Low Risk

check_ai_readiness

Check whether a website is properly configured for AI crawler access. Checks robots.txt for AI bot blocks, presence of llms.txt, schema markup, and other signals that affect whether ChatGPT, Claude, Perplexity and other AI assistants can read and cite the site. Returns a readiness summary with sp...

Risk signalsAccepts URL/endpoint input (url)

Part of the AEO Audit server.

check_ai_readiness is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call check_ai_readiness to retrieve information from AEO Audit without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though check_ai_readiness only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "check_ai_readiness": {}
  }
}

See the full AEO Audit policy for all 3 tools.

Get this rule live on your own AEO Audit server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access check_ai_readiness gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so check_ai_readiness only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the check_ai_readiness tool do? +

Check whether a website is properly configured for AI crawler access. Checks robots.txt for AI bot blocks, presence of llms.txt, schema markup, and other signals that affect whether ChatGPT, Claude, Perplexity and other AI assistants can read and cite the site. Returns a readiness summary with specific blockers.. It is categorised as a Read tool in the AEO Audit MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on check_ai_readiness? +

Register the AEO Audit MCP server in PolicyLayer and add a rule for check_ai_readiness: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches AEO Audit. Nothing to install.

What risk level is check_ai_readiness? +

check_ai_readiness is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit check_ai_readiness? +

Yes. Add a rate_limit block to the check_ai_readiness rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block check_ai_readiness completely? +

Set action: deny in the PolicyLayer policy for check_ai_readiness. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides check_ai_readiness? +

check_ai_readiness is provided by the AEO Audit MCP server (https://aeo-mcp-server.amdal-dev.workers.dev/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AEO Audit tool call.

Deterministic rules across all 3 AEO Audit tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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