This record as markdown: /tools/hybridlabor-api-aos/scale-objects.md
What scale_objects does on Aos
AI agents invoke scale_objects to trigger actions in Aos. 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 scale_objects is rated High
The tool operates within Rhino 8 CAD environment where scale_objects modifies geometry dimensions. Without a description, confidence is reduced. However, given the server's explicit capability to 'execute arbitrary Python scripts' and the presence of sibling tools performing irreversible geometry operations (booleans, baking), this tool likely triggers computational changes to model state.
From the tool's definition Tool name 'scale_objects' with empty description; sibling tools include geometry creation, boolean operations, and 'execute arbitrary Python scripts' per server description. Scaling objects in CAD is a geometric transformation operation.
Attacks that exploit this kind of access
The rule that runs scale_objects safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Aos, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For scale_objects, this is the rule to start with:
scale_objects 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 Aos, apply this rule, and every scale_objects call is checked against it from then on.
Questions about scale_objects
scale_objects is a execute tool on the Aos MCP server. It is categorised as a Execute tool in the Aos MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Aos MCP server in PolicyLayer and add a rule for scale_objects: 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 Aos. Nothing to install.
scale_objects 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 scale_objects 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 scale_objects. 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.
scale_objects is provided by the Aos MCP server (@hybridlabor-api/aos). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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