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name: environment-usage description: "Run, inspect, wrap, record, and smoke-test ManiSkill environments from the public package with CPU/GPU, observation/control/render, and demo guidance." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Environment Usage

Use this sub-skill when the task is about existing ManiSkill environments only: quickstart creation, observation/control/render selection, CPU vs GPU backend choice, wrapper composition, demo modules, and safe smoke tests from the public package.

Start here:

• references/workflows.md for safe run flows, wrapper order, and smoke patterns.
• references/api-reference.md for gym.make, BaseEnv, backend, and wrapper contracts.
• references/cli-and-modules.md for runnable demo and visualization commands.
• references/troubleshooting.md when import, render, backend, asset, or wrapper issues appear.
• scripts/smoke_no_render_cpu.py for a bounded CPU smoke run that works from any cwd.

What this sub-skill covers:

• gym.make / mani_skill.envs usage for public tasks
• BaseEnv runtime options and backend selection
• CPUGymWrapper, ManiSkillVectorEnv, RecordEpisode
• FlattenObservationWrapper, FlattenRGBDObservationWrapper, FlattenActionSpaceWrapper
• demo_random_action, demo_robot, visual demo modules, demo_reset_distribution
• help-only guidance for benchmarking / GPU sim
• safe CPU smoke patterns and backend caveats

What it does not cover:

• custom task authoring internals
• trajectory conversion, replay, teleop, or dataset collection details
• learning baselines and training recipes
• asset download internals beyond user-facing caveats

Routing:

• Custom task building -> ../custom-environments/
• Replay, teleop, datasets -> ../trajectories-and-datasets/
• Training baselines -> ../learning-and-baselines/

Operating rules:

1. Prefer import mani_skill.envs followed by gym.make(...) for ordinary use. Reach for mani_skill.envs.sapien_env.BaseEnv only when you need constructor details, print_sim_details(), or low-level runtime inspection.
2. Treat obs_mode as the observation contract and control_mode as the action contract. If the user is unsure which mode to choose, inspect env.observation_space, env.action_space, and the bundled API notes before changing code.
3. Use num_envs=1 for CPU smoke and num_envs>1 for GPU parallelization. Default sim_backend="auto" selects PhysX CPU for one env and PhysX CUDA for multiple envs; use explicit physx_cpu, physx_cuda, or physx_cuda:n when you need to pin the backend.
4. Keep rendering explicit. Use render_backend="none" or None for headless smoke checks, and only ask for human, rgb_array, sensors, or all after display/Vulkan support is known.
5. Apply ManiSkill-native wrappers before outer API adapters. RecordEpisode should be last among ManiSkill wrappers, CPUGymWrapper is for single-env CPU runs only, and ManiSkillVectorEnv is the outer adapter for batched GPU envs that need Gymnasium vector semantics.
6. Use the demo modules for feature-specific inspection before custom code when possible. Prefer help output first for benchmark scripts and expensive visualizations.
7. When a task mentions replay, teleoperation, dataset collection, or training, route it to the dedicated sibling sub-skill instead of extending environment usage.