# AI Crawler Readiness Auditor (`nectared_screen/ai-crawler-readiness-auditor`) Actor Audit domains for llms.txt, robots.txt AI bot rules, sitemap hints, and public AI crawler readiness signals. - **URL**: https://apify.com/nectared\_screen/ai-crawler-readiness-auditor.md - **Developed by:** [jaehan byun](https://apify.com/nectared_screen) (community) - **Categories:** SEO tools, Developer tools, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $10.00 / 1,000 domain audits 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 Crawler Readiness Auditor Audit domains for AI crawler readiness signals: `llms.txt`, `llms-full.txt`, `robots.txt` rules for AI user agents, sitemap hints, and homepage references. ### What it does This Actor helps SEO, developer relations, documentation, and content teams check whether a site is easy for AI crawlers and agentic tools to discover. For each domain, it fetches public files only and returns a compact readiness score with concrete remediation notes. It does not log in, bypass access controls, use residential proxies, or crawl private content. ### Input - `domains`: Domains or URLs to audit. - `maxDomains`: Safety cap for one run. - `requestTimeoutSecs`: Timeout for each public HTTP request. - `checkHomepage`: Whether to fetch the homepage and look for discovery hints. Example: ```json { "domains": ["apify.com", "docs.apify.com", "example.com"], "maxDomains": 25, "requestTimeoutSecs": 12, "checkHomepage": true } ```` ### Output Each dataset item represents one audited domain. Important fields: - `readinessScore`: 0-100 score based on public AI discoverability signals. - `llmsTxt`: status, URL, line count, byte size, and extracted links for `/llms.txt`. - `llmsFullTxt`: status and size for `/llms-full.txt`. - `robots`: robots.txt status plus AI bot allow/disallow findings. - `sitemap`: sitemap hints from robots.txt, homepage HTML, and `/sitemap.xml`. - `issues`: concrete problems to fix. - `recommendations`: actionable next steps. Example output item: ```json { "domain": "example.com", "origin": "https://example.com", "readinessScore": 28, "grade": "D", "llmsTxt": { "exists": false, "statusCode": 404 }, "robots": { "exists": true, "aiBotRules": [] }, "sitemap": { "found": false, "urls": [] }, "issues": ["Missing /llms.txt", "No sitemap hints found"], "recommendations": ["Add /llms.txt with key documentation and product URLs"] } ``` ### Pricing When pay-per-event monetization is enabled, this Actor is intended to charge one `domain-audit` event per audited domain. It checks the user spending limit before auditing each domain. ### Limitations - The Actor checks public files and homepage HTML only; it is not a full-site crawler. - robots.txt interpretation is conservative and focused on AI-related user-agent names. - A high score means good public discovery hygiene, not guaranteed ranking in AI products. # Actor input Schema ## `domains` (type: `array`): Domains or website URLs to audit for AI crawler readiness. ## `maxDomains` (type: `integer`): Safety cap for how many unique domains to audit in one run. ## `requestTimeoutSecs` (type: `integer`): Timeout for each public HTTP request. ## `checkHomepage` (type: `boolean`): Fetch the homepage and look for llms.txt and sitemap references. ## Actor input object example ```json { "domains": [ "apify.com", "docs.apify.com", "example.com" ], "maxDomains": 25, "requestTimeoutSecs": 12, "checkHomepage": true } ``` # 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("nectared_screen/ai-crawler-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 = {} # Run the Actor and wait for it to finish run = client.actor("nectared_screen/ai-crawler-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 '{}' | apify call nectared_screen/ai-crawler-readiness-auditor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nectared_screen/ai-crawler-readiness-auditor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Crawler Readiness Auditor", "description": "Audit domains for llms.txt, robots.txt AI bot rules, sitemap hints, and public AI crawler readiness signals.", "version": "0.1", "x-build-id": "BYHcCzQufTmX6RUe0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nectared_screen~ai-crawler-readiness-auditor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nectared_screen-ai-crawler-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nectared_screen~ai-crawler-readiness-auditor/runs": { "post": { "operationId": "runs-sync-nectared_screen-ai-crawler-readiness-auditor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nectared_screen~ai-crawler-readiness-auditor/run-sync": { "post": { "operationId": "run-sync-nectared_screen-ai-crawler-readiness-auditor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "domains" ], "properties": { "domains": { "title": "Domains or URLs", "type": "array", "description": "Domains or website URLs to audit for AI crawler readiness.", "default": [ "apify.com", "docs.apify.com", "example.com" ], "items": { "type": "string" } }, "maxDomains": { "title": "Maximum domains", "minimum": 1, "maximum": 100, "type": "integer", "description": "Safety cap for how many unique domains to audit in one run.", "default": 25 }, "requestTimeoutSecs": { "title": "Request timeout seconds", "minimum": 3, "maximum": 30, "type": "integer", "description": "Timeout for each public HTTP request.", "default": 12 }, "checkHomepage": { "title": "Check homepage signals", "type": "boolean", "description": "Fetch the homepage and look for llms.txt and sitemap references.", "default": true } } }, "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 } } } } } } } } } } ```