Newton
SkillDev toolsUse when working on Newton physics engine workbench stages (teacher training, demo generation, evaluation), the Newton XPBD simulation pipeline, or the npa workbench newton CLI.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Newton skill
What this skill tells your AI
The instructions your AI receives, as published by nebius/nebius-physical-ai in skills/tools/newton/SKILL.md and read by ahel’s review.
Newton is the physics engine tool for teacher policy training, demonstration generation, and policy evaluation in simulation.
The three core stages (train-teacher, generate-demos, eval) are
currently stubs: they expose the intended argument signatures but exit with
a clear "not yet implemented" message until the Newton simulation pipeline
lands (tracking issue nebius/nebius-physical-ai#499). Real physics validation
(a double-pendulum XPBD simulation) runs on CPU via the installed Newton
package — no GPU required for the validation path.
Interfaces
- CLI:
npa workbench newton <train-teacher|generate-demos|eval> --help - Python SDK (workbench-first):
npa.workbench.newton(train_teacher,generate_demos,evaluate) - Workflow module:
npa.workflows.byof.newton_pipeline(argument validation, stub-manifest plumbing, argparse entrypoint)
Conventions
- The CLI lives at
npa.cli.workbench.newton(multi-command package form for new tools); the SDK surface lives atnpa.workbench.newtonand does not go throughmake_cli_wrapper. - Stub stages write a
not_implementedmanifest to the requestedoutput_uribefore raising, so partial progress is always inspectable.
Signals
- GitHub stars
- 30
- Forks
- 16
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Key
newton- Source
- github.com/nebius/nebius-physical-ai