Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nebius/nebius-physical-ai --skill mjlabgit clone --depth 1 https://github.com/nebius/nebius-physical-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nebius/nebius-physical-ai/mjlab)<a href="https://agentmods.dev/skills/nebius/nebius-physical-ai/mjlab"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/mjlab/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nebius/nebius-physical-ai/mjlab"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/mjlab.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00033 | $0.00238 |
| Opus 5 | $0.00016 | $0.00119 |
| Sonnet 5 | $0.00007 | $0.00048 |
| Haiku 4.5 | $0.00003 | $0.00024 |
Grade A, and why
mjlab scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
MJLab
MJLab is the locomotion evaluation stage for SONIC Workbench workflows.
Interfaces
CLI:
npa workbench mjlab eval
npa workbench mjlab workflow
npa workbench mjlab status
npa workbench mjlab list
SkyPilot YAML:
workflows/testing/mjlab-eval.yamlworkflows/testing/sonic-locomotion-finetuning.yaml
Routing And Data Flow
Route MJLab evaluation to H100 for the checked-in workflow templates.
Inputs and outputs use S3 paths:
--input-path: retargeted motion or rollout artifacts.--checkpoint: SONIC checkpoint artifact.--output-path: MJLab evaluation output prefix.
The result artifact is mjlab_eval.json.
Workflow Constraint
Keep orchestration logic in SkyPilot YAML. Do not add a Python runner script for the SONIC locomotion fine-tuning path.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago Changed af64bc9eecf7
- 12d ago First seen · 42 lines · 33 tokens per session scan A ca7ac6e69c7d
mjlab is a skill published in the GitHub repository nebius/nebius-physical-ai (29 stars, last pushed today), licensed Apache-2.0. It adds 33 tokens to every session and 238 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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