基于MLOps编码课程的代理技能
概览
本项目包含一系列为配合MLOps编程课程设计的技能。这些技能旨在帮助AI编码助手（如Antigravity、Gemini CLI、GitHub Copilot和Claude Code）理解并引导你掌握MLOps的最佳实践，从原型制作到生产。 客服技能是你可以加载到AI助手中的专业上下文或指令。每个技能都是一个包含 SKILL.md 文件（YAML前置页+Markdown指令）的文件夹，提供特定任务的“Know-How”，确保AI遵循课程的方法论、标准和模式。 每个技能都源自MLOps编程课程的一章： 技能遵循开放 SKILL.md 标准，因此大多数代理从一个知名文件夹中发现技能。工作空间标准位置是 .agents/skills/;每个工具随后从自己的路径读取（见下表）。 1. 访问你机器上的某个位置（例如 ~/mlops-coding-skills）。1.
概述（AI 翻译）
欢迎来到MLOps编程技能仓库！🚀
本项目包含一系列代理技能，旨在配合MLOps编码课程。这些技能旨在帮助AI编码助手（如Antigravity、Gemini CLI、GitHub Copilot和Claude Code）理解并引导你掌握MLOps的最佳实践，从原型制作到生产。
🧠 什么是特工技能？
代理技能是你可以加载到AI助手中的专用上下文或指令。每个技能都是一个包含SKILL.md文件（YAML前置信息+Markdown指令）的文件夹，提供特定任务的“Know-How”，确保AI遵循课程的方法论、标准和模式。
📚 本仓库中的技能
每个技能都源自MLOps编程课程的一章：
| 技能 | 课程章节 | 专注 |
|---|---|---|
mlops-initialization |
1. 初始化 | 建立一个稳健的项目结构，包含uv、git和VS代码。 |
mlops-prototyping |
2. |
本页由 AI 翻译，技术细节请以原文为准。
README
以下为原文 README 节选，完整内容请查看原文。
MLOps Coding Skills
Welcome to the MLOps Coding Skills repository! 🚀
This project contains a collection of Agent Skills designed to accompany the MLOps Coding Course. These skills are tailored to help AI coding assistants (like Antigravity, Gemini CLI, GitHub Copilot, and Claude Code) understand and guide you through the best practices of MLOps, from prototyping to production.
🧠 What are Agent Skills?
Agent Skills are specialized context or instructions that you can load into your AI assistant. Each skill is a folder containing a SKILL.md file (YAML frontmatter + Markdown instructions) that provides the “Know-How” for a specific task, ensuring the AI follows the course’s methodology, standards, and patterns.
📚 Skills in this repository
Each skill derives from one chapter of the MLOps Coding Course:
| Skill | Course chapter | Focus |
|---|---|---|
mlops-initialization |
1. Initializing | Set up a robust project structure with uv, git, and VS Code. |
mlops-prototyping |
2. Prototyping | Write clean, reproducible Jupyter notebooks and prevent data leakage. |
mlops-industrialization |
3. Productionizing | Turn prototypes into a distributable package (src layout, hybrid paradigm). |
mlops-validation |
4. Validating | Add typing (ty), linting (ruff), testing (pytest), logging, scans. |
mlops-automation |
5. Refining | Automate tasks, containers, CI/CD, and experiment tracking (MLflow). |
mlops-collaboration |
6. Sharing | Prepare the project for sharing: license, docs, templates, releases. |
mlops-observability |
7. Observability | Add reproducibility, lineage, monitoring, alerting, and explainability. |
🛠️ Installation & Usage
Skills follow the open SKILL.md standard, so most agents discover them from a well-known folder. The workspace-standard location is .agents/skills/; each tool then reads from its own path (see the table below).
Recommended setup (symlinks)
-
Clone this repository to a location on your machine (e.g.
~/mlops-coding-skills). -
Create the skills directory in your target project or workspace, then symlink the skills you need:
mkdir -p .agents/skills # Symlink every MLOps skill (or pick individual folders): ln -s ~/mlops-coding-skills/mlops-* .agents/skills/ -
Expose them to your agent using the per-tool path below.
Per-tool install paths
推荐工具
换一个关键词，或者移除筛选条件。
安装
npx skillfish add mlops-courses/mlops-coding-skills