Convert Stitch designs into production React + Vite dashboards with TanStack Query, accessible tokens from DESIGN.md, and Web3-ready patterns (ethers/viem).
npx skills add https://github.com/google-labs-code/stitch-skills --skill react-vite-dashboard
You are a frontend engineer building data-dense dashboards from Stitch screens. Target stack: React 18, Vite, TypeScript, TanStack Query, React Router, and optional ethers v6 or viem for on-chain reads.
DESIGN.md (see the design-md skill) for token fidelitynpm create vite@latest)list_tools, note the Stitch prefix (e.g. stitch:).[prefix]:get_screen with project and screen IDs..stitch/designs/{screen}.html and .png.colors.*, typography.*, spacing.* to CSS variables in src/index.css.src/components/, src/pages/, src/hooks/.| Pattern | Implementation |
|---------|----------------|
| Layout grid / flex | Tailwind utilities or CSS modules aligned to DESIGN.md spacing tokens |
| Cards / panels | <section> with tokenized border-radius and elevation fallbacks for forced-colors |
| Tables | Semantic <table> or TanStack Table; never div-only grids for tabular data |
| Buttons | <button type="button"> with visible focus ring (preserve browser default unless DESIGN.md defines focus tokens) |
| Forms | <label htmlFor> + <input id>; associate errors with aria-describedby |
| Loading | Skeleton components; aria-busy on containers during fetch |
| Wallet connect | Isolate in WalletProvider; never embed private keys in generated code |
/* src/index.css — example token bridge */
:root {
--color-primary: /* from DESIGN.md colors.primary */;
--font-body: /* typography.body-md.fontFamily */;
}
Run the design.md linter locally before shipping UI:
npx @google/design.md lint DESIGN.md
useReadContract (viem/wagmi) or ethers Contract + TanStack Query queryFn.formatUnits; show network name and chain ID in settings footer.txHash exists.eth_call in render loops.src/
├── components/ # Presentational UI from Stitch
├── pages/ # Route-level screens
├── hooks/ # useQuery wrappers, wallet hooks
├── lib/ # ABI helpers, formatters
└── styles/ # Token CSS variables
VITE_* prefix only for public endpoints)any on contract ABIsWhen following links on stitch.withgoogle.com/docs, use the full https://stitch.withgoogle.com/docs/... URL if relative navigation redirects incorrectly.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.
Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.
Retrieve and display GitHub Copilot usage metrics for organizations and enterprises using the GitHub CLI and REST API.
Socratic mentoring for junior developers and AI newcomers. Guides through questions, never answers. Triggers: "help me understand", "explain this code", "I''m stuck", "Im stuck", "I''m confused", "Im confused", "I don''t understand", "I dont understand", "can you teach me", "teach me", "mentor me", "guide me", "what does this error mean", "why doesn''t this work", "why does not this work", "I''m a beginner", "Im a beginner", "I''m learning", "Im learning", "I''m new to this", "Im new to this", "walk me through", "how does this work", "what''s wrong with my code", "what''s wrong", "can you break this down", "ELI5", "step by step", "where do I start", "what am I missing", "newbie here", "junior dev", "first time using", "how do I", "what is", "is this right", "not sure", "need help", "struggling", "show me", "help me debug", "best practice", "too complex", "overwhelmed", "lost", "debug this", "/socratic", "/hint", "/concept", "/pseudocode". Progressive clue systems, teaching techniques, and success metrics.
Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.
High-performance DataFrame library for Python ETL, analytics, and pandas migration. Use for expression-based data manipulation with lazy query optimization, parallel execution, streaming out-of-core processing, Arrow interoperability, and optional GPU execution.
Take google-labs-code/react-vite-dashboard from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npx.
Without those the skill loads but fails at the first command.