log_interaction
Log and optionally auto-execute an interaction step. If the built-in Playwright browser is active (launched by start_ui_dive), the action is automatically executed in the browser — just provide a CSS selector in
This record as markdown: /tools/io-github-homenshum-nodebench/log-interaction.md
What log_interaction does on Nodebench
AI agents invoke log_interaction 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 log_interaction is rated High
This tool automatically executes browser actions via Playwright when a browser is active. Providing a CSS selector triggers actual browser interactions (clicks, form submissions, navigation), which are external operations with effects that depend on the provided selector argument. This qualifies as Execute rather than Write because it runs code/browser automation whose consequences are determined at runtime.
From the tool's definition 'Log and optionally auto-execute an interaction step. If the built-in Playwright browser is active... the action is automatically executed in the browser — just provide a CSS selector'
Attacks that exploit this kind of access
The rule that runs log_interaction 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_interaction, this is the rule to start with:
log_interaction 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 log_interaction call is checked against it from then on.
Questions about log_interaction
Log and optionally auto-execute an interaction step. If the built-in Playwright browser is active (launched by start_ui_dive), the action is automatically executed in the browser — just provide a CSS selector in. 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 log_interaction: 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.
log_interaction 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 log_interaction 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 log_interaction. 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.
log_interaction 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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