# LLMs.txt AI Discovery Auditor (`glowing_glove/llms-txt-ai-discovery-auditor`) Actor

Check websites for llms.txt, llms-full.txt, robots AI crawler rules, sitemap hints, and AI search readiness gaps.

- **URL**: https://apify.com/glowing\_glove/llms-txt-ai-discovery-auditor.md
- **Developed by:** [Ushba Khan](https://apify.com/glowing_glove) (community)
- **Categories:** AI, SEO tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $24.00 / 1,000 audited ai discovery sites

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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

## LLMs.txt AI Discovery Auditor

LLMs.txt AI Discovery Auditor helps SEO teams, AI search consultants, content teams, and SaaS marketers understand whether a website is prepared for AI crawlers and LLM-oriented discovery.

The actor checks for `/llms.txt`, `/llms-full.txt`, robots rules, sitemap hints, and simple content signals that influence whether AI systems can understand key pages.

### Business Use Cases

- Audit websites for AI search readiness.
- Find clients missing `llms.txt` or AI crawler guidance.
- Monitor owned sites for robots changes that affect AI visibility.
- Build AI SEO reports for agencies.
- Compare competitor AI discovery setup.

### Input

```json
{
  "websites": ["https://apify.com", "https://example.com"]
}
```

### Output You Get

- `website`
- `llmsTxtFound`
- `llmsFullTxtFound`
- `robotsFound`
- `aiCrawlerPolicy`
- `sitemapHints`
- `aiDiscoveryScore`
- `contentSignals`
- `recommendedFixes`

### How It Works

The actor fetches public AI discovery files and robots.txt, checks common AI crawler directives, extracts sitemap references, and summarizes the site’s readiness in a compact score.

### Practical Workflow

Run the actor across client or competitor domains. Prioritize sites with no `llms.txt`, blocked AI crawlers, missing sitemap hints, or weak homepage content signals.

### Notes

AI discovery practices are still evolving. This actor reports public technical signals and practical recommendations, not guaranteed ranking outcomes in any specific AI product.

# Actor input Schema

## `websites` (type: `array`):

Websites

## `requestTimeoutSecs` (type: `integer`):

Request timeout

## Actor input object example

```json
{
  "websites": [
    "https://apify.com",
    "https://example.com"
  ],
  "requestTimeoutSecs": 25
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `summary` (type: `string`):

No description

# 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 = {
    "websites": [
        "https://apify.com",
        "https://example.com"
    ]
};

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

# Prepare the Actor input
run_input = { "websites": [
        "https://apify.com",
        "https://example.com",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("glowing_glove/llms-txt-ai-discovery-auditor").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 '{
  "websites": [
    "https://apify.com",
    "https://example.com"
  ]
}' |
apify call glowing_glove/llms-txt-ai-discovery-auditor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,glowing_glove/llms-txt-ai-discovery-auditor"
        }
    }
}

```

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/VTIt7taPn5umzDIw4/builds/sWMRbYcfrKlvti2WL/openapi.json