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数据与研究 · SKILL.md

benchmark-integrations

benchmark-integrations

【数据与研究】Guides RoboVerse benchmark metadata, dataset and demo conversion, and optional LIBERO, ManiSkill, MJLab, robosuite, RobotWin, and SimplerEnv integrations.

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GitHub

name: benchmark-integrations description: "Guides RoboVerse benchmark metadata, dataset and demo conversion, and optional LIBERO, ManiSkill, MJLab, robosuite, RobotWin, and SimplerEnv integrations." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Benchmark Integrations

Use this route when the task mentions benchmark task specs, dataset layouts, LIBERO, ManiSkill, MJLab, robosuite, RobotWin, SimplerEnv, passthrough, replay, demo conversion, or cross-framework evaluation.

Route

  1. Read workflows.md to select metadata-only, local-fixture conversion, replay, passthrough, or native integration.
  2. Read data-formats.md before converting or replaying data. Establish task/robot/simulator/camera/action identity and episode boundaries first.
  3. Treat each external stack as an optional backend with its own dependency, asset, license, data, display, GPU, and version gate. The package's CPU import does not verify a native integration.
  4. Run the tiny fixture or inventory path before any download, rollout, render, sweep, or policy evaluation. Record PASS, SKIP_NOT_SELECTED, or the actual blocker; never disguise missing assets as a test failure.
  5. Use troubleshooting.md for locator, format, passthrough, replay, and backend failures.

The BenchmarkTaskSpec metadata API is lightweight and robot-agnostic; use it for planning even when a native benchmark backend is unavailable. Task changes route to task-development; measured parity routes to parity-and-tooling.

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