How I built a practical agent skill that turns rough READMEs into polished proje

<p>If you've been using AI coding agents like Claude Code, OpenClaw, Codex CLI, or Cursor, you've probably seen people talking about "skills" — packaged instructions that make

<p><a href="https://chainofthought.show/guests/sterling-chin/" rel="noopener noreferrer">Sterling Chin</a>, an applied AI engineer and senior developer advocate at Postman,

<ul> <li>GitHub repository: <a href="https://github.com/gezilinll/agent-grove" rel="noopener noreferrer">https://github.com/gezilinll/agent-grove</a> </li> <li>Online

<p><strong>TL;DR:</strong> I built the same browser agent twice — once with 500 lines of Python, once with 7 lines of JSON. The second one took 5 minutes. The agent harness layer

<p>Eighteen months ago, MCP was <em>the</em> thing. Every demo and chatbot connector was running on MCP under the hood. When I started seeing everyone talk about <em>Skills</em>,

<h1> Google Remy and Meta Hatch: The Technical Architecture Behind 24/7 Personal AI Agents </h1> <p>Two big AI agent stories broke this week that every developer building on top

<p>Most agent setups start with a pile of useful local skills.</p> <p>That pile usually makes sense to the person who built it. There is a skill for GitHub, one for writing, one

<p>I'm a huge fan of coding agents. My daily consumption is at about <strong>7 million tokens</strong> and growing. I started on Cursor, fell in love with OpenCode, got into