This record as markdown: /tools/hybridlabor-api-aos/select-objects.md
What select_objects does on Aos
AI agents invoke select_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 select_objects is rated High
Selecting objects in Rhino changes the application's selection state and can have downstream effects when combined with other tools (e.g., subsequent operations act on selected objects). This is not a pure read operation because it modifies the interactive state of the external Rhino environment, making it an Execute-level action.
From the tool's definition 'Select a list of objects in the Rhino viewport by GUID' — triggers a viewport interaction/state change in an external application (Rhino)
Attacks that exploit this kind of access
The rule that runs select_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 select_objects, this is the rule to start with:
select_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 select_objects call is checked against it from then on.
Questions about select_objects
Select a list of objects in the Rhino viewport by GUID. 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 select_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.
select_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 select_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 select_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.
select_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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