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cosmos-framework: Skill for Claude Code

.agents/skills/cosmos3-nano-sim-auto/post-training/SKILL.md

cosmos3-nano-sim-auto-post-training is a skill for Claude Code, Codex from NVIDIA/cosmos-framework. It costs 65 tokens per session (2,831 once invoked), scanned A, original, no licence file.

A Cosmos Framework training workflow that turns Cosmos3-Nano-Transfer-Auto into Cosmos3-Nano-Sim-Auto using customer driving data. It covers distillation, several training methods, saved-model handoffs, resuming, and student export.

In plain words
What is it for?
Use it to run post-training with RGB, WSM, captions, and LiDAR data, manage checkpoints, resume interrupted work, and export the resulting student model.
Why use it?
It gives a defined path for preparing and transferring a model when the training stages and their outputs must connect correctly.

Skill for Claude CodeCodex ✓ vendor

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing. Also seen: installed under .agents/ (shared by several agents).

This is NVIDIA/cosmos-framework's own configuration. It tells Claude Code and Codex how to work on cosmos-framework itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything cosmos-framework configures →

not rated 618repo +29 today A scan 65 tokens custom licence
View source ↗ NVIDIA/cosmos-framework nvidia.github.io
Reuse

Borrowing it

Nothing to install: this file belongs to NVIDIA/cosmos-framework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/NVIDIA/cosmos-framework/main/.agents/skills/cosmos3-nano-sim-auto/post-training/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/NVIDIA/cosmos-framework

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for cosmos3-nano-sim-auto-post-training

README.md
[![agentmods](https://agentmods.dev/badge/skills/nvidia/cosmos-framework/post-training/github.svg)](https://agentmods.dev/skills/nvidia/cosmos-framework/post-training)
Your own site
<a href="https://agentmods.dev/skills/nvidia/cosmos-framework/post-training"><img src="https://agentmods.dev/badge/skills/nvidia/cosmos-framework/post-training/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.

agentmods 80×15 button for cosmos3-nano-sim-auto-post-training

Your own site · 80×15
<a href="https://agentmods.dev/skills/nvidia/cosmos-framework/post-training"><img src="https://agentmods.dev/badge/skills/nvidia/cosmos-framework/post-training.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,831 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00065 $0.02831
Opus 5.5 $0.00026 $0.01132
Sonnet 5.5 $0.00013 $0.00566
Haiku 4.5 $0.00006 $0.00283

Measured 16d ago against content hash 4893bdeba221, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

cosmos3-nano-sim-auto-post-training 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 16d 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.

.agents/skills/cosmos3-nano-sim-auto/post-training/SKILL.md · 253 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

Files

What ships with it

6 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.

Changes

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.

  1. 16d ago First seen · 253 lines · 65 tokens per session scan A 4893bdeba221

Subscribe to this mod's changes

cosmos3-nano-sim-auto-post-training is a skill published in the GitHub repository NVIDIA/cosmos-framework (618 stars, last pushed today), with no licence file. It adds 65 tokens to every session and 2,831 once invoked, about $0.0003 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 2026-10-22.

Data and AIScientific
Related

cosmos3-nano-sim-auto-post-training compared with skills from other repositories

cosmos3-nano-sim-auto-post-training next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
cosmos3-nano-sim-auto-post-trainingNVIDIA/cosmos-frameworkSkill618todaynoneA65Claude Code, Codex
arboretoK-Dense-AI/scientific-agent-skillsSkill56k4d agoMITA55Claude Code, Codex
deepspot-mK-Dense-AI/scientific-agent-skillsSkill56k4d agoMITA70Claude Code
torchdrugK-Dense-AI/scientific-agent-skillsSkill56k4d agoMITA64Claude Code
pyhealthK-Dense-AI/scientific-agent-skillsSkill56k4d agoMITA84Claude Code, Codex
nemo-mbridge-perf-expert-parallel-overlapNVIDIA/skillsSkill3.9kyesterdayApache-2.0A56Claude Code
ml-training-recipesOrchestra-Research/AI-Research-SKILLsSkill14k26d agoMITA88Claude Code