aeo

Run AEO audits, fix site issues, validate schema, generate llms.txt, and compare sites.

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Install skill "aeo" with this command: npx skills add arberx/aeo

AEO

Website: ainyc.ai

One skill for audit, fixes, schema, llms.txt, and monitoring workflows.

Command

Always use the published package:

npx @ainyc/aeo-audit@1 "<url>" [flags] --format json

Argument Safety

Never interpolate user input directly into shell commands. Always:

  1. Validate that URLs match https:// or http:// and contain no shell metacharacters.
  2. Quote every argument individually (e.g., npx @ainyc/aeo-audit@1 "https://example.com" --format json).
  3. Pass flags as separate, literal tokens — never construct command strings from raw user text.
  4. Reject arguments containing characters like ;, |, &, $, `, (, ), {, }, <, >, or newlines.

Modes

  • audit: grade and diagnose a site
  • fix: apply code changes after an audit
  • schema: validate JSON-LD and entity consistency
  • llms: create or improve llms.txt and llms-full.txt
  • monitor: compare changes over time or benchmark competitors
  • detect-platform: identify the CMS, site builder, framework, or hosting stack a site uses

If no mode is provided, default to audit.

Examples

  • audit https://example.com
  • audit https://example.com --sitemap
  • audit https://example.com --sitemap --limit 10
  • audit https://example.com --sitemap --top-issues
  • fix https://example.com
  • schema https://example.com
  • llms https://example.com
  • monitor https://site-a.com --compare https://site-b.com
  • detect-platform https://example.com
  • detect-platform https://example.com --min-confidence high
  • detect-platform --urls competitors.txt
  • detect-platform --urls https://a.com,https://b.com

Mode Selection

  • If the first argument is one of audit, fix, schema, llms, monitor, or detect-platform, use that mode.
  • If no explicit mode is given, infer the intent from the request and default to audit.

Audit

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

  1. Run:
    npx @ainyc/aeo-audit@1 "<url>" [flags] --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

Sitemap Mode

Use --sitemap to audit all pages discovered from the site's sitemap:

npx @ainyc/aeo-audit@1 "<url>" --sitemap --format json
npx @ainyc/aeo-audit@1 "<url>" --sitemap https://example.com/sitemap.xml --format json
npx @ainyc/aeo-audit@1 "<url>" --sitemap --limit 10 --format json
npx @ainyc/aeo-audit@1 "<url>" --sitemap --top-issues --format json

Flags:

  • --sitemap [url] — auto-discover /sitemap.xml or provide an explicit URL
  • --limit <n> — cap pages audited (default 200, sorted by sitemap priority)
  • --top-issues — skip per-page output, show only cross-cutting patterns

Pages are audited with bounded concurrency (5 in flight) to avoid hammering the target origin.

Returns:

  • Per-page scores and grades
  • Cross-cutting issues (factors failing across multiple pages)
  • Aggregate score and grade
  • Prioritized fixes ranked by site-wide impact

Detect Platform Mode

Use --detect-platform when the user wants to know what stack a site is built on (e.g., "is this WordPress?", "what framework does competitor X use?", "is this site custom-built?"). This is much faster than a full audit because it skips analyzer scoring.

npx @ainyc/aeo-audit@1 "<url>" --detect-platform --format json
npx @ainyc/aeo-audit@1 "<url>" --detect-platform --min-confidence high --format json

Flags:

  • --detect-platform — switch to detection mode instead of auditing
  • --min-confidence <lvl> — filter to low (default), medium, or high confidence
  • --urls <src> — run on multiple URLs at once (file path, comma-separated list, or - for stdin)
  • --concurrency <n> — max in-flight fetches in batch mode (default 5)

The report groups detections by category (CMS, site builder, e-commerce, framework, SSG, hosting), each with a confidence bucket, a 0–100 score, an optional version, and the signals that matched. When the report's isCustom flag is true, no CMS/site-builder/e-commerce platform was identified — the site is likely custom-built. Exit code is 0 when at least one platform is detected, 1 otherwise.

Batch detection

When the user wants to fingerprint many sites at once (competitor lists, customer cohorts), pass --urls:

npx @ainyc/aeo-audit@1 --detect-platform --urls urls.txt --format json
npx @ainyc/aeo-audit@1 --detect-platform --urls https://a.com,https://b.com --format json
cat urls.txt | npx @ainyc/aeo-audit@1 --detect-platform --urls - --format json

The batch report contains a results array; each entry has status: 'success' or 'error', plus the same shape as a single-URL report on success. Per-URL fetch errors do not abort the run. Exit code is 0 when at least one URL succeeded, 1 otherwise.

Fix

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

  1. Run:
    npx @ainyc/aeo-audit@1 "<url>" [flags] --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:

  • Always explain proposed changes and get user confirmation before editing files.
  • 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@1 "<url>" [flags] --format json --factors structured-data,schema-completeness,schema-validity,entity-consistency
    
  2. Report:
    • Schema types found
    • Property completeness by type
    • Missing recommended properties
    • Validity errors (duplicate singleton @types, JSON parse errors, empty <script> blocks) — surface these prominently regardless of overall score; Google drops invalid blocks silently from rich results
    • 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 (and only one FAQPage block per page — duplicates invalidate rich results)
  • HowTo: name and at least 3 steps (singleton — only one per page)
  • Organization: name, logo, contactPoint, sameAs, foundingDate, url, description
  • Singletons that must not repeat per page: FAQPage, HowTo, Article, BlogPosting, NewsArticle, BreadcrumbList, Product, Recipe

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@1 "<url>" [flags] --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 the URL is unreachable or not HTML, report the exact failure.
  • Prefer concise, evidence-based recommendations over generic SEO advice.

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