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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.
Passed 22 of 22 test cases with the skill, and 5 of 22 without it.
and 18 more in the full report
17 fixed5 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 17 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which CLI subcommand group in dstack is dedicated to listing, watching, exporting, and deleting preset artifacts?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies `dstack preset` as the command group. | Missed | Passed |
The instructions your model reads when the skill loads.
Use /dstack for CLI commands, YAML fields, apply behavior, fleets, and other
dstack syntax. This skill covers creating and managing presets.
Presets offer two things: a toolkit that streamlines model inference optimization using agents, and a portable format that deploys the final preset to any cloud, Kubernetes cluster, or bare-metal fleet. A preset holds the serving configuration that produced the result, the benchmark it reached, and the exact hardware it was verified on.
Presets are used for three kinds of work: finding an optimized baseline, optimizing through patching source code, and supporting new hardware.
When to use this skill:
dstack preset commandsWhen NOT to use this skill:
dstack skill)Follow the presets documentation.
test cases passed, vs 5 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.