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rag-pipeline

Skill

Build a RAG (retrieval-augmented generation) pipeline or a custom search engine on top of Bright Data's Discover API — using intent-ranked web results + parsed page content as the retrieval/ingestion layer for an LLM or vector store. Use when the user wants to "build a RAG pipeline", "add web search

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Install

git clone https://github.com/brightdata/skills.git ~/.claude/skills/rag-pipeline

What is rag-pipeline?

Build a RAG (retrieval-augmented generation) pipeline or a custom search engine on top of Bright Data's Discover API — using intent-ranked web results + parsed page content as the retrieval/ingestion layer for an LLM or vector store. Use when the user wants to "build a RAG pipeline", "add web search to my LLM/agent", "ground my model in live web data", "build a search engine over the web", "ingest web content into a vector DB / knowledge base", or "give my chatbot retrieval". Covers both live retrieval (Discover at query time as a web-grounded retriever) and ingestion (Discover → chunk → embed → vector store → retrieve). Built on the `discover-api` skill. For a one-off written report use `live-research`; for raw markdown of specific known URLs use `scrape`.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~192 tokens of context used while enabled, before you invoke anything

Documentation

README · ~4 min read

Bright Data — RAG / Search-Engine Pipeline

Use Discover as the retrieval layer for an LLM app or a custom search engine. Discover already returns intent-ranked, relevance-scored results with parsed page content, so it does the "search + fetch + clean" stage of RAG for you. This is a code/architecture skill built on the discover-api skill — read that for API mechanics (trigger/poll, modes, params, limits).

Pick the right neighbor: a written brief → live-research; markdown of specific URLs you already have → scrape; structured platform records → data-feeds.

Two architectures — choose first

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