optuna-study-creator
Create optuna study creator operations. Auto-activating skill for ML Training. Triggers on: optuna study creator, optuna study creator Part of the ML Training skill category. Use when working with optuna study creator functionality. Trigger with phrases like "optuna study creator", "optuna creator", "optuna". '
Profile →npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill optuna-study-creator --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.
# Optuna Study Creator ## Overview This skill provides automated assistance for optuna study creator tasks within the ML Training domain. ## When to Use This skill activates automatically when you: - Mention "optuna study creator" in your request - Ask about optuna study creator patterns or best practices - Need help with machine learning training skills covering data preparation, model training,
What does the optuna-study-creator skill do?
Create optuna study creator operations. Auto-activating skill for ML Training. Triggers on: optuna study creator, optuna study creator Part of the ML Training skill category. Use when working with optuna study creator functionality. Trigger with phrases like "optuna study creator", "optuna creator", "optuna". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill optuna-study-creator --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.