Dictionary
Design vocabulary, key terms, techniques, and AI language for designers.
26 resources
Design Tokens
The smallest units of a design system. Named values that store visual design decisions like colors, spacing, typography, and shadows.
MCP (Model Context Protocol)
A standard that helps AI assistants connect to tools like Figma with rich context. The bridge between your design files and AI coding tools.
AI Agent
An AI that does not just answer, it acts: reads files, runs tools, makes changes, and works toward a goal across multiple steps with limited supervision.
Context Window
Everything the AI can 'see' at once: your prompt, the files, the images, and the conversation so far. When it fills up, older details fall out of view.
LLM (Large Language Model)
The kind of AI behind Claude, ChatGPT, and Gemini. A model trained to predict text, which makes it good at writing, coding, and reasoning over language.
Animation Vocabulary
The working vocabulary of UI motion. Around 80 terms for entrances, easing, springs, transitions, scroll, and performance, so you can name the exact motion you want instead of asking for 'smoother'.
Chromatic
A visual regression testing service built for Storybook. Catches unintended UI changes before they ship.
CLAUDE.md
A markdown file that teaches Claude Code about a project. Turns generic AI output into project-aware AI output.
Design System Observatory
A monitoring dashboard that tracks the health of your design system. Measures token coverage, component adoption, accessibility, and design-code parity.
Environment Variables (.env files)
A .env file is a small text file that holds secrets like API keys outside your code. Your app reads from it at runtime. Never commit it to Git.
GitHub Actions
GitHub's built-in CI/CD platform. Runs workflows in response to events like a push, a pull request, or a schedule.
Personal Access Token (PAT)
A secret string that authenticates a user with a service like GitHub or Figma in place of a password.
Playwright
A browser automation tool for end-to-end tests, visual regression, and automatic component screenshots.
Primitive vs Semantic Tokens
The difference between raw value tokens and purpose-driven tokens. Understanding this distinction is essential for scalable design systems.
Storybook
A tool for developing, documenting, and testing UI components in isolation. The default home for design system component docs.
Style Dictionary
An open-source build system that transforms design tokens from JSON into any platform format (CSS, iOS, Android, and more).
Supabase
A backend platform with database, auth, and storage features. A pre-built infrastructure kit for web applications.
Tokens Studio
A Figma plugin that manages design tokens inside Figma and syncs them to GitHub, GitLab, or other sources of truth.
Vercel
A deployment and hosting platform for modern web applications. The 'publish to web' button with strong defaults.
Hallucination
When an AI states something false with full confidence: a made-up API, a token that does not exist, a citation that was never written. Fluent, plausible, and wrong.
Prompt
The instruction you give an AI. The clearer and more specific it is, the better the result. A system prompt sets the standing rules for the whole session.
RAG (Retrieval-Augmented Generation)
A technique that lets an AI look things up before it answers. It retrieves the relevant documents first, then generates from them, instead of relying on memory.
Skill (Claude Code)
A reusable instruction file that teaches Claude how to do one job your way, invoked with a slash command. Your taste, your review process, your rules, made portable.
Subagent
A second AI agent spun up to handle one focused task in its own context, then report back. Used to search, review, or work in parallel without cluttering the main session.
Tokens (the AI kind, not design tokens)
The small chunks of text an AI reads and writes, and what your usage is measured in. Not to be confused with design tokens, which are reusable style values.
Vibe Coding
Building software by describing what you want in plain language and letting the AI write the code, steering by feel and result rather than by reading every line.