1,594 boosters for "AI" — open source, verified from GitHub, ready to install
You are a Dropbox specialist for the user's connected Dropbox account. Surface the tool's , , , and the you passed inside when the tool returned them. Never invent a field the tool did not return. Return only one JSON object (no markdown or prose outside it):
"name": "figma-developer-mcp", "mcpName": "io.github.GLips/Figma-Context-MCP", "description": "Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.",
An audit skill that systematically evaluates interface quality across accessibility, performance, theming, and responsive design, generating prioritized reports with severity ratings and actionable recommendations. Ideal for developers and QA teams seeking to identify and document UI/UX issues before fixes are implemented.
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.
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.
The 'bolder' booster helps developers amplify visually safe or generic designs into more engaging, memorable experiences while maintaining usability. Best suited for UI/UX developers and designers working with Claude Code who want to enhance design impact.
Polish is a final quality assurance skill that refines UI/UX details like alignment, spacing, and consistency before deployment. It's useful for developers and designers who want to elevate finished features from good to production-ready.
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.
"name": "baoyu-skills", "name": "Jim Liu (宝玉)", "email": "junminliu@gmail.com"
"name": "@midscene/android-mcp", "description": "Midscene MCP Server for Android automation", "bin": "dist/index.js",
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.
This is a Bootstrap 5 admin dashboard template built with CoreUI components. It uses Pug templating, Sass for styles, and vanilla JavaScript for interactivity. 1. Create Pug template in 2. Extend base layout:
"name": "kubeshark", "description": "Kubernetes network observability skills powered by Kubeshark MCP. Root cause analysis, traffic filtering, snapshot forensics, PCAP extraction, and more.", "name": "Kubeshark",
This file explains the Knowledge Base feature and how it's implemented. The knowledge base helps users store and manage information that can be used to help draft responses to emails. It acts as a personal database of information that can be referenced when composing replies. Users can create, edit,
Search the Hugging Face Hub for llama.cpp-compatible GGUF repos, choose the right quant, and launch the model with or . 1. Search the Hub with . 3. Prefer the exact HF local-app snippet and quant recommendation when it is visible.
You are an expert at using the TRL (Transformers Reinforcement Learning) library to train and fine-tune large language models. TRL provides CLI commands for post-training foundation models using state-of-the-art techniques: TRL is built on top of Hugging Face Transformers and Accelerate, providing s
Tiebreakers when the request is ambiguous: "embedding model" / "vector search" / "similarity" → [SentenceTransformer]. "rerank" / "ranker" / "two-stage" → [CrossEncoder]. "SPLADE" / "sparse" / "inverted index" → [SparseEncoder]. If still unclear, ask. Override only if the user specifies otherwise: T
Build and publish a Gradio demo on Hugging Face Spaces that runs inference with a user-provided LoRA. Use whenever someone asks to create, generate, ship, or publish "a Space", "a demo", "a Gradio app", or "a playground" for a LoRA — whether the base model is Qwen-Image, Qwen-Image-Edit, LTX, or ano
Provides the Hugging Face Hub CLI (`hf`) tool for downloading, uploading, and managing models, datasets, and Spaces directly from Claude Code. Essential for developers integrating Hugging Face resources into AI workflows.
This skill provides comprehensive tools for AI engineers and researchers to publish, manage, and link research papers on the Hugging Face Hub. It streamlines the workflow from paper creation to publication, including integration with arXiv, model/dataset linking, and authorship management. The inclu
This skill is for running evaluations against models on the Hugging Face Hub on local hardware. It does not cover: If the user wants to run the same eval remotely on Hugging Face Jobs, hand off to the skill and pass it one of the local scripts in this skill.
Train object detection, image classification, and SAM/SAM2 segmentation models on managed cloud GPUs. No local GPU setup required—results are automatically saved to the Hugging Face Hub. Use this skill when users want to: Helper scripts use PEP 723 inline dependencies. Run them with :
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
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
