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研究检索操作浏览器github未标认证来源可访问许可证需确认审计提醒

browse-aeo浏览 aeo

Agent Skill

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。

总安装

288

周安装

12

GitHub Stars

公开资料未说明

下载量

96
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

2

许可证

unknown

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: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

简介

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。

SKILL.md

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)

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

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

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

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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