msresearch-mattergen Skill
MatterGen workflows for property-conditioned inorganic crystal generation, MatterSim triage, adapter fine-tuning, and Azure AI Foundry hosted deployment. Use when users ask about MatterGen, materials discovery, crystal generation, property-conditioned diffusion (bulk modulus, band gap, magnetic density, HHI), MatterSim Published by microsoft in vibe-kit.
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Deployment, Includes SKILL.md, Reusable instructions
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Copy skill directory
4 months ago · NOASSERTION license
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What is msresearch-mattergen Skill?
MatterGen workflows for property-conditioned inorganic crystal generation, MatterSim triage, adapter fine-tuning, and Azure AI Foundry hosted deployment. Use when users ask about MatterGen, materials discovery, crystal generation, property-conditioned diffusion (bulk modulus, band gap, magnetic density, HHI), MatterSim Published by microsoft in vibe-kit. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Deployment
- Deployment use cases
Declared skill metadata
- Declared license: MIT
- Source file: skills/msresearch-mattergen/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use msresearch-mattergen Skill
- Use it for deployment.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/vibe-kit
- Skill file: skills/msresearch-mattergen/SKILL.md
What it does
MatterGen workflows for property-conditioned inorganic crystal generation, MatterSim triage, adapter fine-tuning, and Azure AI Foundry hosted deployment. Use when users ask about MatterGen, materials discovery, crystal generation, property-conditioned diffusion (bulk modulus, band gap, magnetic density, HHI), MatterSim
Skill instructions
Scope - Property-conditioned inorganic crystal generation and candidate triage - Local CUDA workflows, hosted Azure AI Foundry inference, adapter-based extension - Generation, evaluation, and adapter fine-tuning only — DFT-level physics validation is out of scope and should be handed to computational chemistry teams Prerequisites - Windows users: run inside a WSL2 distro (Ubuntu recommended) with NVIDIA drivers installed on the Windows host (not inside WSL). The MatterGen/MatterSim prototype was developed and tested on WSL2/Ubuntu; native Windows Python/PowerShell is not supported for the local CUDA path. See Microsoft's WSL install guide and NVIDIA's CUDA-on-WSL guide. The Azure AI Foundry hosted path still requires WSL2 for the local CLI tooling used to call it. - Python 3.10 (3.11+ breaks torchcluster wheels) with pip and uv - CUDA-capable GPU (16 GB VRAM recommended) — or Azure AI Foundry access for the hosted path - Git LFS installed before cloning the MatterGen repo - MatterSim i
Verified compatibility and discovery
Frequently asked questions
What is msresearch-mattergen?
msresearch-mattergen is a open-source AI agent skill with Copy skill directory. MatterGen workflows for property-conditioned inorganic crystal generation, MatterSim triage, adapter fine-tuning, and Azure AI Foundry hosted deployment.
Who is msresearch-mattergen best for?
msresearch-mattergen is best for reusing agent instructions, scripts, and references, deployment workflows.
How do I install msresearch-mattergen?
Install or run msresearch-mattergen using Copy skill directory. Check msresearch-mattergen for the latest setup command.
Is msresearch-mattergen actively maintained?
msresearch-mattergen may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
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Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
