Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".
Create a detailed refactor plan with tiny commits via user interview, then file it as a GitHub issue. Use when user wants to plan a refactor, create a refactoring RFC, or break a refactor into safe incremental steps.
Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".
Disciplined diagnosis loop for hard bugs and performance regressions. Reproduce → minimise → hypothesise → instrument → fix → regression-test. Use when user says "diagnose this" / "debug this", reports a bug, says something is broken/throwing/failing, or describes a performance regression.
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
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:
npx skills@latest add mattpocock/skills
Pick the skills you want, and which coding agents you want to install them on. Make sure you select /setup-matt-pocock-skills.
Run /setup-matt-pocock-skills in your agent. It will:
/triage uses labels)Bam - you're ready to go.
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.
npx claudepluginhub yniantongtian-oss/skillsA growing collection of Claude-compatible academic workflow bundles for producing work at Nature-journal standard. Covers scientific figures (nature-figure), manuscript prose polishing (nature-polishing), manuscript drafting and methods writing (nature-writing), reviewer-style pre-submission assessment (nature-reviewer), citation retrieval and export (nature-citation), data availability statements and FAIR metadata (nature-data), paper-to-PPTX presentation conversion (nature-paper2ppt), literature search via MCP (nature-academic-search), paper reading and annotation (nature-reader), and peer-review response drafting (nature-response). Future releases planned: statistical reporting, cover letters, and review articles. Rules are derived from primary sources, including published Nature papers, journal author guidelines, and structured writing curricula.
Ultra-compressed communication mode. Cuts ~75% of tokens while keeping full technical accuracy by speaking like a caveman.
Frontend design skill for UI/UX implementation
Comprehensive UI/UX design plugin for mobile (iOS, Android, React Native) and web applications with design systems, accessibility, and modern patterns
Memory compression system for Claude Code - persist context across sessions
Marketing skills for AI agents — conversion optimization, copywriting, SEO, paid ads, ad creative, and growth
Standalone image generation plugin using Nano Banana MCP server. Generates and edits images, icons, diagrams, patterns, and visual assets via Gemini image models. No Gemini CLI dependency required.