GEO Content Auditor — AI Answerability Score

Audit any webpage for AI-answerability. Get a 0–100 score per page and a prioritized fix list so ChatGPT, Perplexity, Claude, and Gemini start citing your content in answers.

This is the "fix your own pages" piece of the GEO family: the AI Visibility Rank Tracker tells you if you're being mentioned; the AI Citation Monitor shows which sources AI cites; the GEO Content Auditor tells you why your page isn't being picked and exactly what to change.

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What it audits

Each page is scored across 5 dimensions (100 pts total):

Dimension	Max	What it checks
Structure	30	Question-style headings, direct answer near top, FAQ sections, lists/tables, H1-H3 hierarchy
Extractable facts	25	Specific stats, dates, named entities, clear definitions, concrete examples
Entity clarity	20	Brand clearly defined, author byline, JSON-LD structured data, product clearly named
Machine readability	15	Semantic markup, content chunkability, llms.txt presence
Authority signals	10	Sources cited, publication date, internal links, breadcrumbs

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Output per page

{
  "url": "https://example.com/blog/best-tools",
  "page_title": "Best Productivity Tools 2026",
  "ai_answerability_score": 61,
  "grade": "C",
  "structure_score": 18,
  "facts_score": 15,
  "entity_score": 12,
  "readability_score": 10,
  "authority_score": 6,
  "strengths": ["Clear H2 headings", "Includes specific statistics"],
  "issues": [
    "No FAQ schema — add FAQPage JSON-LD to become directly quotable",
    "No direct 1-sentence answer in opening paragraph",
    "Brand name not defined clearly — add Organization JSON-LD"
  ],
  "quick_wins": [
    "Add FAQPage JSON-LD with 5 buyer questions",
    "Open with a direct 1-sentence answer",
    "Add publication and last-updated dates"
  ],
  "missing_schema_types": ["FAQPage", "Organization"],
  "suggested_qa_pairs": [
    { "question": "What is the best productivity tool for teams?", "answer_hint": "Compare top 3 with use cases" }
  ],
  "llms_txt_present": false,
  "has_json_ld": false,
  "word_count": 1240,
  "prompt_fit_score": 55,
  "error": null,
  "audited_at": "2026-06-08T12:00:00.000Z"
}

Plus a SUMMARY in the key-value store: site-wide average score, top issues across all pages, quick wins, priority pages (lowest scoring = biggest opportunity), and a missing schema frequency table.

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Input

Field	Type	Description
startUrls	URL list	Pages to audit.
brandName	string	Your brand/product name (entity clarity check). Default: Apify.
targetPrompts	string[]	Buyer questions this content should answer. Optional — scores prompt-fit when provided.
maxPages	integer	Max pages per run (1–50). Default: 10.

The LLM model is managed internally for predictable cost and quality.

Example input

{
  "startUrls": [
    { "url": "https://yoursite.com/blog/best-tools" },
    { "url": "https://yoursite.com/product/features" }
  ],
  "brandName": "YourBrand",
  "targetPrompts": [
    "What is the best tool for X?",
    "How do I solve Y?"
  ],
  "maxPages": 10
}

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API key (required)

All LLM analysis runs through OpenRouter — set one environment variable in the Apify Console (Settings → Environment variables, mark Secret):

OPENROUTER_API_KEY = sk-or-...

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Pricing (Pay Per Event)

Event	When
actor-start	Once per run.
page-audited	Each successfully audited page.

Failed pages are not charged.

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Use cases

• GEO content strategy — find the exact structural and semantic gaps keeping your pages out of AI answers.
• Content audit before publishing — score new content before it goes live.
• Agency client reporting — deliver an AI-readiness score with actionable fixes.
• llms.txt gap detection — instantly see which of your domains are missing it.
• Pairs with AI Visibility Rank Tracker + AI Citation Monitor for the full GEO picture: are you cited? → what do AI engines cite? → why aren't your pages being picked?