model-registry-manager
Manage model registry manager operations. Auto-activating skill for ML Deployment. Triggers on: model registry manager, model registry manager Part of the ML Deployment skill category. Use when working with model registry manager functionality. Trigger with phrases like "model registry manager", "model manager", "model". '
Profile →npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill model-registry-manager --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Model Registry Manager ## Overview This skill provides automated assistance for model registry manager tasks within the ML Deployment domain. ## When to Use This skill activates automatically when you: - Mention "model registry manager" in your request - Ask about model registry manager patterns or best practices - Need help with machine learning deployment skills covering model serving, mlops p
What does the model-registry-manager skill do?
Manage model registry manager operations. Auto-activating skill for ML Deployment. Triggers on: model registry manager, model registry manager Part of the ML Deployment skill category. Use when working with model registry manager functionality. Trigger with phrases like "model registry manager", "model manager", "model". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill model-registry-manager --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.