Aeo

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

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.