model-registry
model-registry is an MLOps & model serving skill for AI agents, published by RHEcosystemAppEng in the agentic-plugins repository on GitHub. Skillspace rates model-registry D (69/100) and it passed the safety scan; the rating is based on static analysis only.
Register, version, and manage ML models in the OpenShift AI Model Registry. Browse the Model Catalog, track model metadata, and promote models across environments. Use when: - "Register a new model in the registry" - "List registered models" - "What versions exist for my model?" - "Promote a model from dev to production" - "Show model artifacts and storage URIs" Handles model registration, versioning, metadata management, artifact tracking, and cross-environment promotion. NOT for deploying models (use /model-deploy). NOT for model performance monitoring (use /ai-observability).
- Grade
- D
- Quality
- 69 / 100
- Safety
- Passed
- GitHub stars
- 44
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 78 / 100
- Maturity
- Packaged: licensed, with a version or references
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
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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