Based on mattpocock/skills Just feel I will change this a lot throug time.

Skills for dev work

My agent skills that I use work on mine and company projects.

Trial and error to see what really useful.

Quickstart (30-second setup)

1. Run the skills.sh installer:

npx skills@latest add luizhcrocha/skills

2. Pick the skills you want, and which coding agents you want to install them on. Make sure you select /setup-luizrocha-skills.

3. Run /setup-luizrocha-skills in your agent. It will:

   • Ask you which issue tracker you want to use (GitHub, Linear, or local files)
   • Ask you what labels you apply to tickets when you triage them (/triage uses labels)
   • Ask you where you want to save any docs we create

4. 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:

• /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.

#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.

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 /diagnose skill that wraps best debugging practices into a simple loop.

#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:

• /to-prd quizzes you about which modules you're touching before creating a PRD
• /zoom-out tells the agent to explain code in the context of the whole system

And crucially, /improve-codebase-architecture helps you rescue a codebase that has become a ball of mud. I recommend running it on your codebase once every few days.

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

Engineering

Skills I use daily for code work.

• diagnose — Disciplined diagnosis loop for hard bugs and performance regressions: reproduce → minimise → hypothesise → instrument → fix → regression-test.
• grill-with-docs — Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates CONTEXT.md and ADRs inline.
• triage — Triage issues through a state machine of triage roles.
• improve-codebase-architecture — Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
• codebase-design — Shared vocabulary and principles for designing deep modules — module, interface, depth, seam, adapter, leverage, locality — used directly or pulled in by other skills.
• domain-modeling — Actively build and sharpen a project's domain model: challenge fuzzy terms, capture the glossary in CONTEXT.md, and record hard-to-reverse decisions as ADRs inline.
• setup-luizrocha-skills — Scaffold the per-repo config (issue tracker, triage label vocabulary, domain doc layout) that the other engineering skills consume. Run once per repo before using to-issues, to-prd, triage, diagnose, tdd, improve-codebase-architecture, or zoom-out.
• tdd — Test-driven development with a red-green-refactor loop. Builds features or fixes bugs one vertical slice at a time.
• to-issues — Break any plan, spec, or PRD into independently-grabbable GitHub issues using vertical slices.
• to-prd — Turn the current conversation context into a PRD and submit it as a GitHub issue. No interview — just synthesizes what you've already discussed.
• zoom-out — Tell the agent to zoom out and give broader context or a higher-level perspective on an unfamiliar section of code.
• prototype — Build a throwaway prototype to flesh out a design — either a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route.
• coding-standards-ts — TypeScript coding standards and design taste: correctness first, precise domain modeling, typed failures, deep modules, explicit boundaries, real-seam tests, with topic files for Effect and Cloudflare.

Productivity

General workflow tools, not code-specific.

• caveman — Ultra-compressed communication mode. Cuts token usage ~75% by dropping filler while keeping full technical accuracy.
• grill-me — Get relentlessly interviewed about a plan or design until every branch of the decision tree is resolved.
• grilling — Get interviewed relentlessly, one question at a time, down every branch of the decision tree until you reach shared understanding. The engine behind grill-me and grill-with-docs.
• handoff — Compact the current conversation into a handoff document so another agent can continue the work.
• orchestrate — Fan a batch of pending tasks out across subagents, a dynamic workflow, or an agent team, partitioned by file ownership so workers never conflict, with shared coding standards baked into every worker prompt.
• teach — Teach a new skill or concept over multiple sessions using a stateful teaching workspace grounded in a mission, trusted resources, and learning records.
• write-a-skill — Create new skills with proper structure, progressive disclosure, and bundled resources.

Misc

Tools I keep around but rarely use.

• git-guardrails-claude-code — Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, etc.) before they execute.
• migrate-to-shoehorn — Migrate test files from as type assertions to @total-typescript/shoehorn.
• scaffold-exercises — Create exercise directory structures with sections, problems, solutions, and explainers.
• setup-pre-commit — Set up Husky pre-commit hooks with lint-staged, Prettier, type checking, and tests.