External services and backend capabilities for AbotClaw robots — vision APIs, VLM/LLM endpoints, planners, speech services, grasping backends, and client SDKs. Use when a robot skill needs an external service, when checking what backend tools already exist,…
Bundle an AbotClaw robot skill and its dependencies into a single executable Python file or portable submission artifact. Use when preparing robot code for execution environments that want one file, when flattening dependency chains, or when packaging a skill…
SpatialMemoryHub-based robot memory querying, writing, and retrieval for AbotClaw. Use when the agent needs to store or retrieve object memory, place memory, keyframe memory, or semantic frame memory; when checking whether a memory service is running; when…
Use a deployed VLAC-style vision-language-action critic service to evaluate task progress, compare current observations against a reference image, and judge task completion from robot camera frames. Use when the agent needs external progress supervision,…
Robot connection and reachability guidance for the AbotClaw fleet. Use when identifying the correct robot base URL, auth method, health check, safest first connectivity test, or when debugging why Piper, Unitree G1, or Unitree Go2 cannot be reached.
Hardware roles, embodiment boundaries, and task-fit guidance for Piper, Unitree G1, and Unitree Go2. Use when deciding which robot should handle a task, when reasoning about embodiment constraints, or when documenting robot-specific assumptions in a skill.
Execute or plan a real task on Piper, Unitree G1, or Unitree Go2. Use when the user asks the robot fleet to do something in the physical world, including observing, moving, manipulating, inspecting, or multi-robot task execution.
Discover how a robot is actually used by reading its deployed guide and SDK reference before writing code. Use when starting robot work, when the API is unclear, when a new robot is added, or when OpenClaw must determine the real robot usage pattern instead…