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 cosmos-data-factorygit 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/cosmos-data-factory)<a href="https://agentmods.dev/skills/nebius/nebius-physical-ai/cosmos-data-factory"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/cosmos-data-factory/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/cosmos-data-factory"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/cosmos-data-factory.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00041 | $0.00574 |
| Opus 5.5 | $0.00016 | $0.00230 |
| Sonnet 5.5 | $0.00008 | $0.00115 |
| Haiku 4.5 | $0.00004 | $0.00057 |
Grade A, and why
cosmos-data-factory 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 9d 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
Cosmos Data Factory IAA and EVG
Keep CDF-specific work in this directory. Leave
workflows/main/paidf-cosmos3.yaml in place. This package adapts NVIDIA's
IAA/EVG reference implementation to the existing NPA CLI and SkyPilot runtime;
the README records the pinned source and orchestration mapping.
For robotics requests, use the README's task-fit and reuse map. Reuse the existing main PAIDF/VDA path for robot-video augmentation and existing LeRobot/Sim2Real tools for training/evaluation. IAA supports human-appearance perception; EVG supports generated-event perception. Do not duplicate those existing graphs or treat a physical-AI label as proof of robot-policy usefulness.
Load shared setup, then the matching workflow skill:
- IAA: skill and guide. Use person images to evaluate clothing, color, and footwear edits with verification/search labels.
- EVG: skill and guide. Use scene images to evaluate generated event videos with detection, tracking, captioning, QA, and search annotations.
Use the two checked-in specs through generic npa workbench workflow commands.
Retain their nine-state IAA and twelve-state EVG graphs and real component
adapters. The existing canonical skills stay registered in skills/index.yaml;
this local entry point links them without creating another implementation.
Check the guides' current sampling coverage before promising an attribute or
event. IAA exposes six clothing/footwear fields; EVG's fixed event list omits
fighting and shoplifting. Upstream distribution JSON is not a direct NPA override.
Choose inputs using the guides before treating a run as a representative demo. For requested visual proof, follow proof.md, including actual media, source hashes, sampled attributes/events, annotation coverage, and quality verdicts. Keep historical integration fixtures identified as such. Robot dataset frames used for EVG test image-to-event-video synthesis; they do not establish robot action or policy generalization. Video-to-video edge conditioning remains part of the separate main PAIDF workflow.
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 44 lines · 41 tokens per session scan A f9b42e349562
cosmos-data-factory is a skill published in the GitHub repository nebius/nebius-physical-ai (50 stars, last pushed today), licensed Apache-2.0. It adds 41 tokens to every session and 574 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-10-13.
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