How to Build Self-Improving Coding Agents, Part 2: Skills as Playbooks
Alternatively titled: How I stopped re-explaining workflows and started building reusable playbooks for my coding agents
Hello fellow datanistas!
Ever find yourself explaining the same workflow to your coding agent over and over? I did, and it was draining my energy. So I started building skills—reusable playbooks that let my agents handle repetitive tasks without me having to spell things out every time.
In this post, I dig into the concept of ‘skills’ for coding agents: what they are, how I use them, and why they’ve become essential in my workflow. If you’re tired of repeating yourself and want your agents to actually learn, this is for you.
Skills are the other half of the self-improving agent system—prompt compression in action. Instead of re-explaining a workflow, I want a playbook I can invoke. For me, a skill is just a folder with a SKILL.md file (the prompt) and any scripts or assets needed. A good skill makes three things explicit: when to use it, what steps to take, and what good output looks like.
Some examples from my own work:
A GitHub debugging skill for CI failures, so the agent follows a repeatable process.
A release announcement skill, so I don’t spend half an hour composing messages for Teams every time.
A report-writing skill for ML model training sessions, using real logs and artifacts.
A domain expertise skill, where a teammate encoded her chromatography debugging process—making tacit knowledge explicit and reusable.
What I like about skills is how easy they are to iterate on. I can feed my agent examples of what “good” looks like, and as my taste evolves, I update the skill. It’s a feedback loop: edit, improve, repeat. Skills are also reviewable and shareable—open a PR, get feedback, and everyone benefits.
Distribution is still a work in progress. Tools like OpenSkills are making it easier to install and update skills across machines and repos, but discovery isn’t standardized yet. Still, the direction is promising, and I expect things to converge soon.
With both memory (AGENTS.md) and skills (playbooks), the next question is: what do you invest in next? That’s what I’ll cover in Part 3.
Skills turn repetitive workflows into reusable playbooks for your coding agents, making them smarter and saving you time.
What’s one workflow you wish your coding agent could handle without you having to explain it every time? Have you tried building a skill for it?
If you want to see concrete examples and my full process, check out the full post: How to build self-improving coding agents - Part 2. If you find it useful, feel free to share or subscribe for updates.
Happy Coding,
Eric