dstack

A unified orchestration layer for heterogeneous AI compute. It standardizes how to manage compute and run training and inference on GPU clouds, Kubernetes, VMs, or bare-metal clusters.

Stars: 2.3k
Skills: 3
License: MPL-2.0
Last commit: Nov 10, 2026

install.sh

# every skill in this repo, via the skills CLI

npx skills add dstackai/dstack

# or, for Claude Code, copy one skill folder into

~/.claude/skills/ (all projects)

.claude/skills/ (this project)

View dstackai/dstack on GitHub

Inside this pack

3 skills in dstack

Each skill is a SKILL.md file your agent loads when a task matches its description.

01
dstack-presets
Create and manage dstack presets: a toolkit that streamlines model inference optimization with agents, and a portable preset format. Use together with the dstack skill, and only when the user explicitly asks to create a preset or manage existing presets, not for deploying or serving a model.
View skill
02
dstack-prototyping
Use with the dstack skill for model-serving work when the image, serving command, resources, backend/fleet choice, or service behavior is not proven. Guides task-first prototyping on real hardware, choosing fleets/backends that can reuse idle instances and caches, checking vLLM/SGLang sources, and verifying the final dstack service with a model request.
View skill
03
dstack
dstack is an open-source control plane for GPU provisioning and orchestration across GPU clouds, Kubernetes, and on-prem clusters.
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