RAG Query Transformation Skill

SkillAI & models

Query expansion, HyDE, and multi-query generation for improved retrieval

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the RAG Query Transformation Skill skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/ai-agents-conversational/skills/rag-query-transformation/SKILL.md and read by ahel’s review.

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

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: rag-query-transformation
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter

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