Analyze AIO scores content readiness for AI answer engines like ChatGPT, Perplexity, and Gemini. An Analyze ecosystem plugin by DXPR.

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AI Optimization Analysis: AI Answer Engine Readiness Scoring for Drupal

Automated analysis measuring how well your content is structured for AI answer engines (ChatGPT, Perplexity, Gemini, Google AI Overviews).

Features

• 8 Deterministic Checks: Heading hierarchy, JSON-LD structured data, meta tag completeness, semantic HTML, FAQ patterns, internal link density, plus optional AI checks
• Visual Feedback: Gauge displays with percentage scores and progressive-disclosure full reports grouped by severity
• Educational Reports: Each failing check explains why it matters for AI answer engines and what to do, teaching AIO alongside scoring
• Analyze Framework Integration: Consistent UI and reporting across all analysis tools
• Batch Processing: Analyse large content volumes efficiently via GUI or Drush
• Smart Caching: Content-hash-based cache invalidation; results are only recomputed when content changes

Requirements

• Analyze framework (>=1.3.0)
• Views Color Scales (>=1.1.0)

Optional:

• AI module with configured provider (enables citation readiness and tone authority checks)

Installation

composer require drupal/analyze_aio
drush en analyze_aio

Configuration

Basic Setup

1. Enable per content type at /admin/config/content/analyze-settings
2. Configure checks at /admin/config/analyze/aio
3. Configure permissions at /admin/people/permissions#module-analyze_aio

Optional AI Checks

1. Configure an AI provider at /admin/config/ai/providers
2. Enable AI checks at /admin/config/analyze/aio
3. Two additional checks become available: citation readiness and tone authority

Check Reference

Check	What it scores
Heading Hierarchy	Single H1, proper nesting, question-shaped headings
JSON-LD	Structured data with content-type and AI-friendly schemas
Meta Completeness	Title, description, Open Graph, canonical URL
Semantic HTML	article, section, figure, time, details elements
FAQ Detection	FAQ schema, definition lists, question headings
Internal Link Density	Internal and external link coverage
Citation Readiness	AI: whether content is structured for citation
Tone Authority	AI: expertise signals and authoritative voice

AI Coding Assistant Integration

The AIO module includes a built-in Agent Skills file (via the base Analyze module) that teaches AI coding assistants how to run AI optimisation analysis through natural language. Run drush analyze:setup-ai to enable, then ask naturally:

"Analyse AI optimisation readiness on all articles"
"Check structured data on the about page"
"Run AIO and SEO analysis together on blog posts"

Batch processing is available via the centralised Analyze batch system:

# Check analysis coverage
drush analyze:batch --status

# Run this analyzer on all enabled content types
drush analyze:batch \
  --analyzers=analyze_aio_readiness

# Run on specific content types with limit
drush analyze:batch \
  --analyzers=analyze_aio_readiness \
  --types=node:article --limit=50

# Force re-analysis of already analysed content
drush analyze:batch \
  --analyzers=analyze_aio_readiness --force

Compatible with Claude Code, Codex CLI, Gemini CLI, GitHub Copilot, Cursor, and other tools supporting the Agent Skills standard.

Analysis

Results show AI optimisation scores with visual gauge progression and progressive-disclosure full reports. Cache invalidation is automatic; content is only re-analysed when it changes.

Display Options

• Gauge visualisation with clear progression
• Full report with severity-grouped checks (Needs attention / Can be improved / Passed)
• Views integration for custom reports
• Colour-coded results with Views Color Scales module

Development

Docker Commands

# Lint code
docker compose run --rm drupal-lint

# Check deprecations
docker compose run --rm drupal-check

# Auto-fix issues
docker compose run --rm drupal-lint-auto-fix

Pre-commit Hook

Automatically runs linting checks before commits:

• Auto-fixes coding standard violations
• Blocks commits with remaining issues
• Provides coloured output for feedback

Related Modules

Required dependencies; this module directly uses their APIs:

• Analyze - Content analysis framework; this module extends AnalyzePluginBase and implements BatchableAnalyzerInterface
• Views Color Scales - Colour-coded score display in the bundled AIO Views report

Optional integration:

• AI - LLM provider layer; enables citation readiness and tone authority checks

Sibling Analyze plugins:

• SEO Analysis - Traditional SEO scoring
• AI Brand Voice - Brand voice consistency scoring
• AI Sentiments Analysis - Multi-dimensional content tone analysis
• Broken Links Analyzer - Link health monitoring per page
• Search Console Analyzer - Google Search performance per page