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Agent Skill · 研究检索

deep-research(深入研究)

deep-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。

deep-research 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 62,484。

总安装 333周安装 14GitHub Stars 94下载 116核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:deep-research(深入研究)
来源仓库:https://github.com/nateberkopec/dotfiles
仓库路径:skills/deep-research
安装命令:
npx skills add https://github.com/nateberkopec/dotfiles --skill deep-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/nateberkopec/dotfiles --skill deep-research

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

deep-research 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于关键词搜索、任务场景匹配或来源线索梳理等研究检索场景。通过 npx skills add 命令从 GitHub 仓库安装,需结合原始 README 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或文件读写操作。注意该技能当前分类为研究检索,主要服务于信息定位与筛选需求。

来源仓库内路径:skills/deep-research

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/nateberkopec/dotfiles --skill deep-research;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

deep-research 怎么安装?

在终端执行 npx skills add https://github.com/nateberkopec/dotfiles --skill deep-research。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

deep-research 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

deep-research 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/nateberkopec/dotfiles --skill deep-research;npx skills add nateberkopec/dotfiles --skill "deep-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。

deep-research 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

deep-research 用的人多吗?

公开数据是累计安装 333 次,近一周安装 14 次,下载 116 次,GitHub 94 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

deep-research 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
deep-research

深入研究 · 本页

33394执行命令MIT有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Deep Research

This skill conducts comprehensive research on complex topics using a multi-agent architecture, producing detailed reports similar to academic journals or whitepapers.

Purpose

The deep-research skill transforms broad research questions into thorough, well-cited reports using a three-agent system:

  1. Lead Agent (You): Conducts interviews, plans research, orchestrates subagents
  2. Researcher Agents: Execute web searches and save findings to files
  3. Report-Writer Agent: Synthesizes research notes into final report

When to Use This Skill

Use this skill when the user requests:

  • In-depth research on a complex topic
  • A comprehensive report or analysis
  • Research that requires multiple sources and synthesis
  • Deep investigation similar to academic or whitepaper standards
  • Detailed analysis with proper citations

Do NOT use this skill for:

  • Simple fact-finding queries
  • Single-source information lookup
  • Code-only research within repositories
  • Quick exploratory searches

Agent Architecture

Lead Agent (You - the Orchestrator)

Role: Interview user, plan research threads, spawn and coordinate subagents

Tools allowed: Task (to spawn subagents), AskUserQuestion, Write (for research plan only)

Responsibilities:

  • Conduct user interview to scope research
  • Perform initial reconnaissance
  • Decompose topic into 10+ research threads
  • Spawn researcher agents in parallel
  • Spawn report-writer agent after research completes

Researcher Agents

Role: Execute focused research on assigned subtopic

Tools allowed: WebSearch, WebFetch, Write

Responsibilities:

  • Search the web for information on assigned topic
  • Fetch and analyze relevant pages
  • Save structured research notes to research_notes/ directory

Output format: Each researcher saves a markdown file to research_notes/[subtopic-slug].md with:

  • Summary of findings
  • Key facts and data points
  • Source URLs with brief descriptions
  • Notable quotes or excerpts
  • Conflicts or gaps identified

Report-Writer Agent

Role: Synthesize all research notes into final report

Tools allowed: Read, Glob, Write

Responsibilities:

  • Read all files from research_notes/ directory
  • Identify themes, patterns, and conflicts across sources
  • Structure and write the final report
  • Create the sources bibliography

Research Process

Phase 1: Interview and Scope Definition

Start by interviewing the user to understand their research needs. Ask questions about:

  1. Research objectives: What are they trying to understand or decide?
  2. Depth and breadth: How comprehensive should the research be?
  3. Target audience: Who will read this report?
  4. Key questions: What specific questions need answering?
  5. Time constraints: Is this time-sensitive information?
  6. Scope boundaries: What should be explicitly included or excluded?

The interview should be thorough but efficient. Use the AskUserQuestion tool to gather this information in 2-3 rounds of questions maximum.

Phase 2: Initial Reconnaissance

After the interview, perform initial reconnaissance to identify the research landscape:

  1. Conduct 3-5 broad web searches to map the topic space
  2. Identify key subtopics, domains, and areas of focus
  3. Note promising sources, authoritative voices, and research gaps
  4. Create a research plan outlining 10+ specific research threads

Save the research plan to research_plan.md documenting:

  • The research threads identified
  • Which researcher will handle each thread
  • Expected output from each researcher

Phase 3: Parallel Research (Researcher Agents)

Launch 10+ researcher agents in parallel using the Task tool. Each agent receives a focused research assignment.

Spawning researcher agents:

Task tool with:
- subagent_type: "general-purpose"
- prompt: Include these elements:
  1. Clear statement: "You are a RESEARCHER agent"
  2. Specific subtopic assignment
  3. Tool restrictions: "Only use WebSearch, WebFetch, and Write tools"
  4. Output instructions: "Save your findings to research_notes/[subtopic].md"
  5. Format requirements for the research notes file

Example researcher prompt:

You are a RESEARCHER agent investigating: "Technical implementation of quantum error correction"

YOUR TOOLS: Only use WebSearch, WebFetch, and Write.

TASK:
1. Use WebSearch to find authoritative sources on quantum error correction implementation
2. Use WebFetch to extract detailed information from promising sources
3. Save your findings to research_notes/quantum-error-correction.md

OUTPUT FORMAT (save to research_notes/quantum-error-correction.md):
# Quantum Error Correction Implementation

## Summary
[2-3 paragraph summary of key findings]

## Key Findings
- [Bullet points of important facts, data, techniques]

## Sources
1. [URL] - [Brief description of what this source contributed]
2. [URL] - [Brief description]
...

## Notable Quotes
> "[Relevant quote]" - Source

## Gaps and Conflicts
- [Any conflicting information or areas needing more research]

Launch all researcher agents in a single message with multiple Task tool calls for true parallelism.

Phase 4: Report Generation (Report-Writer Agent)

After all researcher agents complete, spawn a single report-writer agent:

Spawning the report-writer agent:

Task tool with:
- subagent_type: "general-purpose"
- prompt: Include these elements:
  1. Clear statement: "You are a REPORT-WRITER agent"
  2. Tool restrictions: "Only use Read, Glob, and Write tools"
  3. Instructions to read all files from research_notes/
  4. Report structure requirements
  5. Output file paths for report and sources

Example report-writer prompt:

You are a REPORT-WRITER agent synthesizing research findings into a final report.

YOUR TOOLS: Only use Read, Glob, and Write.

TASK:
1. Use Glob to list all files in research_notes/
2. Use Read to load each research notes file
3. Synthesize findings into a comprehensive report
4. Write the final report to [topic]-report.md
5. Write the sources bibliography to [topic]-sources.md

REPORT STRUCTURE:
- Executive Summary (2-3 paragraphs)
- [Adaptive middle sections based on topic]
- Critical Analysis
- Conclusions
- References (numbered citations)

SOURCES FILE STRUCTURE:
# Research Sources for [Topic]

## [1] Source Title
- **URL**: [url]
- **Accessed**: [date]
- **Type**: [Academic paper / Blog post / Documentation / News article]
- **Key Points**: [bullet points]
- **Relevance**: [why this source matters]

WRITING GUIDELINES:
- Use numbered citations [1], [2], etc.
- Cross-reference findings across multiple researcher notes
- Note any conflicts or gaps in the research
- Use clear, precise academic language
- Include tables for comparisons where appropriate

Phase 5: Output and Summary

After the report-writer completes:

  1. Inform the user of the generated files:

- [topic]-report.md: Main research report - [topic]-sources.md: Complete bibliography - research_notes/: Directory of raw research (can be deleted)

  1. Provide a brief verbal summary of key findings
  2. Offer to answer follow-up questions or expand on any section

File Structure

./
├── research_plan.md           # Your research plan (Phase 2)
├── research_notes/            # Researcher agent outputs (Phase 3)
│   ├── subtopic-1.md
│   ├── subtopic-2.md
│   └── ...
├── [topic]-report.md          # Final report (Phase 4)
└── [topic]-sources.md         # Bibliography (Phase 4)

Logging and Observability

Track research progress by documenting in research_plan.md:

  1. Research threads assigned: List each subtopic and its researcher
  2. Status tracking: Note when each researcher completes
  3. Issues encountered: Document any gaps or conflicts found

This provides transparency into the research process and helps with debugging or expanding research later.

Best Practices

Agent Separation

  • Lead agent: ONLY spawns agents and coordinates - no direct research
  • Researchers: ONLY search, fetch, and write notes - no synthesis
  • Report-writer: ONLY reads notes and writes report - no new research

This separation ensures clean handoffs and reproducible results.

Research Quality

  • Prioritize authoritative, recent sources (especially for time-sensitive topics)
  • Cross-reference claims across multiple researcher notes
  • Note conflicting information or perspectives
  • Distinguish between facts, expert opinions, and speculation
  • Be transparent about limitations in available information

Efficiency

  • Launch all researcher agents truly in parallel (single message, multiple Task tool calls)
  • Use model="haiku" for researcher agents to reduce costs
  • Use model="sonnet" for report-writer agent for better synthesis
  • Clear task delineation prevents redundant research

Common Patterns

Comparative Research

When comparing technologies, approaches, or solutions:

  • Assign one researcher per option being compared
  • Assign one researcher for cross-cutting concerns (performance, cost, etc.)
  • Report-writer creates comparison tables

Technical Deep-Dives

When researching technical topics:

  • Assign researchers to: fundamentals, implementation, case studies, limitations
  • Report-writer structures from basics to advanced

Market/Landscape Research

When surveying a domain or market:

  • Assign researchers to: major players, emerging players, trends, analysis firms
  • Report-writer categorizes and evaluates the landscape

Historical/Evolution Research

When investigating how something developed:

  • Assign researchers to different time periods or key events
  • Report-writer creates timeline and connects to present

平台分布

Claude Code

24.56%
按下载量换算28

windsurf

22.85%
按下载量换算27

OpenCode

17.34%
按下载量换算20

Codex

12.62%
按下载量换算15

Antigravity

7.82%
按下载量换算9

Gemini CLI

3.25%
按下载量换算4

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/nateberkopec/dotfiles --skill deep-research;npx skills add nateberkopec/dotfiles --skill "deep-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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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