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These skills only load on macOS systems.", "autonomous-ai-agents": "Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.", "creative": "Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.", "data-science": "Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.", "diagramming": "Diagram creation skills for generating visual diagrams, flowcharts, architecture diagrams, and illustrations using tools like Excalidraw.", "domain": "Passive domain reconnaissance using Python stdlib. Use this skill for subdomain discovery, SSL certificate inspection, WHOIS lookups, DNS records, domain availability checks, and bulk multi-domain analysis. No API keys required. Triggers on requests like \"find subdomains\", \"check ssl cert\", \"whois lookup\", \"is this domain available\", \"bulk check these domains\".", "email": "Skills for sending, receiving, searching, and managing email from the terminal.", "feeds": "Skills for monitoring, aggregating, and processing RSS feeds, blogs, and web content sources.", "gaming": "Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.", "gifs": "Skills for searching, downloading, and working with GIFs and short-form animated media.", "github": "GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.", "mcp": "Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Includes the built-in native MCP client (configure servers in config.yaml for automatic tool discovery) and the mcporter CLI bridge for ad-hoc server interaction.", "media": "Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.", "mlops": "Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models", "mlops/cloud": "GPU cloud providers and serverless compute platforms for ML workloads.", "mlops/evaluation": "Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.", "mlops/inference": "Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.", "mlops/models": "Specific model architectures and tools — computer vision (CLIP, SAM, Stable Diffusion), speech (Whisper), audio generation (AudioCraft), and multimodal models (LLaVA).", "mlops/research": "ML research frameworks for building and optimizing AI systems with declarative programming.", "mlops/training": "Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.", "mlops/vector-databases": "Vector similarity search and embedding databases for RAG, semantic search, and AI application backends.", "note-taking": "Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.", "productivity": "Skills for document creation, presentations, spreadsheets, and other productivity workflows.", "productivity/ocr-and-documents": "Skills for extracting text from PDFs, scanned documents, images, and other file formats using OCR and document parsing tools.", "research": "Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.", "smart-home": "Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.", "social-media": "Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations." } }