Erstellen Sie produktionsreife Bright Data-Integrationen mit integrierten Best Practices. Referenzdokumentation für Entwickler, die Coding-Assistenten (Claude Code, Cursor usw.) zur Implementierung von Web Scraping, Suche, Browserautomatisierung und strukturierter Datenextraktion verwenden. Deckt Web Unlocker API, SERP API, Web Scraper API und Browser API (Scraping Browser) ab.
Diese Skill-Datei dient als umfassende Referenz für Entwickler, die mit Coding-Assistenten wie Claude Code oder Cursor produktionsreife Bright Data-Integrationen erstellen möchten. Sie bietet Best Practices für Web Scraping, strukturierte Datenextraktion, Browserautomatisierung und Suchabfragen. Der Skill deckt die wichtigsten Bright Data-APIs ab: Web Unlocker API (für das Umgehen von Anti-Bot-Schutz), SERP API (für die Extraktion von Suchmaschinenergebnissen), Web Scraper API (für das Crawlen von Webseiten) und Browser API/Scraping Browser (für browserbasierte Automatisierung). Er hilft Entwicklern, effiziente und wartbare Integrationen zu schreiben, indem er gängige Fallstricke vermeidet, Authentifizierungsmechanismen erklärt, API-Endpunkte beschreibt und bewährte Codierungsmuster für verschiedene Programmiersprachen bereitstellt. Die Datei ist sowohl für Einsteiger als auch für erfahrene Bright Data-Nutzer als verlässliche Informationsquelle konzipiert.
npx skills add https://github.com/brightdata/skills/tree/main/skills/bright-data-best-practicesInstalled? Explore more Recherche & Datenanalyse skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
Erstellen Sie produktionsreife Bright Data-Integrationen mit integrierten Best Practices. Referenzdokumentation für Entwickler, die Coding-Assistenten (Claude Code, Cursor usw.) zur Implementierung von Web Scraping, Suche, Browserautomatisierung und strukturierter Datenextraktion verwenden. Deckt Web Unlocker API, SERP API, Web Scraper API und Browser API (Scraping Browser) ab.
This repo contains 3 individual skills — each has its own dedicated page.
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.
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.