About this skill
Deploy an LLM on vLLM with continuous batching, deliberate VRAM planning, and multi-model hosting that never overcommits the card. Use when serving on vLLM and deciding memory fraction, context length, tensor parallel size, and how many models share a GPU.
Quick start
- Copy the install prompt. Use the green button above this README.
- Send it to your agent. Paste it into your coding agent’s chat and send.
- Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.
Review, license & listing details
This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.
Only SKILL.md was scanned. Supporting files and scripts were not checked. No safety grade has been assigned.
0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1
Content SHA-256: 83829834cfb2392b672faf0efb61724a813e98c9a74a8871b67b38c70fd4aaf7
About this listing
- Category
- General
- Reported license
- MIT
- Listing language (estimated)
- English
- Review status
- Not individually reviewed
- Agent compatibility
- Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.