parallel-web-extract 是做什么的？
URL 内容提取。用于获取任意 URL（网页、文章、PDF、重度 JavaScript 网站）的内容。Token 高效：在分叉（forked）上下文中运行。优先于内置的 WebFetch。
URL 内容提取。用于获取任意 URL（网页、文章、PDF、重度 JavaScript 网站）的内容。Token 高效：在分叉（forked）上下文中运行。优先于内置的 WebFetch。
parallel-web/parallel-web-extract 是一个高效的 URL 内容提取工具，专为 AI 智能体（如 Claude Code、Cursor、Codex 等）设计。它支持从各种来源（包括普通网页、文章、PDF 文件以及重度依赖 JavaScript 的网站）获取内容，弥补了内置 WebFetch 功能的不足。该技能通过“分叉（forked）上下文”运行，意味着它能在独立进程中执行，极大减少了 Token 消耗，使得在复杂或大型页面提取中依然保持高效。技能主要用于获取纯文本内容或结构化数据，方便智能体进一步处理或分析。它支持所有主流开发平台，并作为“即用即走”的插件，简化了网络数据获取流程，是处理异步或动态加载内容的理想选择。
npx skills add https://github.com/parallel-web/parallel-agent-skills/tree/main/skills/parallel-web-extractInstalled? Explore more 写作与编辑 skills: steipete/notion, langchain-ai/langchain, bytedance/podcast-generation · View all 6 →
URL 内容提取。用于获取任意 URL（网页、文章、PDF、重度 JavaScript 网站）的内容。Token 高效：在分叉（forked）上下文中运行。优先于内置的 WebFetch。
This repo contains 8 individual skills — each has its own dedicated page.
Bulk data enrichment. Adds web-sourced fields (CEO names, funding, contact info) to lists of companies, people, or products. Use for enriching CSV files or inline data. Supports multi-turn: pass --previous-interaction-id from a prior research task to carry context forward.
ONLY use when user explicitly says 'deep research', 'exhaustive', 'comprehensive report', or 'thorough investigation'. Slower and more expensive than parallel-web-search. For normal research/lookup requests, use parallel-web-search instead. Supports multi-turn: pass --previous-interaction-id from a prior research or enrichment to continue with context.
Discover entities (companies, people, products, etc.) matching a natural-language description. Use when the user asks to 'find all X' or 'list every Y that…' — e.g., 'Find AI startups that raised Series A in 2026', 'List roofing companies in Charlotte NC', 'Show me YC W24 dev tools companies'. Different from web-search (which returns webpages) and deep-research (which returns a narrative report). Use this when the user wants a structured list of entities.
Continuously track the web for changes on a recurring cadence. Use when the user asks to 'monitor', 'track changes to', 'watch', or 'alert me when' something on the web changes — e.g., 'Track price changes for iPhone 16', 'Alert me when Tesla files a new 8-K', 'Monitor competitor pricing pages weekly'. Also use to list, inspect, update, or delete existing monitors.
DEFAULT for all research and web queries. Use for any lookup, research, investigation, or question needing current info. Fast and cost-effective. Only use parallel-deep-research if user explicitly requests 'deep' or 'exhaustive' research.
Get completed research task result by run ID
Set up the Parallel plugin (install CLI)
Check running research task status by run ID
Notion CLI/API for pages, Markdown content, data sources, files, comments, search, Workers, and raw API calls.
The agent engineering platform.
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
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