SKILL.md Deep Dive: Stop Repeating Prompts

Most developers using AI coding agents are making a fundamental mistake: treating AI interactions as one-offs instead of reusable assets. They keep repeating the same prompts and context over and over again.

In this deep dive, I show you how to solve this using SKILL.md—an open standard for defining reusable AI workflows.

As software engineering evolves, we need to move from "Prompt Engineering" to "Agent Orchestration." Instead of writing long prompts every time, you can define structured, version-controlled skills that Codex (and other agents) can follow consistently.

📂 What’s Inside:

00:00 Introduction: What is SKILL.md?
01:45 The Problem with Custom Instructions & Long Prompts
04:12 Exploring the Open Standard: Goals and Benefits
06:30 Key Elements of a Skill: Instructions, Tools, and Resources
08:15 Progressive Disclosure: Managing Large Contexts
10:45 Anatomy of a SKILL.md File (YAML Frontmatter)
13:20 Practical Example: Creating Your First Skill
15:50 The Directory Structure: scripts/, references/, and assets/
17:30 Using the $skill-creator Tool for Automation
19:10 Summary and How to Get Involved with Codex
20:15 Closing Remarks

🛠️ Why This Matters for DevOps & Engineers
Standardisation is the backbone of scalable systems. By applying a DevOps mindset to AI workflows, we can build more reliable, maintainable, and shareable automation. If you're working with AI coding agents, this approach will save you hours of manual work.

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If you're interested in AI, DevOps, and real-world engineering workflows, consider subscribing! I share insights from 20 years of experience in backend systems and infrastructure.