# AI Visibility Audit - ChatGPT, Gemini, Claude (GEO/AEO) (`piposlab/ai-visibility-audit`) Actor Check if your brand shows up in AI assistant answers (ChatGPT, Gemini, Claude) for buyer-intent prompts. Get an AI visibility score, competitor share-of-voice, and gaps. - **URL**: https://apify.com/piposlab/ai-visibility-audit.md - **Developed by:** [Alejandro Bufarini](https://apify.com/piposlab) (community) - **Categories:** AI, SEO tools - **Stats:** 2 total users, 0 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 ## AI Visibility Audit - ChatGPT, Gemini, Claude (GEO / AEO) When your customers ask AI assistants ("what's the best X?", "recommend a Y"), **does your brand show up?** This actor measures it. It runs realistic buyer-intent prompts across **ChatGPT, Google Gemini and Claude**, checks whether your brand appears in the answers, and compares you to competitors. This is **GEO / AEO** (Generative Engine Optimization / Answer Engine Optimization): the 2026 version of SEO for AI search. ### What you get - An **AI Visibility Score** (0-100): how often you appear across engines + prompts - **Per-engine breakdown** (are you in ChatGPT but missing in Gemini?) - **Competitor share-of-voice** (who the AI recommends instead of you) - **Every prompt + answer excerpt**, flagged for brand/competitor mentions, so you see exactly where you're invisible ### Input - `brand` (required), `category`, `website`, `competitors[]`, `promptCount`, optional `customPrompts[]`, `engines[]`. - If you don't supply prompts, it generates realistic buyer prompts for your category automatically. ### Output A `summary` record (score, breakdown, share-of-voice) plus one `answer` record per promptร—engine with the excerpt and mention flags. ### Honest scope It tests each model's answers for your prompts. A low score means buyers using AI assistants are unlikely to be shown your brand โ€” the actionable signal GEO work targets. Uses public LLM APIs. # Actor input Schema ## `brand` (type: `string`): The brand to audit (exact name as buyers would say it). ## `website` (type: `string`): Brand website (context). ## `category` (type: `string`): What the brand does, e.g. 'project management software'. ## `competitors` (type: `array`): Competitor names to compare share-of-voice against. ## `customPrompts` (type: `array`): Override the auto-generated buyer prompts. ## `promptCount` (type: `integer`): How many buyer-intent prompts to test. ## `engines` (type: `array`): AI engines to test: openai, gemini, anthropic. ## Actor input object example ```json { "brand": "Notion", "category": "note-taking and docs app", "promptCount": 12, "engines": [ "openai", "gemini", "anthropic" ] } ```` # 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 = { "brand": "Notion", "category": "note-taking and docs app" }; // Run the Actor and wait for it to finish const run = await client.actor("piposlab/ai-visibility-audit").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "brand": "Notion", "category": "note-taking and docs app", } # Run the Actor and wait for it to finish run = client.actor("piposlab/ai-visibility-audit").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "brand": "Notion", "category": "note-taking and docs app" }' | apify call piposlab/ai-visibility-audit --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=piposlab/ai-visibility-audit", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Visibility Audit - ChatGPT, Gemini, Claude (GEO/AEO)", "description": "Check if your brand shows up in AI assistant answers (ChatGPT, Gemini, Claude) for buyer-intent prompts. Get an AI visibility score, competitor share-of-voice, and gaps.", "version": "0.1", "x-build-id": "OuBnb3PjKJuRpbUcW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/piposlab~ai-visibility-audit/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-piposlab-ai-visibility-audit", "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/piposlab~ai-visibility-audit/runs": { "post": { "operationId": "runs-sync-piposlab-ai-visibility-audit", "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/piposlab~ai-visibility-audit/run-sync": { "post": { "operationId": "run-sync-piposlab-ai-visibility-audit", "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": [ "brand" ], "properties": { "brand": { "title": "Brand / company name", "type": "string", "description": "The brand to audit (exact name as buyers would say it)." }, "website": { "title": "Website", "type": "string", "description": "Brand website (context)." }, "category": { "title": "Category", "type": "string", "description": "What the brand does, e.g. 'project management software'." }, "competitors": { "title": "Competitors", "type": "array", "description": "Competitor names to compare share-of-voice against.", "items": { "type": "string" } }, "customPrompts": { "title": "Custom prompts (optional)", "type": "array", "description": "Override the auto-generated buyer prompts.", "items": { "type": "string" } }, "promptCount": { "title": "Number of prompts", "minimum": 3, "maximum": 40, "type": "integer", "description": "How many buyer-intent prompts to test.", "default": 12 }, "engines": { "title": "Engines", "type": "array", "description": "AI engines to test: openai, gemini, anthropic.", "default": [ "openai", "gemini", "anthropic" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```