Articles

Matt Pocock's Skills project is an engineering skill library designed for AI coding assistants (e.g., Claude Code). By modularizing standard software development workflows, it addresses the core pain point of unstable AI-generated code quality. This project, built with just a few Markdown files, has earned 23,000 stars on GitHub, becoming a pivotal practice in AI-assisted development.

Many frontend engineers feel confused the first time they hear about MCP. The name sounds like a protocol, the content feels like agents, and people keep mentioning tools, prompts, resources, and skills. You do not need to digest all of those terms at once; the key idea is simple: MCP is a standard way to let AI connect to tools, fetch data, and actually get things done.

code-review-graph is an open-source tool designed for AI coding assistants. It builds a structured “knowledge graph” of your codebase locally, then feeds only the truly relevant context to the AI, instead of rescanning the entire repository for every task. It uses Tree-sitter to parse ASTs, models functions, classes, imports, call relationships, and tests as a graph, and exposes this graph via MCP to tools like Claude Code, Codex, and Cursor.

Right now, the main full‑stack frameworks I use are Next.js 16 and Rails 8. Through Rails, I came across the officially recommended deployment tool: Kamal. I usually use it to deploy projects on RN and Alibaba Cloud servers. It feels smooth and simple to work with, so I’d like to introduce Kamal2’s core concepts and basic usage to you as well.

In one sentence: Prisma is a modern ORM and data access toolkit for TypeScript and JavaScript.