Create EmbodiChain test files with pytest or SimulationManager class-style structure.
npx skills add https://github.com/DexForce/EmbodiChain --skill add-test-dexforce
Please help me install this Agent Skill. Skill: add-test Source: https://github.com/DexForce/EmbodiChain/tree/main/skills/add-test Command: npx skills add https://github.com/DexForce/EmbodiChain --skill add-test-dexforce
It helps you add reliable test coverage to EmbodiChain modules so changes don’t break observation functors, reward functors, solvers, sensors, or environments.
embodichain/ source tree under tests/ and uses the test_<module>.py convention.SimulationManager, GPU setup, or ordered/shared state.MockSim/MockEnv guidance for fast functor tests without running a real simulation.from __future__ import annotations, descriptive test_<scenario> naming, and black formatting.Tell the AI which EmbodiChain module or function you want to test, whether it needs a live SimulationManager, and the behaviors you must verify.
High-intent search queries and answers about installing and using this skill.
For fast unit tests without running a real GPU simulation, use mocking patterns like MockSim and MockEnv to isolate and test observation functors, reward functors, and sensors quickly.
The correct file placement convention for testing observation functors and sensors is to mirror the embodichain source tree under the tests directory using the test_<module>.py naming format.
Use pytest functions for pure-Python logic components, and switch to class-style tests when your modules require SimulationManager, GPU setup, ordered execution, or shared state across test methods.
Test files must include the Apache 2.0 license header and the required from __future__ import annotations statement, use descriptive test_<scenario> naming, and be formatted with black to pass repository checks.
Yes, you can use MockSim and MockEnv mocking patterns to create fast functor tests without running a live SimulationManager, allowing you to verify observation and reward logic efficiently.
Choose pytest style for pure-logic Python components and class-style tests for simulation-dependent behavior, ensuring tests align with repository conventions for either approach.
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