/rag-retrieval

name: rag-retrieval
license: MIT
compatibility: "Claude Code 2.1.277+."
description: Retrieval-Augmented Generation patterns for grounded LLM responses. Use when building RAG pipelines, embedding documents, implementing hybrid search, contextual retrieval, HyDE, agentic RAG, multimodal RAG, query decomposition, reranking, or pgvector search.
user-invocable: false
disable-model-invocation: true
effort: high
metadata:
  owner-agent: "data-pipeline-engineer"
  category: mcp-enhancement
  version: "2.0.0"
  author: "OrchestKit"
  complexity: "high"
  tags: "rag, retrieval, llm, context, grounding, embeddings, hyde, reranking, pgvector, multimodal"
allowed-tools: "Read Glob Grep WebFetch WebSearch"
path_patterns: ["**/rag/**", "**/retrieval/**", "**/embeddings/**", "**/vector/**"]

RAG Retrieval

Comprehensive patterns for building production RAG systems. Each category has individual rule files in `rules/` loaded on-demand.

House thresholds, fusion ordering, and the latency and quality budgets we assert live in [House delta](#house-delta) below. Vendor documentation is linked, not restated (see [Upstream coverage](#upstream-coverage-do-not-restate)).

Quick Reference

| Category | Rules | Impact | When to Use | |----------|-------|--------|-------------| | [Core RAG](#core-rag) | 4 | CRITICAL | Basic RAG, citations, hybrid search, context management | | [Embeddings](#embeddings) | 3 | HIGH | Model selection, chunking, batch/cache optimization | | [Contextual Retrieval](#contextual-retrieval) | 3 | HIGH | Context-prepending, hybrid BM25+vector, pipeline | | [HyDE](#hyde) | 3 | HIGH | Vocabulary mismatch, hypothetical document generation | | [Agentic RAG](#agentic-rag) | 4 | HIGH | Self-RAG, CRAG, knowledge graphs, adaptive routing | | [Multimodal RAG](#multimodal-rag) | 3 | MEDIUM | Image+text retrieval, PDF chunking, cross-modal search | | [Query Decomposition](#query-decomposition) | 3 | MEDIUM | Multi-concept queries, parallel retrieval, RRF fusion | | [Reranking](#reranking) | 3 | MEDIUM | Cross-encoder, LLM scoring, combined signals | | [PGVector](#pgvector) | 4 | HIGH | PostgreSQL hybrid search, HNSW indexes, schema design |

**Total: 30 rules across 9 categories**

Core RAG

Fundamental patterns for retrieval, generation, and pipeline composition.

| Rule | File | Key Pattern | |------|------|-------------| | Basic RAG | `rules/core-basic-rag.md` | Retrieve + context + generate with citations | | Hybrid Search | `rules/core-hybrid-search.md` | RRF fusion (k=60) for semantic + keyword | | Context Management | `rules/core-context-management.md` | Token budgeting + sufficiency check | | Pipeline Composition | `rules/core-pipeline-composition.md` | Composable Decompose → HyDE → Retrieve → Rerank |

Embeddings

Embedding models, chunking strategies, and production optimization.

| Rule | File | Key Pattern | |------|------|-------------| | Models & API | `rules/embeddings-models.md` | Model selection, batch API, similarity | | Chunking | `rules/embeddings-chunking.md` | Semantic boundary splitting, 512 token sweet spot | | Advanced | `rules/embeddings-advanced.md` | Redis cache, Matryoshka dims, batch processing |

Contextual Retrieval

Anthropic's context-prepending technique — 67% fewer retrieval failures.

| Rule | File | Key Pattern | |------|------|-------------| | Context Prepending | `rules/contextual-prepend.md` | LLM-generated context + prompt caching | | Hybrid Search | `rules/contextual-hybrid.md` | 40% BM25 / 60% vector weight split | | Complete Pipeline | `rules/contextual-pipeline.md` | End-to-end indexing + hybrid retrieval |

HyDE

Hypothetical Document Embeddings for bridging vocabulary gaps.

| Rule | File | Key Pattern | |------|------|-------------| | Generation | `rules/hyde-generation.md` | Embed hypothetical doc, not query | | Per-Concept | `rules/hyde-per-concept.md` | Parallel HyDE for multi-topic queries | | Fallback | `rules/hyde-fallback.md` | 2-3s timeout → direct embedding fallback |

Agentic RAG

Self-correcting retrieval with LLM-driven decision making.

| Rule | File | Key Pattern | |------|------|-------------| | Self-RAG | `rules/agentic-self-rag.md` | Binary document grading for relevance | | Corrective RAG | `rules/agentic-corrective-rag.md` | CRAG workflow with web fallback | | Knowledge Graph | `rules/agentic-knowledge-graph.md` | KG + vector hybrid for entity-rich domains | | Adaptive Retrieval | `rules/agentic-adaptive-retrieval.md` | Query routing to optimal strategy |

Multimodal RAG

Image + text retrieval with cross-modal search.

| Rule | File | Key Pattern | |------|------|-------------| | Embeddings | `rules/multimodal-embeddings.md` | CLIP, SigLIP 2, Voyage multimodal-3 | | Chunking | `rules/multimodal-chunking.md` | PDF extraction preserving images | | Pipeline | `rules/multimodal-pipeline.md` | Dedup + hybrid retrieval + generation |

Query Decomposition

Breaking complex queries into concepts for parallel retrieval.

| Rule | File | Key Pattern | |------|------|-------------| | Detection | `rules/query-detection.md` | Heuristic indicators (<1ms fast path) | | Decompose + RRF | `rules/query-decompose.md` | LLM concept extraction + parallel retrieval | | HyDE Combo | `rules/query-hyde-combo.md` | Decompose + HyDE for maximum coverage |

Reranking

Post-retrieval re-scoring for higher precision.

| Rule | File | Key Pattern | |------|------|-------------| | Cross-Encoder | `rules/reranking-cross-encoder.md` | ms-marco-MiniLM (~50ms, free) | | LLM Reranking | `rules/reranking-llm.md` | Batch scoring + Cohere API | | Combined | `rules/reranking-combined.md` | Multi-signal weighted scoring |

PGVector

Production hybrid search with PostgreSQL.

| Rule | File | Key Pattern | |------|------|-------------| | Schema | `rules/pgvector-schema.md` | HNSW index + pre-computed tsvector | | Hybrid Search | `rules/pgvector-hybrid-search.md` | SQLAlchemy RRF with FULL OUTER JOIN | | Indexing | `rules/pgvector-indexing