{ "schema_version": "1", "hub_commit": "01b4b20f7ea55d9e9395915aed4e82c890c4c1c4", "catalog_url": "https://hub.superfastrobotics.com/catalog/v1/index.json", "records": [ { "schema_version": "1", "id": "maniskill-panda-lift-peg-upright", "name": "ManiSkill panda LiftPegUpright-v1 motion planner", "summary": "Grasp a peg and lift it upright with the official Panda planner.", "capabilities": [ "grasping", "lifting", "reorientation", "motion-planning" ], "aliases": [ "LiftPegUpright-v1", "panda", "panda_lift_peg_upright", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/lift_peg_upright.py", "mani_skill/envs/tasks/tabletop/lift_peg_upright.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.lift_peg_upright:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "LiftPegUpright-v1", "seed": 0, "robot": "panda", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-lift-peg-upright --project ./experiment --json" }, "completion": { "success_condition": "LiftPegUpright-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-lift-peg-upright", "requirements_file": "recipes/maniskill-panda-lift-peg-upright/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official LiftPegUpright-v1 / panda motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.lift_peg_upright import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"LiftPegUpright-v1\", robot_uids=\"panda\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"LiftPegUpright-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-lift-peg-upright.json", "docs/recipes/maniskill-panda-lift-peg-upright.md", "recipes/maniskill-panda-lift-peg-upright/requirements.txt", "recipes/maniskill-panda-lift-peg-upright/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-peg-insertion-side", "name": "ManiSkill panda_wristcam PegInsertionSide-v1 motion planner", "summary": "Align a peg with a side-facing hole and insert it using Panda WristCam.", "capabilities": [ "peg-in-hole", "insertion", "assembly", "motion-planning" ], "aliases": [ "PegInsertionSide-v1", "panda_wristcam", "panda", "panda_peg_insertion_side", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/peg_insertion_side.py", "mani_skill/envs/tasks/tabletop/peg_insertion_side.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda_wristcam", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.peg_insertion_side:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PegInsertionSide-v1", "seed": 0, "robot": "panda_wristcam", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-peg-insertion-side --project ./experiment --json" }, "completion": { "success_condition": "PegInsertionSide-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-peg-insertion-side", "requirements_file": "recipes/maniskill-panda-peg-insertion-side/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PegInsertionSide-v1 / panda_wristcam motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.peg_insertion_side import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PegInsertionSide-v1\", robot_uids=\"panda_wristcam\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PegInsertionSide-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda_wristcam\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-peg-insertion-side.json", "docs/recipes/maniskill-panda-peg-insertion-side.md", "recipes/maniskill-panda-peg-insertion-side/requirements.txt", "recipes/maniskill-panda-peg-insertion-side/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-pick-cube", "name": "ManiSkill Panda PickCube Python recipe", "summary": "Grasp a cube and move it to a target with the official Panda motion planner.", "capabilities": [ "grasping", "pick", "pick-and-place", "motion-planning" ], "aliases": [ "PickCube-v1", "Panda", "Franka", "robot manipulation", "reusable Python code", "pick_cube", "object manipulation" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/pick_cube.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "contributor_reported" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.pick_cube:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PickCube-v1", "seed": 0, "robot": "panda", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-pick-cube --project ./experiment --json" }, "completion": { "success_condition": "PickCube-v1 env info.success is true after upstream solver finishes; adapter exit 0 only when success is true.", "timeout_seconds": 180, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no retries to conceal failures. Use an external 180-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-pick-cube", "requirements_file": "recipes/maniskill-panda-pick-cube/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"CPU/state adapter around the pinned upstream ManiSkill PickCube solver.\n\nThe solver is authored by ManiSkill contributors (Apache-2.0); this hub wrapper\ndoes not contain upstream solver code. It never renders or controls hardware.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs # registers simulation tasks\n from mani_skill.examples.motionplanning.panda.solutions.pick_cube import solve\n\n env = gym.make(\"PickCube-v1\", robot_uids=\"panda\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None)\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PickCube-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n # Keep the invocation contract even if an optional dependency is absent\n # or the simulator cannot initialize. Do not report this as task success.\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "not_run", "verified_by": "Robot Skill Hub API structural intake", "date": "2026-10-17", "environment": { "runtime": "not_run" }, "commands": [ "API schema, exact base/source pin, allowlist and strict unified diff checks" ], "result": "Intake structure checks only. Changed recipe runtime, dependency installation, imports and robot tasks were not run by the hub.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": { "command": "rsh.py prepare maniskill-panda-pick-cube --project CLEAN_PROJECT --download-only --json", "level": "contributor_reported", "reported_by": "submitter", "result": "Pinned 243636110-byte upstream archive SHA-256 and extracted paths verified in two clean Windows projects; corrected render_backend=none adapter preserved. Source-only preparation reports needs_configuration with no venv or dependency install. ManiSkill imports and robot task execution: not_run." }, "hub_verification": { "level": "structure_checked", "runtime": "not_run" } }, "maintenance": { "record_version": "contrib-a5dd78ad4e1d4e3d", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-pick-cube.json", "docs/recipes/maniskill-panda-pick-cube.md", "recipes/maniskill-panda-pick-cube/requirements.txt", "recipes/maniskill-panda-pick-cube/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-place-sphere", "name": "ManiSkill panda PlaceSphere-v1 motion planner", "summary": "Pick up a sphere and place it into a bin with the official Panda planner.", "capabilities": [ "pick-and-place", "grasping", "placing", "motion-planning" ], "aliases": [ "PlaceSphere-v1", "panda", "panda_place_sphere", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/place_sphere.py", "mani_skill/envs/tasks/tabletop/place_sphere.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.place_sphere:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PlaceSphere-v1", "seed": 0, "robot": "panda", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-place-sphere --project ./experiment --json" }, "completion": { "success_condition": "PlaceSphere-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-place-sphere", "requirements_file": "recipes/maniskill-panda-place-sphere/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PlaceSphere-v1 / panda motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.place_sphere import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PlaceSphere-v1\", robot_uids=\"panda\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PlaceSphere-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-place-sphere.json", "docs/recipes/maniskill-panda-place-sphere.md", "recipes/maniskill-panda-place-sphere/requirements.txt", "recipes/maniskill-panda-place-sphere/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-plug-charger", "name": "ManiSkill panda_wristcam PlugCharger-v1 motion planner", "summary": "Grasp a charger, align its pins, and plug it into a receptacle.", "capabilities": [ "insertion", "assembly", "grasping", "motion-planning" ], "aliases": [ "PlugCharger-v1", "panda_wristcam", "panda", "panda_plug_charger", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/plug_charger.py", "mani_skill/envs/tasks/tabletop/plug_charger.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda_wristcam", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.plug_charger:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PlugCharger-v1", "seed": 0, "robot": "panda_wristcam", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-plug-charger --project ./experiment --json" }, "completion": { "success_condition": "PlugCharger-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-plug-charger", "requirements_file": "recipes/maniskill-panda-plug-charger/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PlugCharger-v1 / panda_wristcam motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.plug_charger import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PlugCharger-v1\", robot_uids=\"panda_wristcam\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PlugCharger-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda_wristcam\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-plug-charger.json", "docs/recipes/maniskill-panda-plug-charger.md", "recipes/maniskill-panda-plug-charger/requirements.txt", "recipes/maniskill-panda-plug-charger/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-pull-cube-tool", "name": "ManiSkill panda PullCubeTool-v1 motion planner", "summary": "Use an L-shaped tool to pull a cube toward a goal.", "capabilities": [ "tool-use", "pulling", "grasping", "motion-planning" ], "aliases": [ "PullCubeTool-v1", "panda", "panda_pull_cube_tool", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/pull_cube_tool.py", "mani_skill/envs/tasks/tabletop/pull_cube_tool.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.pull_cube_tool:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PullCubeTool-v1", "seed": 0, "robot": "panda", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-pull-cube-tool --project ./experiment --json" }, "completion": { "success_condition": "PullCubeTool-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-pull-cube-tool", "requirements_file": "recipes/maniskill-panda-pull-cube-tool/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PullCubeTool-v1 / panda motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.pull_cube_tool import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PullCubeTool-v1\", robot_uids=\"panda\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PullCubeTool-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-pull-cube-tool.json", "docs/recipes/maniskill-panda-pull-cube-tool.md", "recipes/maniskill-panda-pull-cube-tool/requirements.txt", "recipes/maniskill-panda-pull-cube-tool/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-pull-cube", "name": "ManiSkill panda PullCube-v1 motion planner", "summary": "Pull a cube to its goal with the official Panda motion planner.", "capabilities": [ "pulling", "object-manipulation", "motion-planning" ], "aliases": [ "PullCube-v1", "panda", "panda_pull_cube", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/pull_cube.py", "mani_skill/envs/tasks/tabletop/pull_cube.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.pull_cube:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PullCube-v1", "seed": 0, "robot": "panda", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-pull-cube --project ./experiment --json" }, "completion": { "success_condition": "PullCube-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-pull-cube", "requirements_file": "recipes/maniskill-panda-pull-cube/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PullCube-v1 / panda motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.pull_cube import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PullCube-v1\", robot_uids=\"panda\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PullCube-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-pull-cube.json", "docs/recipes/maniskill-panda-pull-cube.md", "recipes/maniskill-panda-pull-cube/requirements.txt", "recipes/maniskill-panda-pull-cube/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-push-cube", "name": "ManiSkill panda PushCube-v1 motion planner", "summary": "Push a cube to a goal region with the official Panda motion planner.", "capabilities": [ "pushing", "object-manipulation", "motion-planning" ], "aliases": [ "PushCube-v1", "panda", "panda_push_cube", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/push_cube.py", "mani_skill/envs/tasks/tabletop/push_cube.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.push_cube:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PushCube-v1", "seed": 0, "robot": "panda", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-push-cube --project ./experiment --json" }, "completion": { "success_condition": "PushCube-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-push-cube", "requirements_file": "recipes/maniskill-panda-push-cube/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PushCube-v1 / panda motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.push_cube import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PushCube-v1\", robot_uids=\"panda\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PushCube-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-push-cube.json", "docs/recipes/maniskill-panda-push-cube.md", "recipes/maniskill-panda-push-cube/requirements.txt", "recipes/maniskill-panda-push-cube/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-stack-cube", "name": "ManiSkill Panda StackCube Python recipe", "summary": "Grasp one cube and stack it on another with the official Panda motion planner.", "capabilities": [ "grasping", "stacking", "pick-and-place", "motion-planning" ], "aliases": [ "StackCube-v1", "Panda", "Franka", "robot manipulation", "reusable Python code", "stack_cube", "object manipulation" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/stack_cube.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.stack_cube:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "StackCube-v1", "seed": 0, "robot": "panda", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-stack-cube --project ./experiment --json" }, "completion": { "success_condition": "StackCube-v1 env info.success is true after upstream solver finishes; adapter exit 0 only when success is true.", "timeout_seconds": 180, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no retries to conceal failures. Use an external 180-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-stack-cube", "requirements_file": "recipes/maniskill-panda-stack-cube/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"CPU/state adapter around the pinned upstream ManiSkill StackCube solver.\n\nThe solver is authored by ManiSkill contributors (Apache-2.0); this hub wrapper\ndoes not contain upstream solver code. It never renders or controls hardware.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs # registers simulation tasks\n from mani_skill.examples.motionplanning.panda.solutions.stack_cube import solve\n\n env = gym.make(\"StackCube-v1\", robot_uids=\"panda\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None)\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"StackCube-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n # Keep the invocation contract even if an optional dependency is absent\n # or the simulator cannot initialize. Do not report this as task success.\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "host_os": "windows", "python": "3.10.11", "runtime": "not_installed" }, "commands": [ "git ls-remote https://github.com/haosulab/ManiSkill.git refs/tags/v3.0.0b22", "Download exact commit archive; SHA256 checked", "Review pinned setup.py, LICENSE, upstream run.py and task solver" ], "result": "Source and license verified. Linux execution, dependency installation, imports and task completion have NOT been run by the hub (not_run).", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-stack-cube.json", "docs/recipes/maniskill-panda-stack-cube.md", "recipes/maniskill-panda-stack-cube/requirements.txt", "recipes/maniskill-panda-stack-cube/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-stack-pyramid", "name": "ManiSkill panda StackPyramid-v1 motion planner", "summary": "Arrange three cubes into a pyramid using the official Panda planner.", "capabilities": [ "stacking", "pick-and-place", "multi-object", "motion-planning" ], "aliases": [ "StackPyramid-v1", "panda", "panda_stack_pyramid", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/stack_pyramid.py", "mani_skill/envs/tasks/tabletop/stack_pyramid.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.stack_pyramid:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "StackPyramid-v1", "seed": 0, "robot": "panda", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-stack-pyramid --project ./experiment --json" }, "completion": { "success_condition": "StackPyramid-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-stack-pyramid", "requirements_file": "recipes/maniskill-panda-stack-pyramid/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official StackPyramid-v1 / panda motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.stack_pyramid import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"StackPyramid-v1\", robot_uids=\"panda\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"StackPyramid-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-stack-pyramid.json", "docs/recipes/maniskill-panda-stack-pyramid.md", "recipes/maniskill-panda-stack-pyramid/requirements.txt", "recipes/maniskill-panda-stack-pyramid/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-stick-draw-svg", "name": "ManiSkill panda_stick DrawSVG-v1 motion planner", "summary": "Trace the environment's default SVG outline with the Panda Stick planner.", "capabilities": [ "drawing", "trajectory-following", "svg", "motion-planning" ], "aliases": [ "DrawSVG-v1", "panda_stick", "panda", "panda_stick_draw_svg", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/draw_svg.py", "mani_skill/envs/tasks/drawing/draw_svg.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda_stick", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2", "svgpathtools==1.6.1" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.draw_svg:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "DrawSVG-v1", "seed": 0, "robot": "panda_stick", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-stick-draw-svg --project ./experiment --json" }, "completion": { "success_condition": "DrawSVG-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-stick-draw-svg", "requirements_file": "recipes/maniskill-panda-stick-draw-svg/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official DrawSVG-v1 / panda_stick motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.draw_svg import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"DrawSVG-v1\", robot_uids=\"panda_stick\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"DrawSVG-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda_stick\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n# Optional drawing task parser required by DrawSVGEnv.\nsvgpathtools==1.6.1\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-stick-draw-svg.json", "docs/recipes/maniskill-panda-stick-draw-svg.md", "recipes/maniskill-panda-stick-draw-svg/requirements.txt", "recipes/maniskill-panda-stick-draw-svg/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-panda-stick-draw-triangle", "name": "ManiSkill panda_stick DrawTriangle-v1 motion planner", "summary": "Trace a triangle with the Panda Stick motion planner.", "capabilities": [ "drawing", "trajectory-following", "motion-planning" ], "aliases": [ "DrawTriangle-v1", "panda_stick", "panda", "panda_stick_draw_triangle", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/panda/run.py", "mani_skill/examples/motionplanning/panda/solutions/draw_triangle.py", "mani_skill/envs/tasks/drawing/draw_triangle.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "panda_stick", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.panda.solutions.draw_triangle:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "DrawTriangle-v1", "seed": 0, "robot": "panda_stick", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-panda-stick-draw-triangle --project ./experiment --json" }, "completion": { "success_condition": "DrawTriangle-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-panda-stick-draw-triangle", "requirements_file": "recipes/maniskill-panda-stick-draw-triangle/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official DrawTriangle-v1 / panda_stick motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.panda.solutions.draw_triangle import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"DrawTriangle-v1\", robot_uids=\"panda_stick\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"DrawTriangle-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"panda_stick\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-panda-stick-draw-triangle.json", "docs/recipes/maniskill-panda-stick-draw-triangle.md", "recipes/maniskill-panda-stick-draw-triangle/requirements.txt", "recipes/maniskill-panda-stick-draw-triangle/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-so100-pick-cube", "name": "ManiSkill so100 PickCubeSO100-v1 motion planner", "summary": "Pick up a cube and move it to a goal with the official SO100 planner.", "capabilities": [ "grasping", "pick-and-place", "motion-planning" ], "aliases": [ "PickCubeSO100-v1", "so100", "so100_pick_cube", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/so100/run.py", "mani_skill/examples/motionplanning/so100/solutions/pick_cube.py", "mani_skill/envs/tasks/tabletop/pick_cube.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "so100", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.so100.solutions.pick_cube:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PickCubeSO100-v1", "seed": 0, "robot": "so100", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-so100-pick-cube --project ./experiment --json" }, "completion": { "success_condition": "PickCubeSO100-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-so100-pick-cube", "requirements_file": "recipes/maniskill-so100-pick-cube/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PickCubeSO100-v1 / so100 motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.so100.solutions.pick_cube import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PickCubeSO100-v1\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PickCubeSO100-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"so100\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-so100-pick-cube.json", "docs/recipes/maniskill-so100-pick-cube.md", "recipes/maniskill-so100-pick-cube/requirements.txt", "recipes/maniskill-so100-pick-cube/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-xarm6-pick-cube", "name": "ManiSkill xarm6_robotiq PickCube-v1 motion planner", "summary": "Grasp a cube and move it to a goal with the official xArm6 Robotiq solver.", "capabilities": [ "grasping", "pick-and-place", "motion-planning" ], "aliases": [ "PickCube-v1", "xarm6_robotiq", "xarm6", "xarm6_pick_cube", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/xarm6/run.py", "mani_skill/examples/motionplanning/xarm6/solutions/pick_cube.py", "mani_skill/envs/tasks/tabletop/pick_cube.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "xarm6_robotiq", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.xarm6.solutions.pick_cube:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PickCube-v1", "seed": 0, "robot": "xarm6_robotiq", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-xarm6-pick-cube --project ./experiment --json" }, "completion": { "success_condition": "PickCube-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-xarm6-pick-cube", "requirements_file": "recipes/maniskill-xarm6-pick-cube/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PickCube-v1 / xarm6_robotiq motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.xarm6.solutions.pick_cube import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PickCube-v1\", robot_uids=\"xarm6_robotiq\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PickCube-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"xarm6_robotiq\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-xarm6-pick-cube.json", "docs/recipes/maniskill-xarm6-pick-cube.md", "recipes/maniskill-xarm6-pick-cube/requirements.txt", "recipes/maniskill-xarm6-pick-cube/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-xarm6-plug-charger", "name": "ManiSkill xarm6_robotiq PlugCharger-v1 motion planner", "summary": "Insert a charger using the official xArm6 Robotiq motion planner.", "capabilities": [ "insertion", "assembly", "grasping", "motion-planning" ], "aliases": [ "PlugCharger-v1", "xarm6_robotiq", "xarm6", "xarm6_plug_charger", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/xarm6/run.py", "mani_skill/examples/motionplanning/xarm6/solutions/plug_charger.py", "mani_skill/envs/tasks/tabletop/plug_charger.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "xarm6_robotiq", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.xarm6.solutions.plug_charger:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PlugCharger-v1", "seed": 0, "robot": "xarm6_robotiq", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-xarm6-plug-charger --project ./experiment --json" }, "completion": { "success_condition": "PlugCharger-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-xarm6-plug-charger", "requirements_file": "recipes/maniskill-xarm6-plug-charger/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PlugCharger-v1 / xarm6_robotiq motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.xarm6.solutions.plug_charger import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PlugCharger-v1\", robot_uids=\"xarm6_robotiq\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PlugCharger-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"xarm6_robotiq\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-xarm6-plug-charger.json", "docs/recipes/maniskill-xarm6-plug-charger.md", "recipes/maniskill-xarm6-plug-charger/requirements.txt", "recipes/maniskill-xarm6-plug-charger/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-xarm6-push-cube", "name": "ManiSkill xarm6_robotiq PushCube-v1 motion planner", "summary": "Push a cube to a goal with the official xArm6 Robotiq solver.", "capabilities": [ "pushing", "object-manipulation", "motion-planning" ], "aliases": [ "PushCube-v1", "xarm6_robotiq", "xarm6", "xarm6_push_cube", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/xarm6/run.py", "mani_skill/examples/motionplanning/xarm6/solutions/push_cube.py", "mani_skill/envs/tasks/tabletop/push_cube.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "xarm6_robotiq", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.xarm6.solutions.push_cube:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "PushCube-v1", "seed": 0, "robot": "xarm6_robotiq", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-xarm6-push-cube --project ./experiment --json" }, "completion": { "success_condition": "PushCube-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-xarm6-push-cube", "requirements_file": "recipes/maniskill-xarm6-push-cube/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official PushCube-v1 / xarm6_robotiq motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.xarm6.solutions.push_cube import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"PushCube-v1\", robot_uids=\"xarm6_robotiq\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"PushCube-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"xarm6_robotiq\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-xarm6-push-cube.json", "docs/recipes/maniskill-xarm6-push-cube.md", "recipes/maniskill-xarm6-push-cube/requirements.txt", "recipes/maniskill-xarm6-push-cube/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } }, { "schema_version": "1", "id": "maniskill-xarm6-stack-cube", "name": "ManiSkill xarm6_robotiq StackCube-v1 motion planner", "summary": "Stack one cube on another with the official xArm6 Robotiq solver.", "capabilities": [ "stacking", "pick-and-place", "motion-planning" ], "aliases": [ "StackCube-v1", "xarm6_robotiq", "xarm6", "xarm6_stack_cube", "robot manipulation", "reusable Python code" ], "source": { "repository": "https://github.com/haosulab/ManiSkill", "commit": "33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "tag": "v3.0.0b22", "paths": [ "mani_skill/examples/motionplanning/xarm6/run.py", "mani_skill/examples/motionplanning/xarm6/solutions/stack_cube.py", "mani_skill/envs/tasks/tabletop/stack_cube.py", "setup.py", "LICENSE" ], "archive_url": "https://codeload.github.com/haosulab/ManiSkill/tar.gz/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907", "archive_sha256": "d194e39e4f86063f7ea49f25c918ca7474d088ad8d5abdc37573daf4672f86d4", "archive_bytes": 243636110, "authors": [ "ManiSkill contributors" ], "contributing_url": "https://github.com/haosulab/ManiSkill/tree/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907" }, "license": { "spdx": "Apache-2.0", "url": "https://github.com/haosulab/ManiSkill/blob/33967b9e3ead1f841eec57cc9f31d0d8b8cf0907/LICENSE", "verified": true, "scope": "Upstream ManiSkill code; hub wrapper and metadata use the hub LICENSE." }, "compatibility": [ { "runtime": "maniskill", "runtime_version": "3.0.0b22", "robot": "xarm6_robotiq", "controller": "pd_joint_pos", "observation": "state", "os": "linux", "architecture": "x86_64", "python": "3.10", "status": "source_reviewed" } ], "observation": { "required": [ "simulator_state" ], "privileged_state": true, "description": "Reads ground-truth object poses, collision geometry and robot state directly from the simulator. Not an RGB-only policy." }, "requirements": { "python": ">=3.10,<3.11", "packages": [ "torch==2.5.1", "numpy==1.26.4", "sapien==3.0.0", "mplib==0.1.1", "fast_kinematics==0.2.2" ], "hardware": [ "Linux x86_64 CPU; SAPIEN wheel needs glibc >=2.28" ], "rendering": "disabled explicitly: render_backend=none, render_mode=None, state observations and CPU simulation; graphics paths require separate Vulkan setup", "api_keys": [], "network": [ "GitHub source archive (~233 MiB)", "PyPI and dependency distributions; source package build hooks may execute" ], "dependency_lock": "Direct dependencies pinned; transitive dependencies resolved by pip and captured in the prepared project. No bit-for-bit environment guarantee." }, "invocation": { "entrypoint": "mani_skill.examples.motionplanning.xarm6.solutions.stack_cube:solve", "argv": [ "{python}", "{recipe_dir}/run.py", "--seed", "0" ], "inputs": { "task": "StackCube-v1", "seed": 0, "robot": "xarm6_robotiq", "controller": "pd_joint_pos", "obs_mode": "state", "sim_backend": "cpu", "render_backend": "none", "reward_mode": "sparse" }, "outputs": { "format": "last stdout line JSON", "fields": [ "status", "success", "elapsed_steps", "task", "seed", "runtime", "robot", "controller", "observation", "sim_backend", "render_backend" ], "error_fields": [ "status", "reason_code", "error_type", "message" ] }, "example": "python skills/find-robot-skills/scripts/rsh.py prepare maniskill-xarm6-stack-cube --project ./experiment --json" }, "completion": { "success_condition": "StackCube-v1 env info.success is true after the upstream solver finishes; exit 0 requires success.", "timeout_seconds": 300, "failure_modes": [ "Dependency installation unavailable or incompatible", "Required Linux mplib wheels unavailable on host OS", "Motion planning reports failure or env info.success is false", "Runtime exception or asset download failure" ], "stop_condition": "Stop after one seed; no automatic retries. Use an external 300-second process timeout." }, "preparation": { "recipe_path": "recipes/maniskill-xarm6-stack-cube", "requirements_file": "recipes/maniskill-xarm6-stack-cube/requirements.txt", "install_argv": [ "{python}", "-m", "pip", "install", "-r", "{recipe_dir}/requirements.txt", "{source_dir}" ], "execution_separate": true, "files": { "run.py": "\"\"\"Hub adapter for the pinned official StackCube-v1 / xarm6_robotiq motion planner.\n\nUpstream solver: ManiSkill contributors, Apache-2.0. This wrapper contains no\nupstream solver implementation. Simulation execution is a separate explicit step.\n\"\"\"\nimport argparse\nimport importlib.metadata\nimport json\n\n\ndef main():\n parser = argparse.ArgumentParser(description=__doc__)\n parser.add_argument(\"--seed\", type=int, default=0)\n args = parser.parse_args()\n actual = importlib.metadata.version(\"mani_skill\")\n if actual != \"3.0.0b22\":\n raise RuntimeError(f\"Expected mani_skill 3.0.0b22, found {actual}\")\n import gymnasium as gym\n import mani_skill.envs\n from mani_skill.examples.motionplanning.xarm6.solutions.stack_cube import solve\n\n # Sparse reward avoids robot-specific dense reward helpers in upstream variants.\n env = gym.make(\"StackCube-v1\", robot_uids=\"xarm6_robotiq\", obs_mode=\"state\",\n control_mode=\"pd_joint_pos\", sim_backend=\"cpu\",\n render_backend=\"none\", render_mode=None, reward_mode=\"sparse\")\n try:\n result = solve(env, seed=args.seed, debug=False, vis=False)\n if isinstance(result, int) and result == -1:\n report = {\"status\": \"failed\", \"reason_code\": \"motion_plan_failed\"}\n else:\n info = result[-1]\n success = bool(info[\"success\"].item())\n report = {\"status\": \"task_complete\" if success else \"failed\",\n \"success\": success, \"elapsed_steps\": int(info[\"elapsed_steps\"].item())}\n report.update(task=\"StackCube-v1\", seed=args.seed, runtime=\"3.0.0b22\",\n robot=\"xarm6_robotiq\", controller=\"pd_joint_pos\", observation=\"state\",\n sim_backend=\"cpu\", render_backend=\"none\")\n print(json.dumps(report))\n return 0 if report.get(\"success\") else 1\n finally:\n env.close()\n\n\nif __name__ == \"__main__\":\n try:\n exit_code = main()\n except Exception as error:\n print(json.dumps({\"status\": \"failed\", \"reason_code\": \"runtime_error\",\n \"error_type\": type(error).__name__, \"message\": str(error)}))\n exit_code = 1\n raise SystemExit(exit_code)\n", "requirements.txt": "# Direct dependencies pinned for the initial Linux / Python 3.10 recipe.\n# Install the SHA256-checked upstream source separately as documented.\ntorch==2.5.1\nnumpy==1.26.4\nsapien==3.0.0\nmplib==0.1.1\nfast_kinematics==0.2.2\n# Transitive dependencies are resolved by pip; this is not a full lockfile.\n" } }, "evidence": { "level": "source_reviewed", "verified_by": "Robot Skill Hub source review", "date": "2026-10-17", "environment": { "source": "pinned upstream release", "host": "Windows source inspection" }, "commands": [ "python tools/import_official_samples.py --archive .local/upstream/maniskill-33967b9.tar.gz --check", "python -m unittest discover -s tests/python -p test_bulk_catalog.py" ], "result": "Inspected the pinned solver signature, task registration, source license and wrapper contract. No simulator invocation evidence is attached.", "artifacts": [], "runtime_verification": "not_run", "contributor_reported": null, "hub_verification": { "level": "source_reviewed", "runtime": "not_run" } }, "maintenance": { "record_version": "1.0.0", "last_checked": "2026-10-17", "upstream_status": "pinned_release; no automatic update" }, "contribution": { "allowed_paths": [ "catalog/records/maniskill-xarm6-stack-cube.json", "docs/recipes/maniskill-xarm6-stack-cube.md", "recipes/maniskill-xarm6-stack-cube/requirements.txt", "recipes/maniskill-xarm6-stack-cube/run.py" ], "instructions": "Only actual reusable fixes. Public submission permission and a scoped pilot token are separate requirements. Submission opens a public internal draft PR; it is not publication." } } ] }