# AI Visibility Site Audit — robots.txt & llms.txt checks (`43sunsets/ai-visibility-site-audit`) Actor Audit how visible your own website is to AI crawlers and assistants: robots.txt rules for 13 AI bots, llms.txt, structured data, meta hygiene and sitemap — with a scored report and a ready-to-edit llms.txt draft. - **URL**: https://apify.com/43sunsets/ai-visibility-site-audit.md - **Developed by:** [Ken Yao](https://apify.com/43sunsets) (community) - **Categories:** Developer tools, Automation, Agents - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $250.00 / 1,000 report generateds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 Site Audit Find out — in one run — whether AI crawlers and assistants can actually see your website, and what they see. AI assistants are becoming a real discovery channel. But their crawlers read your site differently than Google does, and most sites have never checked what those bots are allowed to access. This Actor audits **your own site** and returns a scored report (0–100) plus a ready-to-edit `llms.txt` draft. ### What it checks 1. **AI crawler access** — your `robots.txt` rules evaluated for 13 AI crawlers (GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, Claude-Web, anthropic-ai, Google-Extended, PerplexityBot, CCBot, Bytespider, Amazonbot, Applebot-Extended, meta-externalagent). Blocked, partial or allowed — per bot, with the exact rule that applies. 2. **llms.txt / llms-full.txt** — present or not, plus a generated draft built from your actual pages. 3. **Structured data** — JSON-LD presence and types per page (unparseable blocks are flagged too). 4. **Titles & meta descriptions** — presence and length hygiene on every crawled page. 5. **Canonical & indexability** — canonical tags and accidental `noindex`. 6. **sitemap.xml** — present or not. 7. **Thin / JS-rendered content** — pages whose raw HTML contains almost no text, which is what many bots actually see. ### What you get - `REPORT` (Markdown, in the run's key-value store): the full scored audit with per-bot table, per-page findings, and your llms.txt draft. - Dataset: one row per crawled page with all checks, ready to sort and filter. - `OUTPUT`: the summary object (score, grade, category breakdown) for automation. ### Input | Field | Description | |---|---| | `startUrl` | Your website. The crawl stays on this hostname only. | | `maxPages` | Page limit (default 25, max 200). Each crawled page is one billed event. | ### Honest notes - **llms.txt is an emerging convention.** Google has publicly stated it does not affect ranking, and adoption by AI tools is uneven. We report it as low-cost hygiene, not a magic growth switch. - **Static analysis.** Pages are fetched as raw HTML without JavaScript rendering — which is exactly how many crawlers see them. Pages that depend on JS are flagged rather than rendered. - **Blocking AI bots can be the right choice.** The audit makes your current state visible so it is a decision, not an accident. - The Actor audits only the site you provide, stays on the same hostname, and **respects robots.txt** during its own crawl. ### Pricing Pay per event: a small start fee, a per-page fee for each crawled page, and a report fee. Control cost with `maxPages` — a 25-page audit costs well under a dollar. # Actor input Schema ## `startUrl` (type: `string`): The site you own or manage. The audit crawls this site only, stays on the same hostname, and respects robots.txt. ## `maxPages` (type: `integer`): Upper limit of pages crawled (each crawled page is billed as one page-crawled event). ## Actor input object example ```json { "startUrl": "https://www.example.com", "maxPages": 25 } ```` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("43sunsets/ai-visibility-site-audit").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 = {} # Run the Actor and wait for it to finish run = client.actor("43sunsets/ai-visibility-site-audit").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 '{}' | apify call 43sunsets/ai-visibility-site-audit --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=43sunsets/ai-visibility-site-audit", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Visibility Site Audit — robots.txt & llms.txt checks", "description": "Audit how visible your own website is to AI crawlers and assistants: robots.txt rules for 13 AI bots, llms.txt, structured data, meta hygiene and sitemap — with a scored report and a ready-to-edit llms.txt draft.", "version": "1.0", "x-build-id": "8HrlyzRgZVxHwYVPK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/43sunsets~ai-visibility-site-audit/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-43sunsets-ai-visibility-site-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/43sunsets~ai-visibility-site-audit/runs": { "post": { "operationId": "runs-sync-43sunsets-ai-visibility-site-audit", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/43sunsets~ai-visibility-site-audit/run-sync": { "post": { "operationId": "run-sync-43sunsets-ai-visibility-site-audit", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrl" ], "properties": { "startUrl": { "title": "Your website URL", "type": "string", "description": "The site you own or manage. The audit crawls this site only, stays on the same hostname, and respects robots.txt.", "default": "https://www.example.com" }, "maxPages": { "title": "Maximum pages to check", "minimum": 1, "maximum": 200, "type": "integer", "description": "Upper limit of pages crawled (each crawled page is billed as one page-crawled event).", "default": 25 } } }, "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 } } } } } } } } } } ```