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RAG pipeline: chunking, indexing and hybrid search v1.0.0

Use this resource to build a document retrieval pipeline for an AI assistant

New

  • 400 downloads
  • 148 likes
  • 144 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install rag-retrieval-pipeline-implementation

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent picks the chunking strategy and embedding model, configures the vector store and hybrid search, then sets up quality evaluation. You get a RAG pipeline and an evaluation grid.

Mostly picked by

Updated November 2, 2026

Card for the “RAG pipeline: chunking, indexing and hybrid search” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
MIT

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What you get

  • SKILL.md: overview, quick reference and common mistakes
  • references/chunking-strategies.md: chunking strategies
  • references/retrieval-methods.md: retrieval methods
  • references/evaluation.md: quality evaluation

Good fit for

  • Your assistant must answer from your internal documents
  • Your current RAG misses relevant passages

Not for

    Tags

    • rag
    • embeddings
    • vectors
    • search
    • evaluation

    About

    You say

    “Set up a RAG over my product sheets: section-based chunking, hybrid search and a relevance test set.”

    Card for the “RAG pipeline: chunking, indexing and hybrid search” skill

    Skill published by oakoss under the MIT license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to build a document retrieval pipeline for an AI assistant
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.3 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/architecture-patterns.md3.7 KB
    • references/chunking-strategies.md4.5 KB
    • references/evaluation.md2 KB
    • references/production-deployment.md2.3 KB
    • references/retrieval-methods.md15.4 KB
    • SKILL.md11.2 KB

    Origin and licence

    Listed unmodified

    Author
    oakoss
    Source
    github.com/oakoss/agent-skills/tree/85e3a3919d9e0ec7f7302a5143ec4b3e66f5f6ad/skills/rag-implementer
    Licence
    MIT

    Notice

    « rag-implementer » (oakoss, MIT) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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