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grade_agent_run

Grade a single agent run on both outcome quality (task success, regressions, time) and process quality (recon, risk, tests, gates, learnings). Combines deterministic grading from the task bank

Part of the Nodebench server.

grade_agent_run can trigger actions in Nodebench, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke grade_agent_run to trigger processes or run actions in Nodebench. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

grade_agent_run can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "grade_agent_run": {
      "limits": [
        {
          "counter": "grade_agent_run_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Nodebench policy for all 724 tools.

Get this rule live on your own Nodebench 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 grade_agent_run 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 grade_agent_run only ever does what you allow.

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

What does the grade_agent_run tool do? +

Grade a single agent run on both outcome quality (task success, regressions, time) and process quality (recon, risk, tests, gates, learnings). Combines deterministic grading from the task bank. It is categorised as a Execute tool in the Nodebench MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on grade_agent_run? +

Register the Nodebench MCP server in PolicyLayer and add a rule for grade_agent_run: 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 Nodebench. Nothing to install.

What risk level is grade_agent_run? +

grade_agent_run is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit grade_agent_run? +

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

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

grade_agent_run is provided by the Nodebench MCP server (nodebench-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Nodebench tool call.

Deterministic rules across all 724 Nodebench tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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