# AI Search Readiness Audit (GEO/AEO) + llms.txt generator (`tanlabs/ai-search-readiness-audit`) Actor

Check whether ChatGPT, Claude, Perplexity, Gemini and other AI crawlers can access and understand a website: robots.txt rules for 14 AI bots, llms.txt, sitemap, Schema.org, meta tags, server-rendered text, speed. Returns a 0-100 score, prioritized fixes and a ready-to-publish llms.txt draft.

- **URL**: https://apify.com/tanlabs/ai-search-readiness-audit.md
- **Developed by:** [TanLabs](https://apify.com/tanlabs) (community)
- **Categories:** SEO tools, AI, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$8.00 / 1,000 page auditeds

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## AI Search Readiness Audit (GEO / AEO) + llms.txt generator

Will ChatGPT, Claude, Perplexity and Gemini **find, read and cite** your pages? This Actor checks the technical side of Generative Engine Optimization in seconds and tells you exactly what to fix.

### What it checks (per URL)

- **robots.txt vs 14 AI crawlers**: GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, Claude-SearchBot, Claude-User, PerplexityBot, Perplexity-User, Google-Extended, Applebot-Extended, CCBot, Bytespider, meta-externalagent, Amazonbot. Separates *training* bots (OK to block) from *search/answer* bots (blocking them means you won't be cited).
- **/llms.txt** present? If not, you get a **ready-to-publish llms.txt draft** built from your title, description and main internal links.
- **Sitemap** (robots.txt `Sitemap:` or `/sitemap.xml`).
- **Schema.org JSON-LD** types found (Organization, Product, Article, FAQPage…).
- Title, meta description, canonical, Open Graph, `lang`, H1/H2 structure.
- **Server-rendered text**: word count and text/HTML ratio. Content that only appears after JavaScript is invisible to most AI crawlers.
- `noindex` / `noai` meta, FAQ-style content, visible dates, response time.

### Output

`score` (0–100), `grade` (A–F), `fixes` sorted by priority (critical → info) with impact points, `topFixes` (3 lines for reports), all raw signals, and `llmsTxtDraft`.

### Input

```json
{ "urls": ["https://example.com/", "https://example.com/pricing"], "generateLlmsTxt": true }
```

### Who uses it

SEO/GEO agencies auditing client lists, SaaS and e-commerce teams, and AI agents through Apify's MCP server ("audit these 50 domains and list who blocks PerplexityBot").

### Pricing (pay per event)

**Page audited**: one event per URL. robots.txt / llms.txt / sitemap are fetched once per site and are free.

### Notes

Only the URLs you submit plus each site's robots.txt, llms.txt and sitemap.xml are requested, one request each. No login, no proxies. Built by TanLabs.

### More from TanLabs

- [App Store Review Insights](https://apify.com/tanlabs/app-store-review-insights)
- [App Store Top Charts & Rank Tracker](https://apify.com/tanlabs/app-store-top-charts)
- [Social Preview & Meta Tag Checker (Open Graph, X Card)](https://apify.com/tanlabs/social-preview-meta-checker)

# Actor input Schema

## `urls` (type: `array`):

Full URLs (home page, key product or blog pages). Each URL is one audited page.

## `generateLlmsTxt` (type: `boolean`):

Build a draft llms.txt for each site (from its title, description and main internal links) when the site has none.

## Actor input object example

```json
{
  "urls": [
    "https://www.apify.com/"
  ],
  "generateLlmsTxt": true
}
```

# Actor output Schema

## `overview` (type: `string`):

Score, grade and top fixes per page.

## `details` (type: `string`):

All checks, fixes and llms.txt drafts.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "urls": [
        "https://www.apify.com/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("tanlabs/ai-search-readiness-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "urls": ["https://www.apify.com/"] }

# Run the Actor and wait for it to finish
run = client.actor("tanlabs/ai-search-readiness-audit").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "urls": [
    "https://www.apify.com/"
  ]
}' |
apify call tanlabs/ai-search-readiness-audit --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,tanlabs/ai-search-readiness-audit"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/iWHI6SKfxjz7AwVmn/builds/pG0molnwpa5qVLFtG/openapi.json