zenml-quick-wins
Implements ZenML quick wins to enhance MLOps workflows. Investigates codebase and stack configuration, recommends high-priority improvements, and implements metadata logging, experiment tracking, alerts, scheduling, secrets management, tags, git hooks, HTML reports, and Model Control Plane setup. Use when: user wants to improve their ZenML setup, asks about MLOps best practices, mentions "quick wins", wants to enhance pipelines, or needs help with ZenML features like experiment tracking, alerting, scheduling, or model governance.
npx skills add majiayu000/claude-skill-registry --skill quick-wins --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.
# ZenML Quick Wins Implementation Guides users through discovering and implementing high-impact ZenML features that take ~5 minutes each. Investigates current setup, recommends priorities, and implements chosen improvements. ## Workflow Overview ``` ┌─────────────────────┐ │ 1. INVESTIGATE │ Understand current stack + codebase └──────────┬──────────┘ ▼ ┌─────────────────────┐ │ 2. CONFIRM │ ⏸️ Check understanding with user └──────────┬──────────┘ ▼ ┌─────────────────────┐ │ 3. GATHER CONTEXT │ ⏸️ Get additional context from user └──────────┬──────────┘ ▼ ┌─────────────────────┐ │ 4. RECOMMEND │ Prioritize quick wins based on findings └──────────┬──────────┘ ▼ ┌─────────────────────┐ │ 5. PREPARE │ ⏸️ Verify branch setup before changes └──────────┬──────────┘ ▼ ┌─────────────────────┐ │ 6. IMPLEMENT │ Apply selected quick wins └──────────┬──────────┘ ▼ ┌─────────────────────┐ │ 7. VERIFY │ Confirm implementation works └─────────────────────┘ ⏸️ = User checkpoint (uses AskUserQuestion tool) ``` --- ## Phase 1: Investigation **Use subagents to gather information efficiently.** This keeps verbose output out of the main conversation while enabling parallel investigation. ### Recommended
- Workflow Overview
- Phase 1: Investigation
- Recommended: Parallel Subagent Investigation
- What the Subagents Investigate
- Pattern Reference for Analysis
- Fallback: Manual Investigation
- MCP Server Check
- Phase 2: Confirm Understanding ⏸️
- What to Summarize
- Confirmation Questions
- Example Confirmation Message
- Phase 3: Gather Context ⏸️
- Infrastructure Context
- Development Environment
Check for uv project if [ -f "pyproject.toml" ] && command -v uv &> /dev/null; then echo "Using uv - prefix commands with 'uv run'" fi Or activate venv/conda source .venv/bin/activate 2>/dev/null || source venv/bin/activate 2>/dev/null || echo "No venv found" Verify zenml is available zenml version Core stack info zenml status
What does the zenml-quick-wins skill do?
Implements ZenML quick wins to enhance MLOps workflows. Investigates codebase and stack configuration, recommends high-priority improvements, and implements metadata logging, experiment tracking, alerts, scheduling, secrets management, tags, git hooks, HTML reports, and Model Control Plane setup. Use when: user wants to improve their ZenML setup, asks about MLOps best practices, mentions "quick wins", wants to enhance pipelines, or needs help with ZenML features like experiment tracking, alerting, scheduling, or model governance.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill quick-wins --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 majiayu000/claude-skill-registry, a repository with 534 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.