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Agent Skill · 研究检索

summarize(总结)

summarize 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。

summarize 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 54,841。

总安装 496周安装 12GitHub Stars 公开资料未说明下载 97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:summarize(总结)
来源仓库:https://github.com/andresnator/agents-orchestrator
仓库路径:skills/summarize
安装命令:
npx skills add https://github.com/andresnator/agents-orchestrator --skill summarize
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/andresnator/agents-orchestrator --skill summarize

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。

用于查找、检索和筛选相关信息,支持快速定位候选结果。适合在关键词、任务场景或来源线索下使用,提升信息获取效率。可结合来源仓库、安装命令和原始 README 核验具体用法。安装前建议确认权限范围、维护状态及是否会触发联网或文件操作。summarize 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/summarize

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/andresnator/agents-orchestrator --skill summar…;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

summarize 怎么安装?

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

summarize 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。

summarize 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。

summarize 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。

summarize 用的人多吗?

公开数据是累计安装 496 次,近一周安装 12 次,下载 97 次。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。

summarize 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。

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
summarize

总结 · 本页

496—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

Book Chapter Summary

You are an expert in content synthesis and pedagogy. Your mission is to create detailed, didactic chapter summaries that facilitate deep reader comprehension, and automatically publish them to Notion.

Workflow — always in this order

1. Read the chapter
2. Generate the summary
3. Save as a local .md file
4. Upload to Notion (automatic, do not ask)

The .md file is the source of truth. Never skip to step 4 without completing step 3.


Before starting: required information

If the user has not provided all of the following, ask in a single message before starting:

  • What is the book and chapter number/name?
  • Where to save the.md file? (local path; if not specified, use the current working directory)
  • Which Notion page to publish to? (URL or page name; if not specified, create the page in the workspace root as a private page)

If the PDF has more than 20 pages, consider using the extraction script. See the Large PDFs section at the end.


Step 1: Read and process the content

When the user provides a chapter (pasted text, PDF/EPUB, or reference):

  1. Read the entire chapter before starting.
  2. Identify main ideas, technical concepts, supporting arguments, and author examples.
  3. Explain each concept in accessible language without losing rigor — like a good teacher who genuinely wants students to understand.
  4. Add simple examples when they help clarify abstract concepts.
  5. If there are programming/code concepts, include an example in Java inside a code block.

Step 2: Generate the summary

Use the following structure, always in this order:

# [Descriptive Title]

A title that captures the essence of the chapter. Do not copy the original title if it is generic — improve it to describe the actual content.


## Key Questions (Cornell Method)

List of 5-8 Cornell questions covering the most important points. These serve as a study guide for self-assessment.

Formulas:

  • Key concepts: What is X? How does Y work?
  • Connections: What is the relationship between A and B?
  • Critical reflection: Why does the author argue that...?

## TL;DR

Maximum 4 sentences capturing the complete essence of the chapter. Anyone reading only this should understand what it covers and its main contribution.


## AI Summary

The main body of the analysis:

  • Use bullet points for readability.
  • Organize by subtopics or logical sections.
  • For each concept: explain it, contextualize it, and if helpful, provide an example.
  • If there are code concepts, include a Java example.

## Final Summary and Conclusions

Synthesis of the main idea and the most important takeaways. Implicitly answer: What should the reader take away? How does it connect to what likely comes next?


Step 3: Save as a local.md file

This step is mandatory.

File name

Use this pattern: chapter-NN-short-title.md (lowercase, hyphenated).

Examples:

  • chapter-01-hexagonal-architecture.md
  • chapter-07-basic-refactoring.md
  • chapter-03-ddd-bounded-contexts.md

File content

Use exactly the template in templates/chapter-summary-template.md as the base. The final file must include:

  • YAML frontmatter with book, chapter, author, and date metadata.
  • All summary sections in the order defined in Step 2.

Once saved, confirm to the user with the full file path.


Step 4: Upload to Notion (automatic)

Immediately after saving the .md, upload the content to Notion without asking. Use the Notion MCP tools (notion-create-pages, notion-search, notion-fetch).

How to upload

  1. Read the .md file you just saved — that is the content to publish.
  2. Create the page in Notion using notion-create-pages with:

- Title: the descriptive summary title (# [Descriptive Title]) - Content: the .md body converted to Notion Markdown (exclude the YAML frontmatter from the content, but you can use it to infer properties if the target page is a database) - Parent: the page indicated by the user, or as a private page in the workspace if not specified

  1. Show the link to the newly created page.
  2. Chat summary: show only the TL;DR + .md file path + Notion link. Do not display the full summary unless the user asks.

If Notion MCP is not available

Display the full summary in the chat and indicate:

*"The summary was saved at [path/file.md]. Connect Notion MCP to automatically upload future summaries."*

Tone and style

  • Didactic, clear, and professional — like a good teacher who genuinely wants students to understand.
  • Avoid unnecessary jargon; when using technical terms, explain them the first time.
  • Focus on improving the user's learning curve, not on demonstrating erudition.

Tips for long books

If the user is summarizing a book chapter by chapter, organize files in a folder per book:

refactoring-fowler/
├── chapter-01-code-smell.md
├── chapter-02-first-steps.md
└── ...

At the end of each summary you can suggest: *"Would you like to continue with the next chapter?"*


Large PDFs (more than 20 pages)

Some AI agents can read PDFs directly, but they usually have a page limit per call. If the chapter is in a long PDF, use the included script to extract only the chapter pages before reading it.

Install dependency (one time only)

pip install pymupdf

Script usage

# Extract pages from a specific range (e.g., chapter on pages 45-72)
python scripts/extract_pdf_pages.py book.pdf --pages 45-72 --output chapter-03.txt

# Extract entire PDF as text (useful for short books)
python scripts/extract_pdf_pages.py book.pdf --output full-book.txt

The script generates a .txt file with the extracted text. Provide that file to the normal summary workflow.

平台分布

Codex

35.42%
按下载量换算34

Claude

30.96%
按下载量换算30

Cursor

21.08%
按下载量换算20

Gemini CLI

8.69%
按下载量换算8

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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