Distribution
- GitHub repository: Canonry/aeo-audit
- npm package: @ainyc/aeo-audit
- License: MIT
Public Toolkit
@ainyc/aeo-audit
A public audit engine for the technical side of Answer Engine Optimization.
A public CLI and JavaScript library that audits 16 technical on-site factors we believe correlate with AI citation readiness. The tool scores only the on-site technical layer of AEO. Holistic AEO also depends on traditional SEO, content, and external linking. This tool represents our best working model for the on-site layer, not a guaranteed formula.
What Is Public Today
Documentation
- README with CLI and API examples
- Public changelog and roadmap
- Contribution guide for collaborators
How To Use It
CLI
npx @ainyc/aeo-audit https://example.comnpx @ainyc/aeo-audit https://example.com --format jsonJavaScript API
import { runAeoAudit } from '@ainyc/aeo-audit'const report = await runAeoAudit('https://example.com', { includeGeo: false })16-Factor On-Site Technical Scope
Structured Data (JSON-LD)
11%Presence of LocalBusiness, FAQPage, Service, and HowTo schemas.
Content Depth
9%Word count, heading hierarchy, paragraph structure, and list usage.
E-E-A-T Signals
7%Author meta, trust pages, credentials, and review-oriented trust signals.
FAQ Content
7%FAQPage schema, question headings, and direct-answer formatting.
Citations & Authority
7%External references, authoritative links, and sameAs-style corroboration.
Schema Completeness
7%Property depth and richness across the structured data stack.
Entity Consistency
6%Naming consistency across schema, title tags, and on-page identity.
Content Freshness
6%dateModified, Last-Modified, sitemap dates, and current copyright signals.
Content Extractability
6%How easy the content is for answer engines to parse and cite.
AI-Readable Content
5%llms.txt, llms-full.txt, robots.txt, and sitemap.xml availability.
Schema Validity
5%Syntactic and semantic correctness of JSON-LD: required properties, valid types, and zero parse errors.
Definition Blocks
5%Direct definitions, step lists, and HowTo-style explanation blocks.
Named Entities
5%Brand mentions, founder references, and proper-noun density.
Technical SEO
5%Canonical tags, meta descriptions, heading structure, image alt text, and core indexability signals.
Snippet Eligibility
5%Direct-answer formatting, lists, tables, and concise blocks that AI engines lift as inline citations.
AI Crawler Access
4%robots.txt rules for GPTBot, ClaudeBot, PerplexityBot, and peers.
Project Links
GitHub
Source code, issues, and project history.
Open repositorynpm
Install and run the package through npx or your own Node workflow.
Open npm packageProject docs
See how the project is evolving without mistaking roadmap items for shipped features.
What's Next
Directions we're exploring, not shipped features yet.
- npm release and CI integration for broader developer adoption
- site audit and baseline diff workflows
- policy-pack checks for engine-specific crawler rules
- trend tracking and export formats for recurring monitoring
From Our Blog
We Open-Sourced Our AEO Audit Engine
Why Canonry published @ainyc/aeo-audit, what the 13-factor model measures, and what teams can learn from it.
Read the article