Medium Risk

generate_llms_txt

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt....

Risk signalsAccepts URL/endpoint input (url) · Admin/system-level operation

Part of the Datos Gob Es server.

generate_llms_txt can modify Datos Gob Es data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use generate_llms_txt to create or modify resources in Datos Gob Es. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call generate_llms_txt repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Datos Gob Es.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "generate_llms_txt": {
      "limits": [
        {
          "counter": "generate_llms_txt_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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

Browse the full MCP Attack Database →

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

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the generate_llms_txt tool do? +

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.. It is categorised as a Write tool in the Datos Gob Es MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on generate_llms_txt? +

Register the Datos Gob Es MCP server in PolicyLayer and add a rule for generate_llms_txt: 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 Datos Gob Es. Nothing to install.

What risk level is generate_llms_txt? +

generate_llms_txt is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit generate_llms_txt? +

Yes. Add a rate_limit block to the generate_llms_txt 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 generate_llms_txt completely? +

Set action: deny in the PolicyLayer policy for generate_llms_txt. 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 generate_llms_txt? +

generate_llms_txt is provided by the Datos Gob Es MCP server (https://gateway.pipeworx.io/datos-gob-es/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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