webgpu_frame_timing
Measure per-frame CPU and GPU cost over a rAF loop using GPU timestamp queries (device.limits.timestampPeriod conversion). Answers
This record as markdown: /tools/io-github-vmoranv-jshookmcp/webgpu-frame-timing.md
What webgpu_frame_timing does on Jshookmcp
AI agents invoke webgpu_frame_timing to trigger actions in Jshookmcp. 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 webgpu_frame_timing is rated High
Executes a requestAnimationFrame loop with GPU timestamp queries in the browser.
From the tool's definition Measure per-frame CPU and GPU cost over a rAF loop
Attacks that exploit this kind of access
The rule that runs webgpu_frame_timing safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Jshookmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For webgpu_frame_timing, this is the rule to start with:
webgpu_frame_timing 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 Jshookmcp, apply this rule, and every webgpu_frame_timing call is checked against it from then on.
Questions about webgpu_frame_timing
Measure per-frame CPU and GPU cost over a rAF loop using GPU timestamp queries (device.limits.timestampPeriod conversion). Answers. It is categorised as a Execute tool in the Jshookmcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Jshook MCP server in PolicyLayer and add a rule for webgpu_frame_timing: 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 Jshookmcp. Nothing to install.
webgpu_frame_timing 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 webgpu_frame_timing 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 webgpu_frame_timing. 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.
webgpu_frame_timing is provided by the Jshook MCP server (@jshookmcp/jshook). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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