# Agentic Hybrid RAG

> Classify each request as non-retrieval, single-step, or multi-step, then execute the smallest suitable grounded RAG workflow with optional rewriting, reranking, and critique.

- Skill: `docailab/agentic-hybrid-rag` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add docailab/agentic-hybrid-rag`
- Raw SKILL.md: https://api.skillmd.com/api/skills/docailab/agentic-hybrid-rag/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: DocAILab (https://skillmd.com/u/docailab)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/docailab/agentic-hybrid-rag

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# Hybrid Agentic RAG

Use the fixed classifier in `complexity` mode before execution.

## Slots

- `classifier`: select `component-classifier`.
- `retriever`: select one retriever.
- `rewriter`: optional retrieval-query rewriter.
- `reranker`: optional evidence reranker.
- `generator`: select grounded generator.
- `critic`: select answer critic for multi-step execution.

## Routes

- `non-retrieval`: call the Generator with the original query and no documents.
- `single-step`: optionally rewrite the query, retrieve once, optionally rerank, then generate.
- `multi-step`: repeatedly retrieve, accumulate new documents, optionally rerank, generate, and critique until approved, no new evidence, or `max_iterations` is reached.

Always use the original query for generation, reranking, and critique. Rewritten queries are retrieval aids only. Classifier output and generated rewrites are never evidence.

Run `scripts/workflow.py:run(request, components)` after all required slots are bound.