1,482 boosters for "cu" — open source, verified from GitHub, ready to install
"email": "tobi@lutke.com" "description": "Search and retrieve documents from local markdown files.", "email": "tobi@lutke.com"
A comprehensive collection of 1000+ production-ready agentic skills for Claude and related AI coding platforms, enabling developers to rapidly build autonomous multi-agent systems with specialized, battle-tested capabilities.
Context Mode is an MCP server that dramatically reduces Claude's context window consumption through sandboxed code execution and intelligent full-text search, enabling developers to work with larger codebases and knowledge bases without hitting token limits.
This booster equips AI coding assistants with specialized guidance for reading, creating, and editing Word documents programmatically while maintaining formatting and layout fidelity. Developers working with `.docx` files—especially those requiring professional formatting, tables, or visual validation—will find this booster invaluable.
This booster helps developers efficiently create, edit, and analyze spreadsheets in Python using openpyxl and pandas while preserving formulas and formatting. It's ideal for anyone automating spreadsheet workflows or performing data analysis tasks programmatically.
1. add a ts file to , the plugin api doc is in . 2. Add to to the part.
Automates Outlook Calendar operations like creating events, managing attendees, and scheduling meetings through Rube MCP integration. Useful for developers building agentic systems that need programmatic calendar control.
These instructions are derived from and apply to all AI-assisted contributions to the Zephyr RTOS repository. the file's native comment syntax:
You are an expert Documentation Architect using the Divio documentation system. Before proceeding with any documentation request, take a deep breath and center your focus on technical accuracy and user success. 1. Analyze First: When a user requests documentation, first categorize the request into o
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):
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:
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.
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,
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.
Rules and patterns for ML demos on Hugging Face Spaces with ZeroGPU hardware. Covers , duration and quota tuning, process isolation, the CUDA availability model, concurrency safety, and CUDA build constraints. This skill is for Gradio SDK Spaces using ZeroGPU hardware. Docker and Static Spaces canno
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.
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 :
Branch names should go by the following structure (anything in "{}" brackets is a placeholder). "{short-slug}" should be replaced with a short name that best describes the changes - do ask for confirmation if needed. Make sure each commit addresses an atomic unit of work that independently works. Ma
"name": "understand-anything", "description": "AI-powered codebase understanding — analyze, visualize, and explain any project", "homepage": "https://github.com/Lum1104/Understand-Anything",
This skill automates the process of adding, extracting, and managing evaluation results in Hugging Face model cards, supporting multiple data sources including Artificial Analysis API and custom evaluations with vLLM/lighteval. It's valuable for ML practitioners and model maintainers who need to track and display model performance metrics.
For components requiring Router, ThemeProvider, etc., include them in : Create a test store with for Redux-connected components: Use Mock Service Worker for API mocking:
Enables developers to interact with Hugging Face Hub directly from Claude Code using the `hf` CLI—downloading models/datasets, uploading files, creating repositories, and managing cache without leaving the coding environment.
A comprehensive tutorial for creating, registering, and deploying custom third-party agents that extend UFO² automation capabilities beyond Windows GUI automation. Developers building domain-specific automation agents (hardware control, Linux CLI, web automation, IoT) will find this invaluable for understanding the complete agent architecture and implementation workflow.
"description": "Developer experience essentials: GitHub Actions debugging, conversation cloning/half-cloning, context handoffs, and Reddit research via Gemini CLI", "version": "0.14.12", "email": "yoyoyosss@wearehackerone.com"
