# Agent Readiness Audit (`ondrejulehla/agent-readiness-audit`) Actor

Check how ready a website is for AI agents: robots.txt policy for AI crawlers, llms.txt, sitemap, structured data, MCP server card, and JavaScript dependence.

- **URL**: https://apify.com/ondrejulehla/agent-readiness-audit.md
- **Developed by:** [Ondřej Úlehla](https://apify.com/ondrejulehla) (community)
- **Categories:** AI, Agents, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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 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

## Agent Readiness Audit

AI agents are becoming a major consumer of the web. They fetch pages, read robots.txt, look for llms.txt, extract structured data, and increasingly connect through MCP servers. Most websites were never checked against any of that.

This Actor audits any website for **AI-agent readiness** and returns a scored report with concrete recommendations.

### What it checks

| Check | Why it matters for agents |
|---|---|
| robots.txt exists | The only standard place to express a crawler policy |
| AI crawler access | Whether GPTBot, ClaudeBot, PerplexityBot, CCBot and others are allowed, restricted, or blocked |
| llms.txt | A markdown site map made for language models (llmstxt.org), consumed directly by agents |
| XML sitemap | Lets agents enumerate content instead of crawling blind |
| MCP server card | `/.well-known/mcp/server-card.json`, the discovery point for a site's MCP server |
| Structured data | JSON-LD (schema.org) lets agents extract facts without guessing from layout |
| Meta basics | Title, meta description, canonical: the first thing any agent reads |
| Works without JavaScript | Most agents fetch, they do not render; content that only exists after JS is invisible to them |
| Indexing signals | noindex / noai directives in meta tags or X-Robots-Tag headers |

Each check has a weight. The report gives a 0–100 score, a grade (A–F), per-check details, and a recommendation for every failed check.

### Input

```json
{
    "urls": ["https://example.com"],
    "aiCrawlers": ["GPTBot", "ClaudeBot", "PerplexityBot", "CCBot"]
}
```

`urls` is required. `aiCrawlers` is optional and defaults to the major AI agents and training crawlers.

### Output

One dataset item per audited site:

```json
{
    "url": "https://example.com",
    "score": 62,
    "grade": "C",
    "checks": {
        "robotsTxt": { "passed": true, "weight": 10, "status": 200 },
        "aiCrawlerAccess": { "passed": true, "weight": 15, "policies": { "GPTBot": "allowed", "ClaudeBot": "blocked" } },
        "llmsTxt": { "passed": false, "weight": 15, "status": 404 },
        "worksWithoutJs": { "passed": true, "weight": 15, "visibleTextChars": 18240 }
    },
    "recommendations": [
        "Add /llms.txt: a short markdown map of the site for language models (llmstxt.org). Cheap to add, directly consumed by agents."
    ]
}
```

A run summary is stored in the `OUTPUT` record of the key-value store.

### Use cases

- **Site owners**: find out what an AI agent actually sees before deciding on an AI traffic policy.
- **Agencies**: audit client portfolios for the answer-engine era, the same way you audit SEO today.
- **Agent builders**: check whether a target site is agent-friendly before building on top of it.

### Notes

- The audit reads a handful of public URLs per site (homepage, robots.txt, llms.txt, sitemap, well-known paths). It does not crawl the whole site and does not execute JavaScript.
- "Blocked" verdicts describe what robots.txt requests; they are not a legal statement about what any crawler does.

# Actor input Schema

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

One or more website URLs. The audit runs on the site root of each URL.

## `aiCrawlers` (type: `array`):

User-agent names of AI crawlers whose robots.txt policy the audit reports. The default list covers the major AI agents and training crawlers.

## Actor input object example

```json
{
  "urls": [
    "https://apify.com"
  ],
  "aiCrawlers": [
    "GPTBot",
    "ClaudeBot",
    "Claude-User",
    "PerplexityBot",
    "CCBot",
    "Google-Extended",
    "Bytespider",
    "meta-externalagent"
  ]
}
```

# Actor output Schema

## `report` (type: `string`):

One item per audited website with score, grade, per-check details, and recommendations.

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

Compact summary of the run: audited count, failures, and per-site scores.

# 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://apify.com"
    ],
    "aiCrawlers": [
        "GPTBot",
        "ClaudeBot",
        "Claude-User",
        "PerplexityBot",
        "CCBot",
        "Google-Extended",
        "Bytespider",
        "meta-externalagent"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("ondrejulehla/agent-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://apify.com"],
    "aiCrawlers": [
        "GPTBot",
        "ClaudeBot",
        "Claude-User",
        "PerplexityBot",
        "CCBot",
        "Google-Extended",
        "Bytespider",
        "meta-externalagent",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("ondrejulehla/agent-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://apify.com"
  ],
  "aiCrawlers": [
    "GPTBot",
    "ClaudeBot",
    "Claude-User",
    "PerplexityBot",
    "CCBot",
    "Google-Extended",
    "Bytespider",
    "meta-externalagent"
  ]
}' |
apify call ondrejulehla/agent-readiness-audit --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,ondrejulehla/agent-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/7nQebWpKGrwTMvs4j/builds/4XOyRjSn2Ke2LJudx/openapi.json