645 boosters for "ui" — open source, verified from GitHub, ready to install
Provides developers with authoritative, up-to-date OpenAI API documentation and guidance by prioritizing official MCP tools for questions about building with OpenAI products. Ideal for developers integrating OpenAI APIs who need reliable, cited references.
Automates translation of Figma designs into production-ready code with pixel-perfect visual accuracy using the Figma MCP workflow. Ideal for developers and designers who need to implement designs quickly while maintaining design fidelity.
Use MCP to execute JavaScript in Figma files via the Plugin API. All detailed reference docs live in . Before anything, load plugin-api-standalone.index.md to understand what is possible. When you are asked to write plugin API code, use this context to grep plugin-api-standalone.d.ts for relevant t
Build professional-grade design systems in Figma that match code. This skill orchestrates multi-phase workflows across 20–100+ calls, enforcing quality patterns from real-world design systems (Material 3, Polaris, Figma UI3, Simple DS). Every design system build follows this phase order. Skipping o
Automates real browser interactions from the terminal using Playwright CLI for tasks like navigation, form filling, and data extraction. Useful for developers and AI assistants building UI automation workflows without writing test frameworks.
Use this skill when the quality of the work depends on art direction, hierarchy, restraint, imagery, and motion rather than component count. Goal: ship interfaces that feel deliberate, premium, and current. Default toward award-level composition: one big idea, strong imagery, sparse copy, rigorous s
A skill for building and scaffolding ChatGPT Apps SDK applications that combine MCP servers with widget UIs, using a docs-first workflow. Developers building ChatGPT extensions and integrations benefit from structured guidance on tool design, UI registration, and SDK compliance.
A meta-guide that helps users create or update specialized skills to extend Codex's capabilities with domain-specific knowledge and workflows. Developers and AI agents building custom extensions benefit from this structured approach to skill development.
Playwright Interactive enables fast iterative UI debugging by keeping browser and Electron instances alive in a persistent js_repl session, allowing developers to test and refine UI interactions without repeated restarts.
A skill that helps developers create distinctive, production-grade frontend interfaces with polished aesthetics and creative design choices, avoiding generic AI-generated outputs. Ideal for developers building web components, pages, and applications who want professional design quality.
A skill booster that helps developers design and improve onboarding flows, empty states, and first-time user experiences to accelerate user adoption and value realization. Ideal for product teams and developers building user-facing applications.
A design refinement skill that tones down overly bold or aggressive visual elements while preserving design impact, useful for designers and developers seeking more subtle, approachable aesthetics.
teach-impeccable is a one-time setup skill that automatically discovers and persists your project's design context (patterns, tokens, brand assets) into your AI config, enabling Claude Code to maintain consistent design guidelines across all future sessions.
Deep Agents is a system prompt for building intelligent agent assistants with planning, filesystem, and sub-agent capabilities across Claude and other AI platforms. It benefits developers building complex agentic workflows who need structured, production-ready agent behavior.
A Cursor rules prompt that standardizes the DataHub development workflow by directing developers to use a centralized shell script (datahub-dev.sh) for all build, test, and flag operations. This benefits DataHub contributors by reducing setup friction and ensuring consistent development practices across the team.
Train language models using TRL (Transformer Reinforcement Learning) on fully managed Hugging Face infrastructure. No local GPU setup required—models train on cloud GPUs and results are automatically saved to the Hugging Face Hub. Use this skill when users want to: Use Unsloth () instead of standard
Gradio is a Python library for building interactive web UIs and ML demos. This skill covers the core API, patterns, and examples. Detailed guides on specific topics (read these when relevant): Creates a textarea for user to enter string input or display string output..
Your purpose is now is to create reusable command line scripts and utilities for using the Hugging Face API, allowing chaining, piping and intermediate processing where helpful. You can access the API directly, as well as use the command line tool. Model and Dataset cards can be accessed from repos
A skill that generates reusable command-line scripts for automating Hugging Face API interactions, useful for developers who need to repeatedly fetch, process, or chain API calls.
A skill booster for building interactive web UIs and ML demos using Gradio in Python. Developers creating data applications, ML interfaces, and chatbots benefit from guided assistance with Gradio components and patterns.
A skill for fine-tuning and training language models on Hugging Face's cloud GPU infrastructure using TRL, supporting SFT, DPO, GRPO methods and GGUF conversion for local deployment. Developers and ML engineers working with cloud-based model training benefit from this comprehensive guidance.
Ripple is a TypeScript UI framework that combines the best parts of React, Solid, and Svelte. Created by Dominic Gannaway (@trueadm), Ripple is designed to be JS/TS-first with its own file extension that
"name": "context-mode", "version": "1.0.75", "description": "MCP server that saves 98% of your context window with session continuity. Sandboxed code execution in 11 languages, FTS5 knowledge base with BM25 ranking, and automatic state restore across compactions.",
You are the ZCF DevOps Engineer for the ZCF (Zero-Config Code Flow) project.
