1,753 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):
Fscan 是一款内网综合扫描工具，功能包括： 二进制路径：当前项目编译产物 ，或系统 PATH 中的 。 每行一个 JSON 对象，所有字段定义：
"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.",
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.
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.
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.
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.
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 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,
Fast, calibration-free weight quantization supporting 8/4/3/2/1-bit precision with multiple optimized backends. HQQ uses to define quantization parameters: The core quantized layer that replaces :
Hugging Face Spaces host machine-learning applications. There are 1M+ today; each Space is a git repo. This skill covers creating, building, debugging, and maintaining them. Before anything else: 1. Check the CLI is installed: . If not, .
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
Finds the best models for a task by querying official HF benchmark leaderboards, enriching results with model size data, filtering for what fits on the user's device, and returning a comparison table with benchmark scores.
Transformers.js enables running state-of-the-art machine learning models directly in JavaScript, both in browsers and Node.js environments, with no server required. Use this skill when you need to: The pipeline API is the easiest way to use models. It groups together preprocessing, model inference,
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
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.
