inno-prepare-resources
Automates research resource preparation by loading instances, searching GitHub for codebases, building dataset descriptions, and downloading arXiv papers.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
429 skills found
Automates research resource preparation by loading instances, searching GitHub for codebases, building dataset descriptions, and downloading arXiv papers.
Generate and edit images using Google's Nano Banana 2 via WaveSpeed AI. Supports text-to-image, natural language editing, multi-image composition, 4K resolution, and various aspect ratios.
A command-line tool and Expo module for interacting with Apple HealthKit, allowing you to seed, query, and verify health data in development.
The foundational skill for the Superpowers methodology. Ensures agents correctly identify and invoke required development skills before starting any task or conversation.
A powerful CLI tool to automate and manage Google Workspace services, including Gmail, Calendar, Drive, Sheets, and Docs.
Master component-driven development for React, Vue, and Svelte. Learn advanced composition, CSS-in-JS strategies, and API design for scalable UI design systems.
A collection of design patterns for the Langroid multi-agent framework, covering agent configuration, tool handling, task orchestration, and external integrations.
Manages complete plugin lifecycle for JUCE development: install, uninstall, reset, and destroy. Handles system folder deployment, cache management, and safe, version-controlled removal for audio developers.
Pre-execution security guardrails for AI agents. Validates shell commands and file reads against 400+ security patterns to block destructive operations, credential theft, and unauthorized system access.
Easily configure and add Model Context Protocol (MCP) servers to various AI coding clients like Cursor, Claude, VS Code, and more using an interactive or automated command-line interface.
Foundational mental model and operational rules for using TraceMem to ensure secure, auditable, and compliant AI agent execution.
Enable long-running, multi-session autonomous development tasks with state tracking, resumable execution, and dual-agent planning-execution workflows.