browse-aeo

Q: How do I install browse-aeo?

Run npx skills add https://github.com/ulpi-io/skills --skill browse-aeo in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/browse-aeo/ (personal) or .claude/skills/browse-aeo/ (project).

by ulpi-ioSecurity

Score a page for how well AI answer engines can CITE it — Answer Engine Optimization, not classic rankings — by pulling structured data, meta, headings, and answer-shaped content via the browse CLI (schema/meta/headings/text) into a weighted 0-100 audit, plus a SERP mode that reads Google AI Overviews, Perplexity, and ChatGPT Search snapshots to see who actually gets cited. Never fabricates a score: an un-evaluable dimension is marked N/A, and "appears in AI Overviews" is asserted only after a real SERP check. Use to make a page answer-ready or to check its AI-answer visibility.

Installs: 110
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/ulpi-io/skills --skill browse-aeo

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads browse-aeo automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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:

Dimension	Weight	What to check
Structured Data	25%	JSON-LD presence, FAQ/HowTo/Article schema, completeness
Meta Quality	15%	Description as answer snippet, canonical, no blocking robots
Heading Structure	20%	Single H1, question-format H2s, logical nesting
Answer Readiness	25%	Direct definitions, FAQ patterns, concise paragraphs, lists
Authority Signals	15%	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

Always wait after navigation -- browse wait --network-idle before extracting content.
Use camoufox for search engines -- Google and Perplexity actively block headless browsers. Fall back to --runtime camoufox --headed when blocked.
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.
Structured data is the top signal -- JSON-LD FAQ and HowTo schemas are the single most impactful AEO lever. Always check this first.
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.
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:

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

FAQ

What does the browse-aeo skill do?

How do I install browse-aeo?

Run npx skills add https://github.com/ulpi-io/skills --skill browse-aeo in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/browse-aeo/ (personal) or .claude/skills/browse-aeo/ (project).

Which AI agents can use browse-aeo?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is browse-aeo safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains browse-aeo?

It is published by ulpi-io in ulpi-io/skills. It has 110 recorded installs.

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