# Few Shot Example Gen

> Few-shot example generation and optimization for improved LLM performance

- Skill: `a5c-ai/few-shot-example-gen` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add a5c-ai/few-shot-example-gen`
- Raw SKILL.md: https://api.skillmd.com/api/skills/a5c-ai/few-shot-example-gen/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: a5c-ai (https://skillmd.com/u/a5c-ai)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/a5c-ai/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)