repomix
Package entire code repositories into single, AI-optimized files. Ideal for providing codebase context to LLMs like Claude, ChatGPT, and Gemini for analysis, security audits, and bug investigations.
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540 skills found
Package entire code repositories into single, AI-optimized files. Ideal for providing codebase context to LLMs like Claude, ChatGPT, and Gemini for analysis, security audits, and bug investigations.
Neuropixels neural recording analysis toolkit. Provides end-to-end pipelines for SpikeGLX/OpenEphys data, Kilosort4 spike sorting, motion correction, quality metrics, and AI-assisted curation.
AI-driven GitHub project management using swarm coordination, automated issue triage, project board synchronization, and intelligent task decomposition for efficient development workflows.
Build no-code MCP servers that orchestrate tools as directed graphs using YAML for data transformation, conditional routing, and automated workflows.
Programmatically manage OmniFocus tasks and projects. Supports creation, querying, updates, and completion tracking across all OmniFocus versions using native automation and fallback methods.
Private skill distribution system for managing agentics across devices and teams. Install, sync, add, and update your agents, skills, and prompts via a central library catalog.
Official documentation skill for Shipany, an AI-powered SaaS boilerplate. Provides expert guidance on Next.js 15, Drizzle ORM, NextAuth, and payment integrations.
A comprehensive aphorism and quote management system for thematic content enrichment, research, and newsletter curation.
Analyze YouTube videos with automated transcript extraction, AI-powered summarization, Korean translation, and interactive multi-level comprehension quizzes.
Skill for managing MCP-based research, documentation lookups, and coordination between external search tools and plugin-backed memory systems.
Interactive guide for workspace discovery, providing access to specialist agents, automated workflows, CLI tools, and active lifecycle hooks.
Aggressively prune grammatical scaffolding and filler text from inputs to optimize LLM token usage while retaining core semantic content.