Medium Risk

score_resume

Score a resume against a job description for ATS compatibility. Returns keyword match score, missing keywords, section scores, and improvement recommendations. Deterministic keyword scoring — uses no AI credits, but requires a connected AI Applyd account.

Part of the AI Applyd server.

score_resume 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 score_resume 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 score_resume 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": {
    "score_resume": {
      "limits": [
        {
          "counter": "score_resume_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access score_resume 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 score_resume 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 score_resume tool do? +

Score a resume against a job description for ATS compatibility. Returns keyword match score, missing keywords, section scores, and improvement recommendations. Deterministic keyword scoring — uses no AI credits, but requires a connected AI Applyd account.. 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 score_resume? +

Register the AI Applyd MCP server in PolicyLayer and add a rule for score_resume: 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 score_resume? +

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

Can I rate-limit score_resume? +

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

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

score_resume 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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