This record as markdown: /tools/io-github-kivanccakmak-yaver/go-pprof-heap.md
What go_pprof_heap does on Yaver
AI agents invoke go_pprof_heap 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 |
|---|---|---|---|
url | string | — | Running service URL (e.g. http://localhost:6060) |
directory | string | — |
Parameters from the server's own tool schema.
Why go_pprof_heap is rated High
This tool executes a Go profiling command (pprof heap analysis) which is a runtime operation with side effects on the target application. While profiling itself is not destructive, it involves triggering external code execution and runtime inspection that could impact application behavior, memory access patterns, or expose sensitive data in heap contents.
From the tool's definition Tool name 'go_pprof_heap' and description 'Run Go heap profiling' indicate execution of a profiling operation that triggers external runtime analysis of a Go application.
Risk signalsAccepts file system path (directory) · Accepts URL/endpoint input (url)
Attacks that exploit this kind of access
The rule that runs go_pprof_heap 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_heap, this is the rule to start with:
go_pprof_heap 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_heap call is checked against it from then on.
Questions about go_pprof_heap
Run Go heap profiling. 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_heap accepts 2 parameters: url, 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_heap: 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_heap 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_heap 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_heap. 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_heap 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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