/few-shot-example-gen

name: few-shot-example-gen
description: Few-shot example generation and optimization for improved LLM performance
allowed-tools:
  - Read
  - Write
  - Edit
  - Bash
  - Glob
  - Grep
graph:
  domains: [domain:software-engineering]
  specializations: [specialization:ai-agents-conversational]
  skillAreas: [skill-area:prompt-engineering, skill-area:prompt-instruction-tuning-agents]
  roles: [role:ml-engineer, role:backend-engineer]
  workflows: [workflow:ml-model-lifecycle, workflow:feature-development]

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)