record_eval_result

Record the actual result for a specific eval case. Include what happened, the verdict (pass/fail/partial), and optionally telemetry data and judge notes.

SERVERNodebench SOURCEnodebench-mcp

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-homenshum-nodebench/record-eval-result.md

WHAT IT DOES

What record_eval_result does on Nodebench

AI agents use record_eval_result to create or update resources in Nodebench, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Nodebench environment.

RISK

Why record_eval_result is rated Medium

This tool writes evaluation results (verdict, telemetry, notes) to a data store. It creates/modifies records reversibly and does not execute code, delete data, or involve financial transactions. Misuse could corrupt quality-gate metrics or evaluation benchmarks, hence medium severity.

From the tool's definition 'Record the actual result for a specific eval case. Include what happened, the verdict (pass/fail/partial), and optionally telemetry data and judge notes.'

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs record_eval_result safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Nodebench, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For record_eval_result, this is the rule to start with:

record_eval_result Rate-limited

record_eval_result stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "record_eval_result": {
      "limits": [
        {
          "counter": "record_eval_result_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Nodebench, apply this rule, and every record_eval_result call is checked against it from then on.

FAQ

Questions about record_eval_result

What does the record_eval_result tool do? +

Record the actual result for a specific eval case. Include what happened, the verdict (pass/fail/partial), and optionally telemetry data and judge notes. It is categorised as a Write tool in the Nodebench MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on record_eval_result? +

Register the Nodebench MCP server in PolicyLayer and add a rule for record_eval_result: 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 record_eval_result? +

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

Can I rate-limit record_eval_result? +

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

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

record_eval_result 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.

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