Agent-Skills.md

Agent Skills: LangChain Retriever Skill

LangChain retriever implementation with various retrieval strategies for RAG applications

UncategorizedID: a5c-ai/babysitter/langchain-retriever

Repository

a5c-ai/babysitter
a5c-aiLicense: MIT
244

Install this agent skill to your local

pnpm dlx add-skill https://github.com/a5c-ai/babysitter/tree/HEAD/library/specializations/ai-agents-conversational/skills/langchain-retriever

Skill Files

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library/specializations/ai-agents-conversational/skills/langchain-retriever/SKILL.md

Skill Metadata

Name
langchain-retriever
Description
LangChain retriever implementation with various retrieval strategies for RAG applications

LangChain Retriever Skill

Capabilities

  • Implement various LangChain retriever types
  • Configure vector store retrievers
  • Set up multi-query retrievers for improved recall
  • Implement contextual compression retrievers
  • Design ensemble retrievers combining multiple strategies
  • Configure self-query retrievers for structured filtering

Target Processes

  • rag-pipeline-implementation
  • advanced-rag-patterns

Implementation Details

Retriever Types

  1. VectorStoreRetriever: Basic similarity search
  2. MultiQueryRetriever: Generates query variations
  3. ContextualCompressionRetriever: Filters and compresses results
  4. EnsembleRetriever: Combines multiple retrievers
  5. SelfQueryRetriever: Structured metadata filtering
  6. ParentDocumentRetriever: Returns parent chunks

Configuration Options

  • Search type (similarity, mmr, similarity_score_threshold)
  • Number of documents to retrieve (k)
  • Score thresholds
  • Metadata filtering
  • Compression settings

Dependencies

  • langchain
  • langchain-community
  • Vector store client