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RAG or search engine pipeline over the web v1.0.0

Use this resource to build a RAG pipeline or a search engine fed by the web

New

  • 353 downloads
  • 186 likes
  • 214 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install web-grounded-rag-pipeline

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 chooses between live retrieval at query time and ingestion into a vector database, then writes the code and its verification. You get a search architecture that grounds answers in recent web pages.

Mostly picked by

Updated November 2, 2026

Card for the “RAG or search engine pipeline over the web” skill

Details

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

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What you get

  • SKILL.md: two architectures, design rules and verification gates
  • references/code.md: pipeline code examples

Good fit for

  • Your agent must answer from recent web data
  • You want to index web pages into a knowledge base

Not for

    Tags

    • rag
    • llm
    • search

    About

    You say

    “Add web search to my chatbot: live retrieval, with cited sources.”

    Card for the “RAG or search engine pipeline over the web” skill

    Skill published by brightdata 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 RAG pipeline or a search engine fed by the web
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1.1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/code.md10.3 KB
    • SKILL.md7.5 KB

    Origin and licence

    Listed unmodified

    Author
    brightdata
    Source
    github.com/brightdata/skills/tree/37503c1ba31056370323a9d5ba88dd003a280008/skills/rag-pipeline
    Licence
    MIT

    Notice

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

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