Rag query transformation
Skill a5c-ai/babysitter/library/specializations/ai-agents-conversational/skills/rag-query-transformation
Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration
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Query expansion, HyDE, and multi-query generation for improved retrieval
SKILL.md
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RAG Query Transformation Skill
Capabilities
- Implement query expansion techniques
- Configure Hypothetical Document Embeddings (HyDE)
- Set up multi-query generation
- Design query decomposition strategies
- Implement step-back prompting
- Configure query routing for specialized indices
Target Processes
- advanced-rag-patterns
- knowledge-base-qa
Implementation Details
Transformation Techniques
- Multi-Query Generation: Generate query variations
- HyDE: Generate hypothetical answer, embed that
- Query Decomposition: Break complex queries into sub-queries
- Step-Back Prompting: Generate higher-level queries
- Query Expansion: Add synonyms and related terms
Configuration Options
- Number of query variations
- LLM for query generation
- Decomposition depth
- Query routing rules
- Result fusion strategy
Best Practices
- Match technique to query complexity
- Test with representative queries
- Monitor retrieval quality changes
- Balance latency vs quality tradeoffs
Dependencies
- langchain
- LLM provider