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web-research网络研究

Agent Skill

web-research 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

47,040

周安装

2,045

GitHub Stars

22,021

下载量

16,480
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:web-research(网络研究)
来源仓库:https://github.com/langchain-ai/deepagents
仓库路径:skills/web-research
安装命令:
npx skills add https://github.com/langchain-ai/deepagents --skill web-research
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/langchain-ai/deepagents --skill web-research

简介

通过委托子代理、综合调查结果并生成引用的报告来协调多源网络研究。

  • 将研究问题分解为 2-5 个不同的子主题,创建研究计划文件,并并行生成最多 3 个子代理以进行高效调查
  • 每个子代理对每个子主题执行 3-5 次 Web 搜索,并将结果写入包含关键事实、引用和源 URL 的本地文件
  • 通过阅读本地调查结果文件、整合跨子主题的见解以及在最终响应中直接引用来源来综合结果
  • 通过灵活的规划和基于结构化文件的通信,支持简单的事实调查、比较分析和复杂的多角度调查

SKILL.md

Web Research Skill

Research Process

Step 1: Create and Save Research Plan

Before delegating to subagents, you MUST:

  1. Create a research folder - Organize all research files in a dedicated folder relative to the current working directory: mkdir research_[topic_name] This keeps files organized and prevents clutter in the working directory.
  2. Analyze the research question - Break it down into distinct, non-overlapping subtopics
  3. Write a research plan file - Use the write_file tool to create research_[topic_name]/research_plan.md containing:

- The main research question - 2-5 specific subtopics to investigate - Expected information from each subtopic - How results will be synthesized

Planning Guidelines:

  • Simple fact-finding: 1-2 subtopics
  • Comparative analysis: 1 subtopic per comparison element (max 3)
  • Complex investigations: 3-5 subtopics

Step 2: Delegate to Research Subagents

For each subtopic in your plan:

  1. Use the task tool to spawn a research subagent with:

- Clear, specific research question (no acronyms) - Instructions to write findings to a file: research_[topic_name]/findings_[subtopic].md - Budget: 3-5 web searches maximum

  1. Run up to 3 subagents in parallel for efficient research

Subagent Instructions Template:

Research [SPECIFIC TOPIC]. Use the web_search tool to gather information.
After completing your research, use write_file to save your findings to research_[topic_name]/findings_[subtopic].md.
Include key facts, relevant quotes, and source URLs.
Use 3-5 web searches maximum.

Step 3: Synthesize Findings

After all subagents complete:

  1. Review the findings files that were saved locally:

- First run list_files research_[topic_name] to see what files were created - Then use read_file with the file paths (e.g., research_[topic_name]/findings_*.md) - Important: Use read_file for LOCAL files only, not URLs

  1. Synthesize the information - Create a comprehensive response that:

- Directly answers the original question - Integrates insights from all subtopics - Cites specific sources with URLs (from the findings files) - Identifies any gaps or limitations

  1. Write final report (optional) - Use write_file to create research_[topic_name]/research_report.md if requested

Note: If you need to fetch additional information from URLs, use the fetch_url tool, not read_file.

Best Practices

  • Plan before delegating - Always write research_plan.md first
  • Clear subtopics - Ensure each subagent has distinct, non-overlapping scope
  • File-based communication - Have subagents save findings to files, not return them directly
  • Systematic synthesis - Read all findings files before creating final response
  • Stop appropriately - Don't over-research; 3-5 searches per subtopic is usually sufficient

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.94%
按下载量换算4,934

OpenCode

22.1%
按下载量换算3,642

Codex

16.26%
按下载量换算2,680

Gemini CLI

11.33%
按下载量换算1,867

Cursor

7.59%
按下载量换算1,251

Antigravity

3.7%
按下载量换算610

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/langchain-ai/deepagents --skill web-research;npx skills add langchain-ai/deepagents --skill "web-research" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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