This record as markdown: /tools/io-github-kivanccakmak-yaver/go-pprof-cpu.md
What go_pprof_cpu does on Yaver
AI agents invoke go_pprof_cpu to trigger actions in Yaver. 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.
| Parameter | Type | Required | Description |
|---|---|---|---|
binary | string | — | URL or binary to profile (e.g. http://localhost:6060) |
duration | integer | — | Profiling duration in seconds (default: 30) |
directory | string | — |
Parameters from the server's own tool schema.
Why go_pprof_cpu is rated High
The tool executes Go profiling operations—either triggering test benchmarks or making pprof requests—which are external code-execution activities whose effects depend on runtime arguments (which benchmarks to run, which pprof endpoints to probe). This is Execute rather than Read because profiling involves triggering code execution and benchmarking, not merely querying static data.
From the tool's definition Tool name contains 'run' semantic (via 'pprof'); description explicitly states 'Run Go CPU profiling via test benchmarks or pprof URL', indicating execution of profiling operations and external testing/profiling tools.
Risk signalsAccepts file system path (directory)
Attacks that exploit this kind of access
The rule that runs go_pprof_cpu safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Yaver, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For go_pprof_cpu, this is the rule to start with:
go_pprof_cpu 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 Yaver, apply this rule, and every go_pprof_cpu call is checked against it from then on.
Questions about go_pprof_cpu
Run Go CPU profiling via test benchmarks or pprof URL. It is categorised as a Execute tool in the Yaver MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
go_pprof_cpu accepts 3 parameters: binary, duration, directory. The full parameter table on this page comes from the server's own tool schema.
Register the Yaver MCP server in PolicyLayer and add a rule for go_pprof_cpu: 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 Yaver. Nothing to install.
go_pprof_cpu 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 go_pprof_cpu 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 go_pprof_cpu. 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.
go_pprof_cpu is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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