLM performance
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/ai-agents-conversational/skills/few-shot-example-gen
SKILL.md
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
- Semantic Similarity: Select similar examples
- MMR Selection: Diverse example selection
- N-Gram Overlap: Lexical similarity
- Random Sampling: Baseline selection
- 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)
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