Onboard an agent to Bright Data. Use when a coding agent first encounters Bright Data — for live web work (search, scrape, structured data), for wiring Bright Data into product code, for installing the agent skill bundle, or for getting an API key. One install command sets up the CLI, agent skills, and authentication. Routes the reader to the right path: live tools, app integration, MCP, auth-only, or direct REST without any install.
Guide for using the Bright Data CLI (`brightdata` / `bdata`) to scrape websites, search the web, extract structured data from 40+ platforms, manage proxy zones, and check account budget. Use this skill whenever the user wants to scrape a URL, search Google/Bing/Yandex, extract data from Amazon/LinkedIn/Instagram/TikTok/YouTube/Reddit or any other platform, check their Bright Data balance or zones, or do anything involving web data collection from the terminal. Also trigger when the user mentions brightdata, bdata, web scraping CLI, SERP API, or wants to install Bright Data skills into their coding agent.
Generate working code that routes HTTP requests through Bright Data proxy networks (Datacenter, ISP, Residential, Mobile) and help users decide which network and IP pool type to use (shared pool, shared IPs, or dedicated IPs). Use this skill whenever the user mentions Bright Data, brightdata.com, BD proxies, brd.superproxy.io, geo.brdtest.com, a brd-customer- proxy username, a Bright Data zone, the superproxy host, or wants to scrape or route requests through Bright Data — including questions about proxy URL format, country or session or IP or sticky-session targeting, SSL certificate setup for residential or mobile proxies, KYC verification, ignoring SSL errors, choosing between shared pool and shared IPs and dedicated IPs, or integrating Bright Data into Python requests/httpx/aiohttp, Node fetch/axios, Playwright, Puppeteer, Selenium, or Scrapy.
Use Bright Data's Discover API — intent-ranked, AI-relevance-scored web search at scale (not keyword SERP). Trigger a discovery job and retrieve ranked results (link, title, description, relevance_score) with optional parsed page content. Use when the user wants semantic/intent-based web search, "find pages about <topic> that match <goal>", web-grounded retrieval for an LLM, or results filtered by relevance rather than raw keyword rank. Covers the REST API (POST/GET /discover), the CLI (`bdata discover`), and the Python/JS SDKs (`client.discover`), including the standard/zeroRanking/deep/fast modes. This is the foundation skill for `live-research` and `rag-pipeline`. For keyword SERP use `search`; for structured platform data use `data-feeds`.
Web data extraction and discovery using the Bright Data JavaScript/TypeScript SDK (`@brightdata/sdk`). Use when the user is working in Node.js/TypeScript and asks to "scrape", "get data from", "extract", "search for", or "find" information from websites. Also use when the user mentions specific platforms like Amazon, LinkedIn, Instagram, Facebook, TikTok, YouTube, Reddit, Pinterest, ChatGPT, Perplexity, or DigiKey, or asks for "bulk data", "historical data", or "dataset" from JS. Covers scraping, SERP search, AI discovery, datasets, browser automation, and Scraper Studio. For Python, use brightdata-sdk; for the terminal CLI, use brightdata-cli.
Produce a deep, multi-source, cited research brief on a topic from live web data using Bright Data's Discover API (intent-ranked web search + parsed page content). Use when the user wants "live research", to "research <topic> deeply", "research the latest on", "write a report on", "give me a briefing / literature review / market scan", "find and synthesize everything about", or otherwise wants a synthesized, source-grounded answer rather than a list of links. Decomposes the question into multiple intent-ranked Discover queries, pulls page content, deduplicates and ranks by relevance, then synthesizes a structured brief with inline citations. Built on the `discover-api` skill. For competitor-specific intel use `competitive-intel`; for social/brand sentiment use `brand-listening`; for a retrieval *system* (not a one-off report) use `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`.
Build and run AI-generated Bright Data scrapers from the terminal via `bdata scraper create` and `bdata scraper run`. Use this skill whenever the user wants to generate a scraper from a natural-language description, build a custom scraper without writing code, turn a URL + plain-English description into a reusable scraper, run an existing Bright Data collector against a URL, or batch-scrape a list of URLs through one collector. Triggers on phrases like 'build me a scraper for', 'create a scraper that extracts', 'generate a scraper from a description', 'turn this URL into a scraper', 'run this scraper on', 'run my collector', 'batch scrape', 'scrape these URLs', 'scrape a list of URLs', 'competitive pricing table', 'scraper studio', `scraper create`, `scraper run`, `--urls`, `--input-file`, `collector_id`, `automate_template`, or `/dca/`. Covers the AI flow (template create → trigger AI generation → poll progress), the single-URL run flow (async + poll by default, `--sync` for fast pages), the multi-URL batch