run_dogfood_batch_with_judge
Execute the priority 3 dogfood scenarios with automatic LLM judge validation.
This record as markdown: /tools/io-github-homenshum-nodebench/run-dogfood-batch-with-judge.md
What run_dogfood_batch_with_judge does on Nodebench
AI agents invoke run_dogfood_batch_with_judge to trigger actions in Nodebench. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why run_dogfood_batch_with_judge is rated High
This tool triggers execution of predefined dogfood test scenarios with LLM-based validation. While the scenarios themselves are pre-defined (limiting severity from critical), execution of batch operations with external LLM judge validation represents a process that triggers external operations with side effects.
From the tool's definition Tool name contains 'run' and description states 'Execute the priority 3 dogfood scenarios with automatic LLM judge validation.' The use of 'Execute' and 'run' clearly indicates code/operation execution.
Attacks that exploit this kind of access
The rule that runs run_dogfood_batch_with_judge 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 run_dogfood_batch_with_judge, this is the rule to start with:
run_dogfood_batch_with_judge stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Nodebench, apply this rule, and every run_dogfood_batch_with_judge call is checked against it from then on.
Questions about run_dogfood_batch_with_judge
Execute the priority 3 dogfood scenarios with automatic LLM judge validation. 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.
Register the Nodebench MCP server in PolicyLayer and add a rule for run_dogfood_batch_with_judge: 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.
run_dogfood_batch_with_judge is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_dogfood_batch_with_judge 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.
Set action: deny in the PolicyLayer policy for run_dogfood_batch_with_judge. 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.
run_dogfood_batch_with_judge 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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