aeo-audit

name	aeo-audit
description	Run AEO audits, fix site issues, validate schema, generate llms.txt, and compare sites.

AEO

Website: ainyc.ai

Audit and improve how AI systems understand, extract, and cite a website.

What It Covers

• Full AEO audits and score reviews
• Code fixes for weak or missing AEO signals
• JSON-LD and schema validation
• llms.txt and llms-full.txt generation
• Before-vs-after tracking and competitor comparisons

Common Requests

• Audit https://example.com
• Fix AEO issues for https://example.com in this repo
• Validate schema for https://example.com
• Generate llms.txt for this project
• Compare https://site-a.com --compare https://site-b.com

Mode Selection

• Use Audit for grading, diagnosis, and benchmarking.
• Use Fix when the user wants code changes.
• Use Schema for JSON-LD, missing properties, or entity consistency.
• Use llms.txt when the user wants AI-readable markdown files.
• Use Monitor for progress tracking or competitor comparisons.

Audit

Use for broad requests such as "audit this site" or "why am I not being cited?"

1. Run:

   npx @ainyc/aeo-audit@latest $ARGUMENTS --format json
   

2. Return:
   • Overall grade and score
   • Short summary
   • Factor breakdown
   • Top strengths
   • Top fixes
   • Metadata such as fetch time and auxiliary file availability

Fix

Use when the user wants code changes applied after the audit.

1. Run:

   npx @ainyc/aeo-audit@latest $ARGUMENTS --format json
   

2. Find factors with status partial or fail.
3. Apply targeted fixes in the current codebase.
4. Prioritize:
   • Structured data and schema completeness
   • llms.txt and llms-full.txt
   • robots.txt crawler access
   • E-E-A-T signals
   • FAQ markup
   • freshness metadata
5. Re-run the audit and report the score delta.

Rules:

• Do not remove existing schema or content unless the user asks.
• Preserve existing code style and patterns.
• If a fix is ambiguous or high-risk, explain the tradeoff before editing.

Schema

Use when the request is specifically about JSON-LD or schema quality.

1. Run:

   npx @ainyc/aeo-audit@latest $ARGUMENTS --format json --factors structured-data,schema-completeness,entity-consistency
   

2. Report:
   • Schema types found
   • Property completeness by type
   • Missing recommended properties
   • Entity consistency issues
3. Provide corrected JSON-LD examples when useful.

Checklist:

• LocalBusiness: name, address, telephone, openingHours, priceRange, image, url, geo, areaServed, sameAs
• FAQPage: mainEntity with at least 3 Q&A pairs
• HowTo: name and at least 3 steps
• Organization: name, logo, contactPoint, sameAs, foundingDate, url, description

llms.txt

Use when the user wants llms.txt or llms-full.txt created or improved.

If a URL is provided:

1. Run:

   npx @ainyc/aeo-audit@latest $ARGUMENTS --format json --factors ai-readable-content
   

2. Inspect existing AI-readable files if present.
3. Extract key content from the site.
4. Generate improved llms.txt and llms-full.txt.

If no URL is provided:

1. Inspect the current project.
2. Extract business name, services, FAQs, contact info, and metadata.
3. Generate both files from local sources.

After generation:

• Add <link rel="alternate" type="text/markdown" href="/llms.txt"> when appropriate.
• Suggest adding the files to the sitemap.

Monitor

Use when the user wants progress tracking or a competitor comparison.

Single URL:

1. Run the audit.
2. Compare against prior results in .aeo-audit-history/ if present.
3. Show overall and per-factor deltas.
4. Save the current result.

Comparison mode:

1. Parse --compare <url2>.
2. Audit both URLs.
3. Show side-by-side factor deltas.
4. Highlight advantages, weaknesses, and priority gaps.

Behavior

• If the task needs a deployed site and no URL is provided, ask for the URL.
• If the task is diagnosis only, do not edit files.
• If the task is a fix request, make edits and verify with a rerun when possible.
• If npx fails, suggest npm install -g @ainyc/aeo-audit.
• If the URL is unreachable or not HTML, report the exact failure.
• Prefer concise, evidence-based recommendations over generic SEO advice.