DexForce
Official@dexforce
Offers standardized scaffolding and benchmarking interfaces for EmbodiChain environments, enabling systematic development of robotic task environments and atomic action definitions.
Agent Skills by DexForce
Showing 7 vetted skills indexed across 1 GitHub repositories.
DexForcebenchmark
Write EmbodiChain benchmark scripts measuring runtime, CPU/RAM, GPU/VRAM, and correctness.
DexForceadd-test
Create EmbodiChain test files with pytest or SimulationManager class-style structure.
DexForcepre-commit-check
Verify EmbodiChain Python code against pre-commit CI rules.
DexForceadd-functor
Add EmbodiChain functors for observations, rewards, events, actions, datasets, or randomizations.
DexForceadd-atomic-action
Add a custom atomic action to an EmbodiChain environment via ActionCfg and AtomicAction interfaces.
DexForcepr
Create template-compliant GitHub pull requests for EmbodiChain.
DexForceadd-task-env
Scaffold EmbodiChain task environments with Gym IDs and test stubs.
Frequently Asked Questions About DexForce
FAQPage SchemaWhat specific tasks does DexForce enable for developers?▼
DexForce enables the rapid creation of EmbodiChain task environments, the implementation of custom atomic actions, and the definition of observation or reward functors. It also provides standardized benchmarking for runtime and hardware resource utilization, alongside automated test file generation and pull request compliance.
Which engineering personas benefit from these capabilities?▼
These capabilities are designed for robotics engineers, simulation researchers, and reinforcement learning practitioners working within the EmbodiChain ecosystem. It is specifically targeted at developers who need to maintain consistent environment structures, verify code quality through CI rules, and perform rigorous performance profiling of simulation tasks.
What are the prerequisites for using these environment scaffolding skills?▼
Users must have an existing EmbodiChain environment setup. The skills rely on standard class-style structures, specifically the SimulationManager, ActionCfg, and AtomicAction interfaces. Additionally, developers should have a local environment configured to support pytest and pre-commit hooks to ensure compatibility with the provided verification rules.