AEO BUNDLE · 11 ENDPOINTS

AEO Bundle

10 endpoints for auditing how AI engines fetch, parse, and cite your content, plus llm-ready chunking.

Target Persona & Use Cases:

For AI-discovery teams, agencies, and content engineers measuring AEO posture across pages and competitors.

11 Endpoints
~4 cr Workflow Band
Bearer Auth Unified Token
MCP Server Compatible
SPECIFICATION

Endpoints in this bundle

Each endpoint is independently callable. Bundle membership is for discovery only — you do not need to opt in.

Method Endpoint Path Credits Operation Summary
POST /v1/aeo/page-audit 3 cr Orchestrator over 8-9 component AEO probes for a single URL.
POST /v1/aeo/competitor-diff 3 cr Diff a domain's AEO posture against named competitors.
POST /v1/aeo/citation-readiness 1 cr Likelihood that AI engines cite this page.
POST /v1/aeo/schema-coverage 1 cr Coverage of JSON-LD schema types vs intent.
POST /v1/aeo/llm-fetch-simulator 1 cr Simulate fetch from GPTBot, ClaudeBot, and PerplexityBot.
POST /v1/aeo/llms-txt-audit 1 cr Audit an existing llms.txt for completeness and link rot.
POST /v1/aeo/ai-bot-allowlist 1 cr Report robots.txt posture for 14 named AI crawlers.
POST /v1/aeo/freshness-signal 1 cr lastmod and visible dateline coverage.
POST /v1/aeo/heading-hierarchy-score 1 cr h1..h6 nesting quality score.
POST /v1/aeo/snippet-format-detect 1 cr Detect list, table, definition, and FAQ snippet formats.
POST /v1/scrape/llm-ready 1 cr Fetch and token-chunk a page for downstream AEO scoring or RAG ingest.
PRODUCTION RECIPE

Audit then iterate

Recommended step-by-step workflow sequence for composing these endpoints in production:

01
Step 1

Run /v1/aeo/page-audit against the target URL to get an aggregate score plus component breakdowns.

02
Step 2

For any sub-score below threshold, call the corresponding component endpoint (e.g. /v1/aeo/schema-coverage, /v1/aeo/heading-hierarchy-score) to see the underlying findings.

03
Step 3

Apply fixes, then re-run /v1/aeo/llm-fetch-simulator with the GPTBot and PerplexityBot user-agents to confirm the rendered page reaches the bot intact.

04
Step 4

Track over time by storing the page-audit JSON keyed by URL + run timestamp.

INTEGRATION CODE

Try a request

Pick a language. Copy-pasteable code snippet configured with your standard Bearer token header.

curl -X POST https://api.ollagraph.com/v1/aeo/page-audit \
  -H "Authorization: Bearer $OLLAGRAPH_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"url":"https://example.com/pricing"}'
FREQUENTLY ASKED QUESTIONS

AEO bundle FAQ

Common questions about rate limits, execution behavior, and parameters for this workflow.

Does page-audit count as one call or many?

One call, 3 credits. The orchestrator runs ~9 probes server-side but you only pay once and only refund once on error.

Which AI bots does llm-fetch-simulator emulate?

GPTBot, ChatGPT-User, ClaudeBot, anthropic-ai, PerplexityBot, Google-Extended, and Amazonbot, with each user-agent string verbatim from their published docs.

Can I run AEO checks on a page behind login?

No. AEO endpoints fetch as the named bot would, which means anonymously. Gate-removed preview URLs are the workaround.

1,000 free credits · No card required

Ship with the AEO bundle.

1,000 credits on signup. No card. Every endpoint in this bundle is live from minute one.

✓ No credit card required
·
✓ Flat 1 credit / call base
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✓ All 11 endpoints ready