record_execution_decision

Record a structured decision on a live execution trace without storing raw hidden reasoning. Use for rankings, selections, rejections, or escalation logic grounded in evidence.

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-execution-decision.md

WHAT IT DOES

What record_execution_decision does on Nodebench

AI agents use record_execution_decision 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_execution_decision is rated Medium

The tool writes/records a structured decision object to an execution trace. It creates or modifies data (the decision record) in a reversible, auditable way. It does not execute code, delete data, or involve financial transactions. Severity is medium because misuse could corrupt or falsify audit trails and decision records that downstream processes depend on.

From the tool's definition Record a structured decision on a live execution trace without storing raw hidden reasoning

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs record_execution_decision 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_execution_decision, this is the rule to start with:

record_execution_decision Rate-limited

record_execution_decision 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_execution_decision": {
      "limits": [
        {
          "counter": "record_execution_decision_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_execution_decision call is checked against it from then on.

FAQ

Questions about record_execution_decision

What does the record_execution_decision tool do? +

Record a structured decision on a live execution trace without storing raw hidden reasoning. Use for rankings, selections, rejections, or escalation logic grounded in evidence. 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_execution_decision? +

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

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

Can I rate-limit record_execution_decision? +

Yes. Add a rate_limit block to the record_execution_decision 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_execution_decision completely? +

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

record_execution_decision 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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