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Agent Skill · 研究检索

browse-aeo(浏览 aeo)

browse-aeo 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。

browse-aeo 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,权限为操作浏览器;许可证信息还不明确,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 65,084。

总安装 288周安装 12GitHub Stars 公开资料未说明下载 96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:browse-aeo(浏览 aeo)
来源仓库:https://github.com/ulpi-io/skills
仓库路径:skills/browse-aeo
安装命令:
npx skills add https://github.com/ulpi-io/skills --skill browse-aeo
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/ulpi-io/skills --skill browse-aeo

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。

browse-aeo 用于评估页面是否符合 Answer Engine Optimization(AEO)标准。它检查 JSON-LD、FAQPage 等结构化数据存在性,分析其在 AI 搜索结果中的表现潜力。使用时可针对单 URL 做审计,输出可读性强、可操作的优化建议清单。

需配合浏览 CLI 使用,部分高级功能依赖 camoufox 绕过反爬机制。browse-aeo 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/browse-aeo

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/ulpi-io/skills --skill browse-aeo;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

    它需要操作浏览器,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

browse-aeo 怎么安装?

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

browse-aeo 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。

browse-aeo 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

browse-aeo 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。

browse-aeo 用的人多吗?

公开数据是累计安装 288 次,近一周安装 12 次,下载 96 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。

browse-aeo 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。

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
browse-aeo

浏览 aeo · 本页

288—操作浏览器未明确有提醒

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

browse-aeo: Answer Engine Optimization

Goal

Audit a page for AEO readiness or analyze how a query surfaces in AI-powered search. Two modes: Page Audit (analyze a URL) and SERP Analysis (analyze a search query).

Mode 1: Page Audit

Evaluate a single URL for AEO readiness. Run each step in order.

Step 1: Navigate and stabilize

browse goto <url>
browse wait --network-idle

Step 2: Extract structured data

browse schema

Analyze for: JSON-LD presence (critical for AEO), FAQPage schema (directly feeds AI answers), HowTo schema (surfaces in how-to answers), Article/NewsArticle/BlogPosting (attribution), Organization/Person (authority), Breadcrumb (hierarchy), QAPage (Q&A pairs). Empty or minimal structured data is a major AEO gap.

Step 3: Extract and evaluate meta tags

browse meta

Check: meta description (concise direct answer, under 160 chars -- AI uses this as candidate snippet), canonical URL (must be present), Open Graph tags (og:title, og:description), robots directives (noindex or nosnippet blocks AI citation entirely).

Step 4: Analyze heading hierarchy

browse headings

Evaluate: single H1 (clear topic statement), H2s as questions or clear topic labels (AI uses headings to find answer boundaries), question-format H2s ("What is X?", "How to Y?") are strongly preferred, logical nesting (no skipped levels).

Step 5: Analyze page content for answer patterns

browse text

Scan for: direct definitions in the first paragraph ("X is a..." -- AI favors concise leads), FAQ patterns (Q&A pairs even without schema), numbered/bulleted lists (AI prefers extractable structure), concise paragraphs (under 50 words are more likely cited), authority signals ("We tested...", "In our experience..." -- original research language).

Step 6: Produce the AEO audit report

Score the page on a 0-100 scale across these dimensions:

DimensionWeightWhat to check
Structured Data25%JSON-LD presence, FAQ/HowTo/Article schema, completeness
Meta Quality15%Description as answer snippet, canonical, no blocking robots
Heading Structure20%Single H1, question-format H2s, logical nesting
Answer Readiness25%Direct definitions, FAQ patterns, concise paragraphs, lists
Authority Signals15%Organization schema, author markup, original research language

Report: overall score out of 100, per-dimension score with findings and recommendations, then the top 3 highest-impact actions.

Mode 2: SERP Analysis

Check how a query appears in AI-powered search results.

Step 1: Google search with AI Overview detection

browse goto "https://www.google.com/search?q=<url-encoded-query>"
browse wait --network-idle
browse snapshot -i

Read the snapshot to identify: AI Overview (generative answer block, note cited domains), Featured Snippet (boxed answer, note source domain), People Also Ask (expandable questions -- these are AEO targets), organic position of target domain.

If Google blocks the request, retry with camoufox:

browse --runtime camoufox --headed goto "https://www.google.com/search?q=<url-encoded-query>"
browse --runtime camoufox --headed snapshot -i

Step 2: Perplexity analysis (camoufox recommended)

Perplexity has bot detection. Use camoufox:

browse --runtime camoufox --headed goto "https://www.perplexity.ai/search?q=<url-encoded-query>"
browse --runtime camoufox --headed wait --network-idle
browse --runtime camoufox --headed snapshot -i

Read the snapshot to identify: cited source domains (numbered citations), answer structure (paragraphs, lists, tables), citation density. If Perplexity blocks, note it in the report and skip.

Step 3: Produce the SERP analysis report

Report: for each engine (Google, Perplexity), list AI Overview presence, cited domains, featured snippet source, People Also Ask questions, and target domain position. End with observations on what content types are being cited and specific actions to improve citation likelihood.

Key Rules

  1. Always wait after navigation -- browse wait --network-idle before extracting content.
  2. Use camoufox for search engines -- Google and Perplexity actively block headless browsers. Fall back to --runtime camoufox --headed when blocked.
  3. Agent interprets snapshots -- there is no magic SERP parser. The agent reads browse snapshot -i output and identifies AI Overview elements, citations, and People Also Ask by reading the accessibility tree.
  4. Structured data is the top signal -- JSON-LD FAQ and HowTo schemas are the single most impactful AEO lever. Always check this first.
  5. Do not fabricate scores -- if a dimension cannot be evaluated (e.g., page is behind a login wall), mark it as "N/A" and explain why.
  6. Keep recommendations actionable -- "Add FAQ schema" is good. "Improve SEO" is not.

Guardrails

  • Do not add disable-model-invocation; this is a general-purpose audit skill.
  • Do not add context: fork; audit results are needed in the current flow.
  • Do not run browse handoff without explicit user confirmation.
  • Do not guess SERP structure -- always take a snapshot and read it.
  • Do not claim a page "appears in AI Overviews" without actually checking via SERP analysis.

Output Contract

Report:

  1. the mode used (Page Audit or SERP Analysis)
  2. the URL audited or query analyzed
  3. findings per dimension with specific evidence
  4. actionable recommendations ranked by impact
  5. any blockers encountered (bot detection, login walls, empty results)

平台分布

Codex

34.69%
按下载量换算33

Claude

31.14%
按下载量换算30

Cursor

18.33%
按下载量换算18

Gemini CLI

8.7%
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

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。目前只有一个公开来源,建议同时核对源仓库。

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