技能创建器
skill-creator
创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
setup-and-data【数据与研究】Set up NAVSIM v2 dependencies and workspace data, select a supported split, validate paths, and use the Scene, Frame, AgentInput, SensorConfig, and SceneLoader contracts.
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Use this route before training, evaluation, or submission work. It is a read-only setup and data contract: it may inspect an existing environment and workspace, but it must not download archives, delete partial downloads, create large caches, train, score, or upload anything by default.
Read installation.md for the Python/dependency baseline and environment variables.
Read data-layout.md to map a selected split to logs, original sensors, synthetic scenes/sensors, maps, and experiment/cache roots. Treat original and synthetic sensor/log/cache roots as different resources.
Run the bundled, side-effect-free workspace validator before a data-dependent runner:
python scripts/validate_workspace.py --split mini
A successful run ends with VALIDATION PASSED; failures identify the
missing variable or path and exit nonzero. Use --help for split names and
--json for machine-readable diagnostics. The validator does not read a
project config, download data, or create directories.
Read data-api.md when constructing a loader or agent input. Use no-sensor loading first when checking metadata/filtering; enable only the camera history and/or LiDAR iterations actually required by the agent.
For failures, use troubleshooting.md and preserve the distinction between an unavailable optional backend and a broken required data contract.
mini, trainval, and test are OpenScene log/sensor splits.navmini and navtrain are filtered NAVSIM views over mini and
trainval; navtest and the v2 two-stage test views are filtered views over
test. A filtered view does not imply a separate complete log root.navhard_two_stage, warmup_two_stage, and
private_test_hard_two_stage require synthetic/competition assets in
addition to the appropriate original assets. Select their matching bundle;
do not silently reuse navhard_two_stage assets for warmup or private data.test, navtest, navhard_two_stage, warmup_two_stage, or
private_test_hard_two_stage as training data for a competition submission.
See the split matrix in data-layout.md.The nearest references are the authoritative distilled operating context for this sub-skill. They intentionally describe interfaces and layouts rather than asking a later agent to open or execute source-checkout files.