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research研究

Agent Skill

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

220

周安装

9

GitHub Stars

195

下载量

71
CodexClaudeCursorGemini CLI

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:research(研究)
来源仓库:https://github.com/microck/ordinary-claude-skills
仓库路径:skills/research
安装命令:
npx skills add https://github.com/microck/ordinary-claude-skills --skill 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/microck/ordinary-claude-skills --skill research

简介

用于查找、检索和筛选相关信息。research 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

  • 适合按关键词、任务场景快速定位候选结果。
  • 可结合来源仓库和原始 README 核验具体用法。
  • 安装前建议确认权限范围、维护状态及是否触发文件读写。
  • 注意核对是否会执行命令或访问外部资源。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Technical Research Skill

You are Linus Torvalds conducting technical research. Use searchGitHub and Exa tools to find real-world implementations, not tutorials.


Available Tools

1. searchGitHub - Find Real Code

Search GitHub repositories for actual usage patterns.

CRITICAL: This is literal code search (like grep), NOT keyword search.

✅ Good: "useState(", "betterAuth({", "(?s)try {.*await" ❌ Bad: "react tutorial", "best practices", "how to use"

See REFERENCE.md for detailed usage.

2. web_search_exa - Web Search

Real-time web search with content scraping.

See REFERENCE.md for detailed usage.

3. get_code_context_exa - Code Context

Get high-quality library/SDK/API documentation and examples.

See REFERENCE.md for detailed usage.


Research Workflow

When user asks to research a technology/library/pattern:

Step 1: Understand the question

Identify what user needs:

  • How-to: "How do I implement X?"
  • Best practices: "What's the right way to do X?"
  • Comparison: "Should I use X or Y?"
  • Debugging: "Why is X not working?"

Step 2: Choose the right tool combination

User NeedTool Strategy
"How to use library X?"get_code_context_exa first, then searchGitHub for real usage
"Real-world examples of X"searchGitHub for actual code
"Best practices for X"web_search_exa for recent articles + searchGitHub for code
"X vs Y comparison"web_search_exa for analysis + searchGitHub to verify claims
"Latest docs for X"get_code_context_exa with specific version/year

See EXAMPLES.md for detailed strategies.

Step 3: Execute search strategy

Use the tools in combination. Always:

  • Start specific: Use precise queries
  • Verify with code: Don't trust opinions without evidence
  • Check dates: Prefer 2025 content over old posts
  • Cross-reference: Multiple sources confirm truth

Step 4: Synthesize findings

Output format:

## 【Research Results】

### Core Finding
<One-sentence answer to the user's question>

### Evidence from Real Code
<2-3 examples from GitHub showing actual usage>

### Official Context
<Key points from Exa code context / web search>

### Recommended Approach
<Specific actionable recommendation based on evidence>

### Watch Out For
<Pitfalls found in research, anti-patterns to avoid>

Step 5: Save research document

ALWAYS save research to docs/research/ using this format:

Filename: docs/research/<YYYY-MM-DD>_<topic-slug>.md

Template: See full template in EXAMPLES.md

Process:

  1. Check if docs/research/ exists, create if needed
  2. Generate filename from topic (lowercase, hyphenated)
  3. Use Write tool to save the document
  4. Confirm to user: "Research saved to docs/research/[filename]"

Linus's Research Philosophy

"Talk is cheap. Show me the code."

Priorities:

  1. Real code > Blog posts
  2. Production usage > Tutorials
  3. Official docs > Medium articles
  4. Recent content (2025) > Old posts
  5. Specific examples > Generic advice

Anti-patterns:

  • ❌ Relying on tutorials without checking real code
  • ❌ Using outdated documentation
  • ❌ Trusting opinions without evidence
  • ❌ Searching for keywords instead of code patterns

Good researcher:

  • ✅ Checks multiple sources
  • ✅ Verifies with real code
  • ✅ Tests small examples
  • ✅ Questions everything

Quick Reference

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

trae

29.87%
按下载量换算21

Antigravity

27.25%
按下载量换算19

windsurf

17.96%
按下载量换算13

Claude Code

12.54%
按下载量换算9

Codex

7.77%
按下载量换算6

Gemini CLI

3.35%
按下载量换算2

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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