Token导航 LogoToken导航

Agent Skill · 研究检索

ai-summary-request(ai 摘要请求)

ai-summary-request 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。

ai-summary-request 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,权限为需要联网;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 47,767。

总安装 720周安装 30GitHub Stars 31下载 240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:ai-summary-request(ai 摘要请求)
来源仓库:https://github.com/rawveg/skillsforge-marketplace
仓库路径:skills/ai-summary-request
安装命令:
npx skills add https://github.com/rawveg/skillsforge-marketplace --skill ai-summary-request
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/rawveg/skillsforge-marketplace --skill ai-summary-request

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。

AI Summary Request 用于为网站添加 AI 平台集成按钮,支持访客请求网站的 AI 摘要。适用于希望在其网站上添加 AI 平台按钮并允许访客轻松获取业务摘要的用户。通过检测确认网站域名,可选择生成 llms.txt 文件以提升 AI 可发现性。

安装前需确认权限范围、维护状态,以及是否会触发联网或文件读写操作。ai-summary-request 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/ai-summary-request

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/rawveg/skillsforge-marketplace --skill ai-summ…;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

    它需要需要联网,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

ai-summary-request 怎么安装?

在终端执行 npx skills add https://github.com/rawveg/skillsforge-marketplace --skill ai-summary-reques…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ai-summary-request 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。

ai-summary-request 需要什么权限?

权限级别是需要联网。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。

ai-summary-request 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。

ai-summary-request 用的人多吗?

公开数据是累计安装 720 次,近一周安装 30 次,下载 240 次,GitHub 31 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。

ai-summary-request 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

  • 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

  • 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
ai-summary-request

ai 摘要请求 · 本页

72031需要联网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

AI Summary Request

Overview

This skill creates a footer component with AI platform icons that allow visitors to request AI summaries of a website. The workflow begins by detecting and confirming the website domain, then asks whether to optionally generate an llms.txt file for enhanced AI discoverability.

When to Use This Skill

Use this skill when:

  • User wants to add AI platform integration buttons to their site
  • User wants visitors to easily get AI summaries of their business
  • User mentions "AI summary" or AI platform buttons
  • User wants to create an llms.txt file for their website (optional)
  • User asks about making their website AI-discoverable

Workflow

PREREQUISITE: Domain Detection and Confirmation

Before proceeding with any steps, you MUST determine the website domain:

Step 1: Attempt automatic detection

Search for domain information in this priority order:

  1. Environment files (.env, .env.local, .env.production) - look for SITE_URL, BASE_URL, NEXT_PUBLIC_URL, NUXT_PUBLIC_SITE_URL, VITE_SITE_URL, or similar
  2. Deployment configs (vercel.json, netlify.toml, firebase.json, fly.toml) - check for domain/alias settings
  3. CNAME files in public/ or root directory
  4. Configuration files (package.json homepage field, next.config.js, nuxt.config.js, vite.config.js)
  5. HTML files - meta tags or <base> tags in index files
  6. README or documentation mentioning the live site URL
Step 2: Confirm or request domain

If a domain is detected, ask the user to confirm or provide an alternative:

"I detected that this site appears to use the domain [DETECTED_DOMAIN]. Is this correct? If not, please provide the correct domain."

If no domain can be detected, ask the user directly:

"I couldn't automatically detect the domain for this website. What domain should be used for the AI summary links? (e.g., https://example.com)"
Step 3: Normalize and store the domain
  • If the user provides a domain without a protocol, prepend https://
  • Remove any trailing slashes
  • Store the normalized domain as ${WEBSITE_URL} for use in subsequent steps

Example normalizations:

  • example.com → https://example.com
  • https://example.com/ → https://example.com
  • http://example.com → keep as-is (user may have specific requirements)

PREREQUISITE: llms.txt Decision

After confirming the domain, ask the user:

"Would you like me to also generate an llms.txt file for this website? This file helps AI models better understand your site's content and structure, which can improve the quality of AI-generated summaries. - Yes: I'll create a curated llms.txt file and the footer component will reference it - No: I'll create just the footer component, and the AI prompt will direct users to explore the website directly"

Store the user's choice as ${INCLUDE_LLMS_TXT} (true/false).


STEP 1: Generate llms.txt File (OPTIONAL - Only if user chose "Yes")

Skip this step entirely if the user chose not to generate an llms.txt file.

Generate a high-quality llms.txt file for a given website that helps language models quickly understand and reference the site's most valuable content.

Analyze the Website's Content Hierarchy

  • Inspect any available XML or HTML sitemaps (product, page, post) and explore navigation menus to identify major product categories, services, key informational pages, and blog or news posts
  • Focus on top-level categories and representative subcategories or key products, rather than listing every single URL
  • Identify important support or policy pages (e.g., About, Contact, Terms, Privacy, Shipping & Returns)

Select and Curate Content

  • For each major category, select a primary landing page and a few representative subcategories or high-value product pages
  • Include links to authoritative guides, how-to articles, calculators, training programs or other resources
  • Choose a handful of blog posts or case studies that showcase different topics (tutorials, industry insights, success stories). Avoid listing dozens of posts
  • Exclude low-value pages such as checkout flows, login pages, or marketing fluff

Draft Clear Descriptions

  • Use concise, factual descriptions (10-15 words) that explain what each page covers
  • Avoid hype or redundant repetition of the page title
  • When summarizing subcategories, group them in parentheses for brevity

Build the llms.txt in Markdown

  • Start with an H1 title containing the website or company name and a short descriptor
  • Add a blockquote (prefaced by >) that succinctly describes what the business does and who it serves
  • Optionally include a sentence explaining that the list is curated for AI consumption
  • Organize content with H2 headings such as:

- Product categories (or Services if it's a service business) - Representative pages or ## Popular products - Guides & resources - Articles & case studies - Policies & support

  • List each link as a bullet (- [Title](URL): description) under the appropriate section
  • Keep the file in UTF-8 encoding and ensure it stays well under 100 KB by curating rather than exhaustively listing every URL
  • Add an optional "Usage guidelines" section stating how you'd like AI models to attribute or use the content, and include an HTML comment like <!-- Last updated: YYYY-MM-DD --> for version tracking

Validate and Publish

  • Verify that all URLs return HTTP 200 and are publicly accessible
  • Check the Markdown structure (one H1, proper headings and bullets)
  • Place the final llms.txt at the website's root and, if possible, add a line in robots.txt (Llmstxt: /llms.txt) to aid discovery
  • Plan regular updates (e.g., quarterly) to reflect changes in products, services or content

Deliverable

Provide the full llms.txt file content, formatted as described above, in the served web root of the current website.


STEP 2: Create AI Summary Request Footer Component

Create an "AI Summary Request" footer component with the following specifications.

Component Structure

  • Centered section containing a header and icon row
  • Header text: "Request an AI summary of [COMPANY_NAME]"
  • Row of 5 clickable AI platform icons in this exact order: ChatGPT, Claude, Gemini, Grok, Perplexity

Visual Styling

  • Container: flex column, centered alignment, 16px vertical gap
  • Header: centered text, base font size (16px), medium font-weight, semantic gray color (#111827 or equivalent)
  • Icon container: flex row, centered, 12px horizontal gap, wrap-enabled
  • Each icon link: 40x40px clickable area with 28x28px visible icon, rounded-full background
  • Icons: Apply CSS filter: brightness(0) for monochrome black effect
  • Padding within circle: 6px (1.5rem equivalent)
  • Hover effect: transform scale(1.1) with cubic-bezier(0.4, 0, 0.2, 1) transition, 150ms duration

Icon Assets

CRITICAL: This skill includes bundled SVG icon files in the resources/ directory. You MUST use these exact icons - do NOT use generic icon libraries, search for alternatives, or create substitutes.

Bundled Icons (Required)

Copy these SVG files from resources/ to the user's project assets directory:

PlatformFileDescription
ChatGPTresources/chatgpt.svgHexagonal flower/aperture pattern with interlocking curved segments
Clauderesources/claude.svgAbstract geometric pattern (NOT the Anthropic backslash logo)
Geminiresources/gemini.svgFour-pointed star/sparkle icon
Grokresources/grok.svgAngular crystalline/triangular pattern (NOT the X/Twitter logo)
Perplexityresources/perplexity.svgHexagonal pattern with isometric cube perspective
Implementation Steps
  1. Copy icons to project: Copy all 5 SVG files from this skill's resources/ directory to the user's project (e.g., /public/icons/ai/ or /assets/icons/)
  2. Reference in component: Use relative paths to the copied SVG files in the footer component
  3. Do NOT substitute: These are the only approved icons - do not use CDN links, icon libraries, or recreate from descriptions
Icon Validation

Before finalizing, visually confirm:

  • ChatGPT icon is NOT a speech bubble or generic chat icon
  • Claude icon is NOT a simple backslash or text character
  • Gemini icon is NOT a constellation or zodiac twins symbol
  • Grok icon is NOT the X/Twitter bird or logo
  • Perplexity icon is NOT a question mark or generic markdown symbol

AI Platform Links

Generate URL-encoded links to each AI platform with pre-composed prompt:

  1. ChatGPT: https://chat.openai.com/?q=[ENCODED_PROMPT]
  2. Claude: https://claude.ai/new?q=[ENCODED_PROMPT]
  3. Gemini: https://gemini.google.com/?q=[ENCODED_PROMPT]
  4. Grok: https://grok.com?q=[ENCODED_PROMPT]
  5. Perplexity: https://www.perplexity.ai/?q=[ENCODED_PROMPT]

Prompt Templates (Select based on llms.txt decision)

Use the appropriate template based on the user's llms.txt decision from the prerequisite step.

Template variables:

  • ${WEBSITE_URL} - The confirmed/normalized domain from prerequisite step
  • ${COMPANY_NAME} - The company/site name (ask user if not obvious from codebase)
  • ${KEY_ASPECTS} - Customize based on the business type (e.g., "features, pricing, deliverables" for services; "products, shipping, returns" for e-commerce)
WITH llms.txt (if user chose to generate llms.txt)
Please read the structured information at ${WEBSITE_URL}/llms.txt to understand ${COMPANY_NAME}.

As a potential client, I want to concretely understand what I will receive with ${COMPANY_NAME} (${WEBSITE_URL}).

Detail step by step what the service includes: ${KEY_ASPECTS}.

Explain it simply, as if you were describing the real experience of the service.
WITHOUT llms.txt (if user chose not to generate llms.txt)
Please visit and analyze ${WEBSITE_URL} to understand ${COMPANY_NAME}.

As a potential client, I want to concretely understand what I will receive with ${COMPANY_NAME} (${WEBSITE_URL}).

Detail step by step what the service includes: ${KEY_ASPECTS}.

Explain it simply, as if you were describing the real experience of the service.

Implementation Checklist

  • Detect or ask for website domain and get user confirmation
  • Ask user whether to generate llms.txt file
  • If llms.txt chosen: Generate and place llms.txt at website root
  • Copy all 5 SVG icons from resources/ to project assets directory
  • Select correct prompt template based on llms.txt decision
  • Place component in footer, above copyright notice
  • URL-encode prompt using encodeURIComponent() or equivalent
  • Each link opens in new tab: target="_blank" rel="noopener noreferrer"
  • Add aria-label: "Get AI summary from [Platform Name]"
  • Test all 5 platform links verify prompt pre-population works
  • Verify icons are using the bundled SVGs (NOT generic alternatives)
  • Apply brightness(0) filter for consistent monochrome appearance
  • Ensure 44x44px minimum touch target for mobile accessibility
  • Responsive: icons wrap on screens < 640px width

Technical Notes

  • The llms.txt file follows the emerging standard for AI-readable site documentation
  • The footer component should be framework-agnostic but can be adapted for React, Vue, Svelte, or vanilla HTML/CSS
  • All URLs must be properly encoded to handle special characters in the prompt
  • The component should be accessible and follow WCAG 2.1 guidelines

Bundled Resources

resources/

Contains the official SVG icons for each AI platform:

  • chatgpt.svg - OpenAI ChatGPT hexagonal aperture icon
  • claude.svg - Anthropic Claude geometric pattern icon
  • gemini.svg - Google Gemini four-pointed star icon
  • grok.svg - xAI Grok crystalline pattern icon
  • perplexity.svg - Perplexity hexagonal cube icon

These icons MUST be copied to the user's project and used directly. Do not substitute with alternatives.

Success Criteria

A successful implementation should:

  1. Confirm the website domain with the user before proceeding
  2. Ask the user whether to include llms.txt generation
  3. If llms.txt chosen: Produce a curated, well-structured llms.txt file under 100KB
  4. Create a visually consistent footer component with correct branding
  5. Use the appropriate prompt template based on the user's llms.txt decision
  6. Generate working links that pre-populate prompts in each AI platform
  7. Be accessible on both desktop and mobile devices
  8. Use the bundled SVG icons from resources/ (no substitutes)

平台分布

Claude Code

27.13%
按下载量换算65

Antigravity

23.13%
按下载量换算56

windsurf

20.05%
按下载量换算48

Codex

12.33%
按下载量换算30

OpenCode

8.85%
按下载量换算21

Gemini CLI

3.3%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

继续浏览同类 Skills