vllm-omni-distributed
vllm-omni-distributed is an MLOps & model serving skill for AI agents, published by hsliuustc0106 in the vllm-omni-skills repository on GitHub. Skillspace rates vllm-omni-distributed D (68/100) and it passed the safety scan; the rating is based on static analysis only.
Scale vLLM-Omni across multiple GPUs and nodes using tensor parallelism, pipeline parallelism, OmniConnector disaggregation, connector backends, and Ray. Use when setting up multi-GPU inference, distributing model execution across machines, deploying disaggregated execution, developing OmniConnector backends, or scaling inference horizontally.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 82
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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