log_test_result

Record a test result for Phase 4 (Testing & Validation). Tests are organized by layer: static, unit, integration, manual, live_e2e. All layers must pass before proceeding.

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/log-test-result.md

WHAT IT DOES

What log_test_result does on Nodebench

AI agents use log_test_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 log_test_result is rated Medium

This tool writes/records test result data into a tracking system. It creates or modifies test result records (reversible data entry), with no indication of code execution, deletion, or financial operations. Misuse could corrupt quality gate data, blocking or falsely passing validation phases, which warrants medium severity.

From the tool's definition Record a test result for Phase 4 (Testing & Validation). Tests are organized by layer: static, unit, integration, manual, live_e2e.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs log_test_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 log_test_result, this is the rule to start with:

log_test_result Rate-limited

log_test_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": {
    "log_test_result": {
      "limits": [
        {
          "counter": "log_test_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 log_test_result call is checked against it from then on.

FAQ

Questions about log_test_result

What does the log_test_result tool do? +

Record a test result for Phase 4 (Testing & Validation). Tests are organized by layer: static, unit, integration, manual, live_e2e. All layers must pass before proceeding. 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 log_test_result? +

Register the Nodebench MCP server in PolicyLayer and add a rule for log_test_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 log_test_result? +

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

Can I rate-limit log_test_result? +

Yes. Add a rate_limit block to the log_test_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 log_test_result completely? +

Set action: deny in the PolicyLayer policy for log_test_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 log_test_result? +

log_test_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.

KEEP EXPLORING

More on Nodebench, and thousands of servers like it.

This server

All 824 Nodebench tools →

Across the catalogue

team_manager_emit_result on Team Manager MCP → The MCP Attack Database →

Guides

Govern customer-ops agents →Argument validation →Scoped token →