Agentic Arm APIs: Bounded Tools, Approvals, and Recovery
Give an agent useful skills without unrestricted actuator access. Design narrow tools, reviewable plans, and honest outcomes.
THE ARM LAB / TAG: AI AGENTS
Read about scene evidence, proposed plans, structured tools, approvals, and deliberate recovery.
An agent can choose what to propose next, but a surrounding application still needs to define what is permitted. This collection connects perception and scene context to the tool boundary where a proposed action becomes an authorized operation.
Start with the perception-to-motion guide for the distinction between an observation, an interpretation, and a target. Follow it with the bounded tools article to examine structured arguments, approval context, stale assumptions, and recovery. The two guides describe different layers of the same workflow rather than competing approaches.
As you read, look for the evidence each layer consumes and the claim its output makes. A confident explanation should not silently become proof of permission or completion. The Agentic Arm API overview provides an architectural starting point, and the AI robotic arm overview focuses on perception and planning. The browser playground has no AI model, autonomous agent, or connection to equipment; it is a separate local interface example.
Give an agent useful skills without unrestricted actuator access. Design narrow tools, reviewable plans, and honest outcomes.
Connect perception, scene state, planning, and execution without treating an AI prediction as permission to move.
A little code. A lot to explore.
Start in the browser. Understand the interface. Build with clearer boundaries.