web-research 是做什么的？
搜索多个网络来源，综合发现，并利用委派的子代理生成带引用的研究报告。当用户要求在线研究某个主题、搜索网络、查找信息、获取最新资讯、比较选项或生成研究报告时使用。
搜索多个网络来源，综合发现，并利用委派的子代理生成带引用的研究报告。当用户要求在线研究某个主题、搜索网络、查找信息、获取最新资讯、比较选项或生成研究报告时使用。
该技能通过委派子代理并行搜索多个网络来源，自动综合并整理发现，最终生成带有引用标注的结构化研究报告。它底层依赖LangChain框架来编排搜索与摘要流水线，支持自定义搜索引擎（如Brave Search）和检索工具。对于需要快速获取最新信息、调研竞品或生成可追溯来源的文档摘要的开发者和知识工作者而言，该功能显著提高了信息收集和报告撰写的效率。它适用于Claude Code、Cursor、Codex等支持自定义技能的工具，使用简单，只需提示研究主题即可自动完成从搜索到格式化的完整流程。
npx skills add https://github.com/langchain-ai/deepagents/tree/main/skills/web-researchInstalled? Explore more 研究与数据分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
搜索多个网络来源，综合发现，并利用委派的子代理生成带引用的研究报告。当用户要求在线研究某个主题、搜索网络、查找信息、获取最新资讯、比较选项或生成研究报告时使用。
This repo contains 4 individual skills — each has its own dedicated page.
Searches arXiv for preprints and academic papers, retrieves abstracts, and filters by topic. Use when the user asks to find research papers, search arXiv, look up preprints, find academic articles in physics, math, CS, biology, statistics, or related fields.
Writes and structures long-form blog posts, creates tutorial outlines, and optimizes content for SEO with cover image generation. Use when the user asks to write a blog post, article, how-to guide, tutorial, technical writeup, thought leadership piece, or long-form content.
Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API, or needs LangGraph implementation guidance.
Drafts engaging social media posts, writes hooks, suggests hashtags, creates thread structures, and generates companion images. Use when the user asks to write a LinkedIn post, tweet, Twitter/X thread, social media caption, social post, or repurpose content for social platforms.
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.