hami_vgpu_metrics_summarizer
hami_vgpu_metrics_summarizer is an LLM evaluation & observability skill for AI agents, published by Project-HAMi in the HAMi repository on GitHub. Skillspace rates hami_vgpu_metrics_summarizer F (54/100) and it passed the safety scan; the rating is based on static analysis only.
A comprehensive analysis skill for summarizing HAMi vGPU metrics from Prometheus-style `/metrics` output. It organizes GPU allocation by node, device, pod, and namespace, and produces clear reports covering vGPU core allocation, memory allocation, allocation-based utilization, sharing density, and namespace-level usage patterns.
- Grade
- F
- Quality
- 54 / 100
- Safety
- Passed
- GitHub stars
- 4,586
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
- 75 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Not checked yet
- Category is a classifier prediction; no model has read this skill 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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