使用 Bright Data CLI（`brightdata` / `bdata`）從終端機中抓取網站、搜尋網路、從 40 多個平台提取結構化資料、管理代理區域及檢查帳戶預算的指南。
此技能引導使用者透過 Bright Data CLI（`brightdata` / `bdata`）來操作全面的網路數據收集。它支援抓取任意 URL、使用 SERP API 搜尋 Google/Bing/Yandex 等搜尋引擎，並從 Amazon、LinkedIn、Instagram、TikTok、YouTube、Reddit 等 40 多個熱門平台提取結構化資料。除了抓取功能外，此技能還能管理代理區域、檢查帳戶餘額，並將 Bright Data 工具整合到 AI 編碼代理（如 Claude Code、Cursor、Codex）中。當使用者提到 brightdata、bdata、網路抓取 CLI、SERP API，或需要從終端機進行任何網路數據收集任務時，應自動觸發此技能。它提供清晰的指令，說明如何安裝、設定 API 金鑰，並執行 CLI 命令以高效地從結構化和非結構化網頁來源獲取數據。
npx skills add https://github.com/brightdata/skills/tree/main/skills/brightdata-cliInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
使用 Bright Data CLI（brightdata / bdata）來抓取網站、搜尋網路、從 40 多個平台提取結構化資料、管理代理區域及檢查帳戶預算的指南。當使用者想要抓取 URL、搜尋 Google/Bing/Yandex、從 Amazon/LinkedIn/Instagram/TikTok/YouTube/Reddit 或任何其他平台提取資料、檢查 Bright Data 餘額或區域，或執行任何與終端機網路資料收集相關的操作時，請使用此技能。當使用者提到 brightdata、bdata、網路抓取 CLI、SERP API，或想要將 Bright Data 技能安裝到他們的編碼代理時，也請觸發此技能。
This repo contains 3 individual skills — each has its own dedicated page.
Build production-ready Bright Data integrations with best practices baked in. Reference documentation for developers using coding assistants (Claude Code, Cursor, etc.) to implement web scraping, search, browser automation, and structured data extraction. Covers Web Unlocker API, SERP API, Web Scraper API, and Browser API (Scraping Browser).
Scrape web content as clean markdown/HTML/JSON via the Bright Data CLI (`bdata scrape`). Use when the user wants to fetch a page, extract content from a list of URLs, or crawl paginated listings. Hands off to `data-feeds` for supported platforms (Amazon, LinkedIn, TikTok, Instagram, YouTube, Reddit, etc.) and to `search` when URLs must be discovered first. Requires the Bright Data CLI; proactively guides install + login if missing.
When the user wants to audit, review, or diagnose SEO issues on their site. Uses live web data via the Bright Data CLI for accurate detection of JS-injected schema, hreflang, canonicals, and live SERP-based ranking checks. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. For building pages at scale to target keywords, see programmatic-seo. For implementing structured data, see schema-markup. For AI search optimization, see ai-seo.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.