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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.

Quality

92%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A tight, directive skill body: it sequences prototyping → task-based verification → service verification with explicit checkpoints and error-recovery loops, and provides concrete commands and source URLs. The main gaps are minor — placeholder arguments in the nohup example and advanced Router/PD content inlined rather than split into reference files.

Suggestions

Move the Router and PD-disaggregation sections into a reference file (e.g. references/advanced.md) and link to them from SKILL.md, keeping the main body focused on the core task→service prototyping loop.

Replace the `nohup vllm serve ...` placeholder with one complete concrete serving command (real flags, model name, port) so the pattern is copy-paste ready.

Consolidate the repeated verification checklist (image, command, port, resources, env vars, cache) into a single named checklist section that later steps reference, trimming duplicated enumerations.

DimensionReasoningScore

Conciseness

The body is lean and directive throughout: no concept explanations Claude already knows (no "what is dstack/vLLM" padding), terse section headers, and purposeful restatement of the config checklist as validation checkpoints rather than filler. Quotes like "Submit the task detached, attach or SSH into it... and run commands inside the live environment" show every token carrying instruction. Not 4 because there is no over-explanation to trim.

5 / 5

Actionability

Mostly executable guidance: a literal task command block (`commands: - sleep infinity`), a full nohup pattern with stdin/stdout redirects, concrete CLI (`dstack fleet get <fleet name> --json`), specific URLs to fetch with named sections to look for ("Look for 'Prototyping services' in https://dstack.ai/docs/concepts/tasks.md"). Not 5 because the nohup example is a placeholder (`nohup vllm serve ...`) and no concrete dstack task/service YAML is shown inline (syntax is delegated to the /dstack skill, which is justified but leaves minor gaps).

4 / 5

Workflow Clarity

Clear sequence with explicit validation checkpoints and a feedback loop: choose backend → check serving sources → task on real hardware → "Do not move to a service after checking only GPU visibility, imports, logs, or a health endpoint" → submit service → verify through service URL → on failure "go back to a task" or "fix the configuration and submit the service again". This matches the top anchor including error-recovery loops.

5 / 5

Progressive Disclosure

Well-organized sections with clearly signaled, one-level-deep references (dstack docs URLs, vLLM/SGLang recipe sources, the /dstack skill for syntax). Not 5 because the body is ~133 lines with advanced Router and PD-disaggregation sections inlined that could live in separate reference files (no references/ bundle exists to absorb them), leaving minor organization gaps.

4 / 5

Total

18

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: it explicitly states both what the skill does and when to use it, in third person, with a concrete enumeration of trigger conditions and specific capabilities. The only improvement space is broader natural-language trigger variations (e.g., deploying/serving a model) to widen retrieval surface.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions covering the full workflow: "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." These are specific capabilities, not vague domain language, and comprehensively cover what the skill does. Not 4 because coverage is essentially complete with no meaningful gaps.

5 / 5

Completeness

Both parts are explicit: what — "Guides task-first prototyping... choosing fleets/backends... checking vLLM/SGLang sources... verifying the final dstack service with a model request"; when — "Use with the dstack skill for model-serving work when the image, serving command, resources, backend/fleet choice, or service behavior is not proven." The trigger clause is concrete and enumerates specific conditions.

5 / 5

Trigger Term Quality

Good natural keyword coverage: "dstack", "model-serving", "vLLM", "SGLang", "fleets/backends", "service", "serving command" — terms a user doing dstack model-serving work would plausibly say. Not 5 because common user-facing variations like "deploy a model", "serve an LLM", or file-extension/URL triggers are missing, so a few natural entry phrases could be added.

4 / 5

Distinctiveness Conflict Risk

It carves out a clear niche (prototyping/unproven serving configurations) and explicitly delineates itself from the adjacent dstack skill ("Use with the dstack skill for model-serving work when... is not proven"), so it is unlikely to trigger for the wrong skill. The trigger terms (dstack, vLLM, SGLang, fleet) are distinctive to this domain.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

dstackai/dstack

Path

skills/dstack-prototyping/SKILL.md

Reviewed

Table of Contents

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