by mattpocock
Skills for Real Engineers. Straight from my .agents directory.
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# Add to your Claude Code skills
git clone https://github.com/mattpocock/skillsGuides for using ai agents skills like skills.
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:
Two ways in, two philosophies. The Claude Code plugin installs the whole set as a managed, read-only bundle that updates when I ship, so you subscribe rather than fork. skills.sh copies editable skill files into your project, so you can hack on them and make them your own. Pick one: installing both leaves you with every skill twice.
claude plugins install mattpocock-skills
Or, from inside a session:
/plugin install mattpocock-skills
It's in Claude Code's official marketplace, so there's nothing to add first, and updates arrive automatically.
npx skills@latest add mattpocock/skills
Pick the skills you want, and which coding agents to install them on. The installer lets you choose which skills to take, so make sure setup-matt-pocock-skills is one of them.
A native Codex plugin is on the roadmap (see .agents/adr/0002-ship-as-a-claude-code-plugin.md).
Use the same installer, on any agent, including Claude Code:
npx skills@latest add mattpocock/skills
It writes the skills into your repo as ordinary files you own and can edit. Nothing updates behind your back; pull my latest changes when you want them with npx skills update.
/setup-matt-pocock-skillsIn your agent, run it once per repo. It will:
/triage uses labels)I built these skills as a way to fix common failure modes I see with Claude Code, Codex, and other coding agents.
"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:
/grill-me - for non-code uses/grill-with-docs - same as /grill-me, but adds more goodies (see below)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.
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.
Here's an example CONTEXT.md, from my course-video-manager repo. Which one is easier to read?
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
"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.
"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:
/to-spec quizzes you about which modules you're touching before creating a specAnd 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.
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.
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.
Skills I use daily for code work.
User-invoked
skills is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by mattpocock. Skills for Real Engineers. Straight from my .agents directory. It has 250,518 GitHub stars.
skills's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/mattpocock/skills" and add it to your Claude Code skills directory (see the Installation section above).
skills is primarily written in Shell. It is open-source under mattpocock on GitHub, so you can review or fork the full source.
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