performance_optimize
Apply performance optimizations Use when native shell timing (
This record as markdown: /tools/ruflo/performance-optimize.md
What performance_optimize does on Ruflo
AI agents invoke performance_optimize to trigger actions in Ruflo. 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 performance_optimize is rated High
Classified as Execute rather than Write because performance optimization typically involves running code or commands whose effects depend on runtime arguments and system state. While reversible in some cases, the tool's capability to modify system behavior through active optimization operations places it in the Execute category.
From the tool's definition Tool name 'performance_optimize' combined with context of 'Apply performance optimizations' and reference to 'native shell timing' suggests execution of optimization routines that may trigger system-level operations.
Attacks that exploit this kind of access
The rule that runs performance_optimize safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ruflo, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For performance_optimize, this is the rule to start with:
performance_optimize 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 Ruflo, apply this rule, and every performance_optimize call is checked against it from then on.
Questions about performance_optimize
Apply performance optimizations Use when native shell timing (. It is categorised as a Execute tool in the Ruflo MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ruflo MCP server in PolicyLayer and add a rule for performance_optimize: 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 Ruflo. Nothing to install.
performance_optimize 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 performance_optimize 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 performance_optimize. 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.
performance_optimize is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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