Medium Risk

auto_apply

Automatically apply to a job using AI. Tailors your resume, generates a cover letter, and submits the application. Provide the job URL and optionally your resume text. Requires paid plan (Hired in 30+).

Part of the AI Applyd server.

auto_apply can modify AI Applyd 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 auto_apply to create or modify resources in AI Applyd. 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 auto_apply 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 AI Applyd.

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

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

See the full AI Applyd policy for all 10 tools.

Get this rule live on your own AI Applyd 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 auto_apply 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 auto_apply 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 auto_apply tool do? +

Automatically apply to a job using AI. Tailors your resume, generates a cover letter, and submits the application. Provide the job URL and optionally your resume text. Requires paid plan (Hired in 30+).. It is categorised as a Write tool in the AI Applyd MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on auto_apply? +

Register the AI Applyd MCP server in PolicyLayer and add a rule for auto_apply: 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 AI Applyd. Nothing to install.

What risk level is auto_apply? +

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

Can I rate-limit auto_apply? +

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

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

auto_apply is provided by the AI Applyd MCP server (https://mcp.aiapplyd.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AI Applyd tool call.

Deterministic rules across all 10 AI Applyd tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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