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Agent Skill · 研究检索

search(搜索)

search 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。

search 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,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 4,130。

总安装 35,640周安装 1,461GitHub Stars 11,688下载 12,480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
unknown

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:search(搜索)
来源仓库:https://github.com/anthropics/knowledge-work-plugins
仓库路径:skills/search
安装命令:
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill search
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill search

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。

search 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词快速定位候选结果时使用。它可结合来源仓库、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或文件读写。适用于通用研究检索类任务。

通过 npx skills add 命令从指定 GitHub 仓库安装。

来源仓库内路径:skills/search

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/anthropics/knowledge-work-plugins --skill sear…;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

    它需要调用外部服务,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

search 怎么安装?

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

search 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。

search 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

search 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

search 用的人多吗?

公开数据是累计安装 35,640 次,近一周安装 1,461 次,下载 12,480 次,GitHub 11,688 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。

search 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 11,688 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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

  • 需要明确授权才能用到公司项目里的场景。
  • 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
search

搜索 · 本页

35,64011,688调用外部服务未明确通过

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

Search Command

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Search across all connected MCP sources in a single query. Decompose the user's question, run parallel searches, and synthesize results.

Instructions

1. Check Available Sources

Before searching, determine which MCP sources are available. Attempt to identify connected tools from the available tool list. Common sources:

  • ~~chat — chat platform tools
  • ~~email — email tools
  • ~~cloud storage — cloud storage tools
  • ~~project tracker — project tracking tools
  • ~~CRM — CRM tools
  • ~~knowledge base — knowledge base tools

If no MCP sources are connected:

To search across your tools, you'll need to connect at least one source.
Check your MCP settings to add ~~chat, ~~email, ~~cloud storage, or other tools.

Supported sources: ~~chat, ~~email, ~~cloud storage, ~~project tracker, ~~CRM, ~~knowledge base,
and any other MCP-connected service.

2. Parse the User's Query

Analyze the search query to understand:

  • Intent: What is the user looking for? (a decision, a document, a person, a status update, a conversation)
  • Entities: People, projects, teams, tools mentioned
  • Time constraints: Recency signals ("this week", "last month", specific dates)
  • Source hints: References to specific tools ("in ~~chat", "that email", "the doc")
  • Filters: Extract explicit filters from the query:

- from: — Filter by sender/author - in: — Filter by channel, folder, or location - after: — Only results after this date - before: — Only results before this date - type: — Filter by content type (message, email, doc, thread, file)

3. Decompose into Sub-Queries

For each available source, create a targeted sub-query using that source's native search syntax:

~~chat:

  • Use available search and read tools for your chat platform
  • Translate filters: from: maps to sender, in: maps to channel/room, dates map to time range filters
  • Use natural language queries for semantic search when appropriate
  • Use keyword queries for exact matches

~~email:

  • Use available email search tools
  • Translate filters: from: maps to sender, dates map to time range filters
  • Map type: to attachment filters or subject-line searches as appropriate

~~cloud storage:

  • Use available file search tools
  • Translate to file query syntax: name contains, full text contains, modified date, file type
  • Consider both file names and content

~~project tracker:

  • Use available task search or typeahead tools
  • Map to task text search, assignee filters, date filters, project filters

~~CRM:

  • Use available CRM query tools
  • Search across Account, Contact, Opportunity, and other relevant objects

~~knowledge base:

  • Use semantic search for conceptual questions
  • Use keyword search for exact matches

4. Execute Searches in Parallel

Run all sub-queries simultaneously across available sources. Do not wait for one source before searching another.

For each source:

  • Execute the translated query
  • Capture results with metadata (timestamps, authors, links, source type)
  • Note any sources that fail or return errors — do not let one failure block others

5. Rank and Deduplicate Results

Deduplication:

  • Identify the same information appearing across sources (e.g., a decision discussed in ~~chat AND confirmed via email)
  • Group related results together rather than showing duplicates
  • Prefer the most authoritative or complete version

Ranking factors:

  • Relevance: How well does the result match the query intent?
  • Freshness: More recent results rank higher for status/decision queries
  • Authority: Official docs > wiki > chat messages for factual questions; conversations > docs for "what did we discuss" queries
  • Completeness: Results with more context rank higher

6. Present Unified Results

Format the response as a synthesized answer, not a raw list of results:

For factual/decision queries:

[Direct answer to the question]

Sources:
- [Source 1: brief description] (~~chat, #channel, date)
- [Source 2: brief description] (~~email, from person, date)
- [Source 3: brief description] (~~cloud storage, doc name, last modified)

For exploratory queries ("what do we know about X"):

[Synthesized summary combining information from all sources]

Found across:
- ~~chat: X relevant messages in Y channels
- ~~email: X relevant threads
- ~~cloud storage: X related documents
- [Other sources as applicable]

Key sources:
- [Most important source with link/reference]
- [Second most important source]

For "find" queries (looking for a specific thing):

[The thing they're looking for, with direct reference]

Also found:
- [Related items from other sources]

7. Handle Edge Cases

Ambiguous queries: If the query could mean multiple things, ask one clarifying question before searching:

"API redesign" could refer to a few things. Are you looking for:
1. The REST API v2 redesign (Project Aurora)
2. The internal SDK API changes
3. Something else?

No results:

I couldn't find anything matching "[query]" across [list of sources searched].

Try:
- Broader terms (e.g., "database" instead of "PostgreSQL migration")
- Different time range (currently searching [time range])
- Checking if the relevant source is connected (currently searching: [sources])

Partial results (some sources failed):

[Results from successful sources]

Note: I couldn't reach [failed source(s)] during this search.
Results above are from [successful sources] only.

Notes

  • Always search multiple sources in parallel — never sequentially
  • Synthesize results into answers, do not just list raw search results
  • Include source attribution so users can dig deeper
  • Respect the user's filter syntax and apply it appropriately per source
  • When a query mentions a specific person, search for their messages/docs/mentions across all sources
  • For time-sensitive queries, prioritize recency in ranking
  • If only one source is connected, still provide useful results from that source

平台分布

Codex

38.25%
按下载量换算4,774

Claude

29.04%
按下载量换算3,624

Cursor

19.43%
按下载量换算2,425

Gemini CLI

9.62%
按下载量换算1,201

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

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