mattpocock/skills

▲ 882 stars today★ 308,196⑂ 25,934

Skills for Real Engineers. Straight from my .agents directory.

About mattpocock/skills

mattpocock/skills is an open-source project on GitHub, mainly written in Shell. Skills for Real Engineers. Straight from my .agents directory. It currently holds 308,196 stars and 25,934 forks with 195 open issues, and was last pushed on 2026-10-31 (repository created 2026-02-03).

Project Overview

AI Homed tracks it on the Today's Trending board, currently at rank #6 with 882 new stars today.

GitHub Repository Details

Repository mattpocock/skills · default branch main · size 2232 KB · watchers 1,595 · source: GitHub REST API and repository README

README

https://github.com/mattpocock/skills/blob/HEAD/Skills

Skills For Real Engineers

skills.sh

My agent skills that I use every day to do real engineering - not vibe coding.

Developing real applications is hard. Approaches like GSD, BMAD, and Spec-Kit try to help by owning the process. But while doing so, they take away your control and make bugs in the process hard to resolve.

These skills are designed to be small, easy to adapt, and composable. They work with any model. They're based on decades of engineering experience. Hack around with them. Make them your own. Enjoy.

If you want to keep up with changes to these skills, and any new ones I create, you can join ~60,000 other devs on my newsletter:

Sign Up To The Newsletter

Installation (30-second setup)

A plugin updates itself. skills.sh copies editable files into your project, and you update them by hand. Pick one per agent, because installing both gives you every skill twice.

1. Get the skills

Claude Code
claude plugin install mattpocock-skills@claude-plugins-official

Updates itself by default.

Codex
codex plugin marketplace add mattpocock/skills
codex plugin add mattpocock-skills@mattpocock

Updates itself at startup.

GitHub Copilot (CLI and VS Code)
copilot plugin marketplace add mattpocock/skills
copilot plugin install mattpocock-skills@mattpocock

Then, once, add to ~/.copilot/settings.json:

{
  "extraKnownMarketplaces": {
    "mattpocock": { "source": { "source": "github", "repo": "mattpocock/skills" }, "autoUpdate": true }
  }
}

In VS Code, run Chat: Install Plugin From Source and enter https://github.com/mattpocock/skills. It updates daily.

Gemini CLI (manual updates)
gemini skills install https://github.com/mattpocock/skills.git --path skills/engineering
gemini skills install https://github.com/mattpocock/skills.git --path skills/productivity

Re-run both commands to update.

Any other agent, or editable files (manual updates)
npx skills@latest add mattpocock/skills -a   # cursor, opencode, devin, windsurf, amp, pi; omit -a to choose

When the installer asks which skills to take, include setup-matt-pocock-skills. To update, run npx skills@latest update, and re-run add to pick up new skills.

2. Run /setup-matt-pocock-skills

In your agent, run it once per repo. It will:

3. Bam - you're ready to go.

Why These Skills Exist

I built these skills as a way to fix common failure modes I see with Claude Code, Codex, and other coding agents.

#1: The Agent Didn't Do What I Want

"No-one knows exactly what they want"
> David Thomas & Andrew Hunt, The Pragmatic Programmer

The Problem. The most common failure mode in software development is misalignment. You think the dev knows what you want. Then you see what they've built - and you realize it didn't understand you at all.

This is just the same in the AI age. There is a communication gap between you and the agent. The fix for this is a grilling session - getting the agent to ask you detailed questions about what you're building.

The Fix is to use:

These are my most popular skills. They help you align with the agent before you get started, and think deeply about the change you're making. Use them _every_ time you want to make a change.

#2: The Agent Is Way Too Verbose

With a ubiquitous language, conversations among developers and expressions of the code are all derived from the same domain model.
> Eric Evans, Domain-Driven-Design

The Problem: At the start of a project, devs and the people they're building the software for (the domain experts) are usually speaking different languages.

I felt the same tension with my agents. Agents are usually dropped into a project and asked to figure out the jargon as they go. So they use 20 words where 1 will do.

The Fix for this is a shared language. It's a document that helps agents decode the jargon used in the project.

Example

Here's an example glossary (still named CONTEXT.md at that pinned commit, from before the skills renamed the convention), from my course-video-manager repo. Which one is easier to read?

  • BEFORE: "There's a problem when a lesson inside a section of a course is made 'real' (i.e. given a spot in the file system)"
  • AFTER: "There's a problem with the materialization cascade"
This concision pays off session after session.

This is built into /grill-with-docs. It's a grilling session, but that helps you build a shared language with the AI, and document hard-to-explain decisions in ADR's.

It's hard to explain how powerful this is. It might be the single coolest technique in this repo. Try it, and see.

[!TIP]
A shared language has many other benefits than reducing verbosity:
> - Variables, functions and files are named consistently, using the shared language
- As a result, the codebase is easier to navigate for the agent
- The agent also spends fewer tokens on thinking, because it has access to a more concise language

#3: The Code Doesn't Work

"Always take small, deliberate steps. The rate of feedback is your speed limit. Never take on a task that’s too big."
> David Thomas & Andrew Hunt, The Pragmatic Programmer

The Problem: Let's say that you and the agent are aligned on what to build. What happens when the agent _still_ produces crap?

It's time to look at your feedback loops. Without feedback on how the code it produces actually runs, the agent will be flying blind.

The Fix: You need the usual tranche of feedback loops: static types, browser access, and automated tests.

For automated tests, a red-green-refactor loop is critical. This is where the agent writes a failing test first, then fixes the test. This helps give the agent a consistent level of feedback that results in far better code.

I've built a /tdd skill you can slot into any project. It encourages red-green-refactor and gives the agent plenty of guidance on what makes good and bad tests.

For debugging, I've also built a /diagnosing-bugs skill that wraps best debugging practices into a disciplined loop, gated phase by phase.

#4: We Built A Ball Of Mud

"Invest in the design of the system _every day_."
> Kent Beck, Extreme Programming Explained
"The best modules are deep. They allow a lot of functionality to be accessed through a simple interface."
> John Ousterhout, A Philosophy Of Software Design

The Problem: Most apps built with agents are complex and hard to change. Because agents can radically speed up coding, they also accelerate software entropy. Codebases get more complex at an unprecedented rate.

The Fix for this is a radical new approach to AI-powered development: caring about the design of the code.

This is built in to every layer of these skills:

And crucially, /improve-codebase-architecture surveys a codebase for deepening opportunities and hands you the candidates. I recommend running it on your codebase once every few days. It is a survey, not a rescue: on a genuinely old codebase it will find real candidates, but it won't untangle the mud for you.

Summary

Software engineering fundamentals matter more than ever. These skills are my best effort at condensing these fundamentals into repeatable practices, to help you ship the best apps of your career. Enjoy.

Reference

These split on one axis: who can invoke them. User-invoked skills are reachable only when you type them (e.g. /grill-me); their job is to orchestrate. Model-invoked skills can be invoked by you _or_ reached for automatically by the agent when the task fits; they hold the reusable discipline. A user-invoked skill may invoke model-invoked skills, but never another user-invoked one.

Engineering

Skills I use daily for code work.

User-invoked

Model-invoked

Productivity

General workflow tools, not code-specific.

User-invoked

Model-invoked

GitHub Stars & Activity

308,196Stars
25,934Forks
195Open issues
ShellLanguage

GitHub Popularity

GitHub stars308,196
Forks25,934
Open issues195
Primary languageShell
LicenseMIT
Stars gained today882
Created2026-02-03
Last pushed2026-10-31

Trending History

Daily boardrank #6 · ▲ 882 stars
Monthly boardrank #2 · ▲ 36,864 stars

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