Amc Setup Calibration Stack
NVIDIA/skills
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose.
Diagnose and repair failures in this repository's mesh-to-USD generation, scoped USD validation, recorded-support inference, FoundationPose calibration, catalog batching, or Isaac Sim drop tests.
Install Mesh To Usd Doctor
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-doctor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-doctor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/mesh-to-usd-doctor .claude/skills/mesh-to-usd-doctor && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "mesh-to-usd-doctor" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-doctor into .claude/skills/mesh-to-usd-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-doctor", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-doctorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-doctor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-doctor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.codex/skills/mesh-to-usd-doctor .agents/skills/mesh-to-usd-doctor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "mesh-to-usd-doctor" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-doctor into .agents/skills/mesh-to-usd-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-doctor", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-doctor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-doctor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.codex/skills/mesh-to-usd-doctor .cursor/skills/mesh-to-usd-doctor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "mesh-to-usd-doctor" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-doctor into .cursor/skills/mesh-to-usd-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-doctor", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/nvidia-isaac/video_to_data.git --path .codex/skills/mesh-to-usd-doctor--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-doctor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-doctor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.codex/skills/mesh-to-usd-doctor .gemini/skills/mesh-to-usd-doctor && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "mesh-to-usd-doctor" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-doctor into .gemini/skills/mesh-to-usd-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-doctor", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-doctorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-doctor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .github/skills && cp -r skills-src/.codex/skills/mesh-to-usd-doctor .github/skills/mesh-to-usd-doctor && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "mesh-to-usd-doctor" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-doctor into .github/skills/mesh-to-usd-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-doctor", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-doctor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install nvidia-isaac/video_to_data mesh-to-usd-doctor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nvidia-isaac/video_to_data.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.codex/skills/mesh-to-usd-doctor .opencode/skills/mesh-to-usd-doctor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "mesh-to-usd-doctor" agent skill from https://github.com/nvidia-isaac/video_to_data/tree/main/.codex/skills/mesh-to-usd-doctor into .opencode/skills/mesh-to-usd-doctor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "mesh-to-usd-doctor", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
mesh-to-usd-doctor- GitHub stars
- 861
- Token cost
- ~1.4k tokens
- SKILL.md length
- 594 words
- Files
- 2
- Skills in repo
- 13
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Diagnose and repair failures in this repository's mesh-to-USD generation, scoped USD validation, recorded-support inference, FoundationPose calibration, catalog batching, or Isaac Sim drop tests.
- Works in 5 steps: Read the exact command and error from… → If no output directory is named, inspect… → Infer the input mode from… → …
- Input contracts
- SKILL.md covers Discover context automatically, Run the fast diagnostic set, Classify the first failure and Detect a stall correctly, plus 1 more section
- Calls python, docker and git
What it does
Mesh To Usd Doctor is an agent skill from nvidia-isaac/video_to_data. Diagnose and repair failures in this repository's mesh-to-USD generation, scoped USD validation, recorded-support inference, FoundationPose calibration, catalog batching, or Isaac Sim drop tests. Use when Docker, GPU, EULA, weights, input contracts, CoACD collision generation, USD references, validation, scale, mesh hashes, contact, settling, standing, videos, reports, resume, or batch status are missing, inconsistent, stalled, or failing.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in DevOps & Cloud, covering Performance reviews and Containers. It works with Docker. The repository describes itself as: Nvidia Isaac Video to Data Pipeline.
When your agent uses it
- Input contracts
- CoACD collision generation
- Batch status are missing
Example prompts
- “/mesh-to-usd-doctor”
Requirements
- Python 3
- Docker
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Read the exact command and error from the conversation or available log.
- If no output directory is named, inspect the newest relevant directory
- Infer the input mode from mesh_to_usd_workflow_report.json and command
- Infer the first incomplete stage from reports and timestamps: support,
- Ask one focused question only when neither input nor output can be found.
What it can do on your machine
Read from SKILL.md and the folder at commit 193382a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
pythondockergit
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use docker and git, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Mesh To Usd Doctor loads about 1.4k tokens when it runs. Until then it costs about 116 tokens; SKILL.md has 594 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 594 words (~1,414 tokens).
“Inspect evidence first and ask later. Work from reconstruction/, preserve the job directory and videos, and diagnose the first bad stage rather than rebuilding or rerunning everything.”
- name
- mesh-to-usd-doctor
Files
SKILL.md and 1 other file in .codex/skills/mesh-to-usd-doctor of nvidia-isaac/video_to_data.
- SKILL.md
- agents/openai.yaml
Open the folder on GitHubat commit 193382a
Compare with similar skills
Mesh To Usd Doctor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Mesh To Usd Doctor this skillnvidia-isaac/video_to_data | 861 | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Amc Setup Calibration StackNVIDIA/skills | 3.6k | — | ~3.9k | Automated safety check: Notes | Apache-2.0 | |
| Iron Proxy Gateway for NanoClawnanocoai/nanoclaw | 31k | — | ~4.6k | Automated safety check: Notes | MIT | |
| GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb | 6.7k | — | ~4k | Automated safety check: Notes | Apache-2.0 | |
| Senior DevOps Toolkitmaslennikov-ig/claude-code-orchestrator-kit | 260 | 6 repos | ~1.1k | Automated safety check: Notes | Custom licence | |
| LangBot Deployment Guidelangbot-app/LangBot | 18k | — | ~1.5k | Automated safety check: Notes | Apache-2.0 |
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Questions about Mesh To Usd Doctor
What does Mesh To Usd Doctor do?
Diagnose and repair failures in this repository's mesh-to-USD generation, scoped USD validation, recorded-support inference, FoundationPose calibration, catalog batching, or Isaac Sim drop tests. Mesh To Usd Doctor is an agent skill from nvidia-isaac/video_to_data. Diagnose and repair failures in this repository's mesh-to-USD generation, scoped USD validation, recorded-support inference, FoundationPose calibration, catalog batching, or Isaac Sim drop tests.
When should I use Mesh To Usd Doctor?
Mesh To Usd Doctor fits situations like: input contracts; coACD collision generation; batch status are missing.
How do I install Mesh To Usd Doctor in Claude Code?
Run `npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-doctor -a claude-code`. Or copy the skill folder (.codex/skills/mesh-to-usd-doctor in nvidia-isaac/video_to_data) into .claude/skills/mesh-to-usd-doctor in your project. Claude Code loads it when a task matches its description.
How do I install Mesh To Usd Doctor in Codex?
Run `npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-doctor -a codex`. Or copy the skill folder (.codex/skills/mesh-to-usd-doctor in nvidia-isaac/video_to_data) into .agents/skills/mesh-to-usd-doctor in your project. Codex loads it when a task matches its description.
Can I use Mesh To Usd Doctor in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add nvidia-isaac/video_to_data --skill mesh-to-usd-doctor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mesh-to-usd-doctor, .gemini/skills/mesh-to-usd-doctor, .github/skills/mesh-to-usd-doctor and .opencode/skills/mesh-to-usd-doctor in your project.
What does Mesh To Usd Doctor need to run?
Going by SKILL.md and its folder, Mesh To Usd Doctor needs the command-line tools its instructions call (python, docker and git). Our summary lists: Python 3; Docker.
Does Mesh To Usd Doctor access the network?
SKILL.md contains no URLs. Its commands use docker and git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Mesh To Usd Doctor safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Mesh To Usd Doctor use?
Mesh To Usd Doctor has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Mesh To Usd Doctor use?
About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Mesh To Usd Doctor?
Skills that share tags, products or a category with Mesh To Usd Doctor: Amc Setup Calibration Stack (NVIDIA/skills, 3.6k stars), Iron Proxy Gateway for NanoClaw (nanocoai/nanoclaw, 31k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars) and Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 260 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Mesh To Usd Doctor?
nvidia-isaac (a GitHub organization) maintains it in nvidia-isaac/video_to_data, which has 861 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 8, 2026.
Source: nvidia-isaac/video_to_data on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.