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evaluate_batch

Evaluate multiple code files in a single call. Returns per-file verdicts with scores and findings, plus aggregate statistics.

Part of the Judges Panel server.

evaluate_batch can trigger actions in Judges Panel, 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 evaluate_batch to trigger processes or run actions in Judges Panel. 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.

evaluate_batch 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": {
    "evaluate_batch": {
      "limits": [
        {
          "counter": "evaluate_batch_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Judges Panel policy for all 78 tools.

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

Evaluate multiple code files in a single call. Returns per-file verdicts with scores and findings, plus aggregate statistics.. It is categorised as a Execute tool in the Judges Panel MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on evaluate_batch? +

Register the Judges Panel MCP server in PolicyLayer and add a rule for evaluate_batch: 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 Judges Panel. Nothing to install.

What risk level is evaluate_batch? +

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

Can I rate-limit evaluate_batch? +

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

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

evaluate_batch is provided by the Judges Panel MCP server (@kevinrabun/judges). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Judges Panel tool call.

Deterministic rules across all 78 Judges Panel tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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