# AEO / GEO Readiness Auditor (`tom2turnt/aeo-readiness-auditor`) Actor Audits public web pages for AI answer-engine (AEO/GEO) + SEO citation-readiness — structured data, answer-up-front, freshness, E-E-A-T, meta — with a 0-100 score and concrete fixes. - **URL**: https://apify.com/tom2turnt/aeo-readiness-auditor.md - **Developed by:** [Tommy G](https://apify.com/tom2turnt) (community) - **Categories:** SEO tools, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## AEO / GEO Readiness Auditor (Apify Actor) Audit any public web page for how ready it is to be **cited by AI answer engines** (ChatGPT, Google AI Overviews, Perplexity) *and* by classic search — then get a **0–100 score, a letter grade, and concrete fixes**. HTML-only (no headless browser), so it is fast and cheap to run. ### What it checks (page-type-aware) Structured-data presence **and quality for the page type** · question-shaped headings · concise answer-up-front block · semantic HTML · entity/`sameAs` signals · title · meta description (incl. `og:description` fallback) · canonical · Open Graph · Twitter card · H1 · heading structure · substantive content (CJK-aware word count) · freshness · author/E-E-A-T · language · image-alt coverage. Detects **page type** (article / qa / product / listing / homepage / other) and scores only the checks that apply to that type. `noindex` pages are capped to 0 / F and flagged `citable: false`. Likely client-rendered (SPA) pages are flagged `confidence: low` rather than silently failed. ### Input ```json { "startUrls": [{ "url": "https://example.com/blog/post" }], "maxConcurrency": 5, "maxPages": 100 } ```` `maxPages` is capped at 200 and `maxConcurrency` at 20 per run (cost guard). ### Output — one STABLE record per URL (ok *and* error rows share this shape) ```json { "status": "ok", "requested_url": "https://example.com/blog/post", "final_url": "https://example.com/blog/post", "http_status": 200, "redirected": false, "page_type": "article", "citable": true, "readiness_score": 86, "grade": "A", "confidence": "high", "render_warning": null, "truncated": false, "blocked_from_indexing": false, "schema_types": ["Article"], "word_count": 612, "title": "...", "meta_description": "...", "checks": { "schemaQuality": { "pass": true, "applicable": true, "weight": 10, "detail": "..." }, "...": {} }, "strengths": ["schemaQuality", "title", "..."], "recommendations": ["Add the citation-relevant schema type ...", "..."], "summary": "Strong article (86/A) — citation-ready; 2 minor opportunities remain.", "audited_at": "2026-05-29T..." } ``` Failed fetches return the **same keys** with `status: "error"`, an `error` message, and `null` scores — so the dataset exports to a clean table. Filter `status == "ok"` before averaging. ### Why it's useful (and money-first) Every site owner in 2026 wants to know "will AI tools cite my page?" — there is no clean, cheap answer for that. This gives a per-page score + a fix list. It is also **dual-use**: the system runs it on its own (and clients') sites for the GEO/AEO citation service. ### Run locally / test (no Apify account needed) ```bash npm install npm test ## unit tests on the pure audit logic (node:test) ``` ### Publish to Apify (the account-holder's step) The free Apify account covers building + publishing free actors (no KYC, no payment). Monetization (pay-per-result pricing + payout) requires the **adult account-holder's** KYC and is a later step. ```bash npm install -g apify-cli apify login ## in the free Apify account apify push ## from this directory — uploads + builds the actor ``` Then, in the Apify Console: set the actor to **Public**, write the store listing (use this README), and keep it **free** initially to learn the discovery algorithm and earn reviews. Only enable pricing later, via the adult account-holder, once the actor shows real repeat organic usage and clears a margin gate (profit = 0.8·revenue − compute). ### Notes / safety - **SSRF-guarded:** rejects non-`http(s)` schemes and private/loopback/link-local/metadata hosts (e.g. `169.254.169.254`, `localhost`, `10.x`), and re-checks every redirect hop. - **Respects robots.txt** and rate-limits (`maxRequestsPerMinute`), per-host politeness. - **Cost-guarded:** `maxPages` ceiling 200, `maxConcurrency` ceiling 20, 1 retry, 30 s/req. - **Stores derived signals only** — no raw page bodies or personal data in the dataset. - HTML-only (no JS execution): genuinely client-rendered pages are flagged `confidence: low` with a `render_warning`, not silently failed. Audit only URLs you have the right to audit. - Core logic is in `src/audit.js` (pure, 14 unit tests + regression cases); `src/main.js` is the Apify wrapper; shared core in `src/lib/` (`jsonld`, `normalize`, `ssrf`). - Known residual: hostname/IP-literal SSRF guard does not resolve DNS (DNS-rebinding mitigated by platform egress controls); HTML-only rendering; heuristic page-type detection. # Actor input Schema ## `startUrls` (type: `array`): Public page URLs to audit for AEO/GEO + SEO citation-readiness. ## `maxConcurrency` (type: `integer`): How many pages to audit in parallel (capped at 20). ## `maxPages` (type: `integer`): Cost guard: maximum pages audited per run (hard ceiling 200). ## Actor input object example ```json { "startUrls": [ { "url": "https://blog.cloudflare.com/" } ], "maxConcurrency": 5, "maxPages": 100 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ { "url": "https://blog.cloudflare.com/" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("tom2turnt/aeo-readiness-auditor").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [{ "url": "https://blog.cloudflare.com/" }] } # Run the Actor and wait for it to finish run = client.actor("tom2turnt/aeo-readiness-auditor").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ { "url": "https://blog.cloudflare.com/" } ] }' | apify call tom2turnt/aeo-readiness-auditor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=tom2turnt/aeo-readiness-auditor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AEO / GEO Readiness Auditor", "description": "Audits public web pages for AI answer-engine (AEO/GEO) + SEO citation-readiness — structured data, answer-up-front, freshness, E-E-A-T, meta — with a 0-100 score and concrete fixes.", "version": "0.1", "x-build-id": "rT0Olq6bDWCadW5zv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/tom2turnt~aeo-readiness-auditor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-tom2turnt-aeo-readiness-auditor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/tom2turnt~aeo-readiness-auditor/runs": { "post": { "operationId": "runs-sync-tom2turnt-aeo-readiness-auditor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/tom2turnt~aeo-readiness-auditor/run-sync": { "post": { "operationId": "run-sync-tom2turnt-aeo-readiness-auditor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "startUrls" ], "properties": { "startUrls": { "title": "URLs to audit", "type": "array", "description": "Public page URLs to audit for AEO/GEO + SEO citation-readiness.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "How many pages to audit in parallel (capped at 20).", "default": 5 }, "maxPages": { "title": "Max pages", "minimum": 1, "maximum": 200, "type": "integer", "description": "Cost guard: maximum pages audited per run (hard ceiling 200).", "default": 100 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```