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        "requires_tools": []
      }
    },
    {
      "skill_name": "python-debugpy",
      "category": "software-development",
      "frontmatter_name": "python-debugpy",
      "description": "Debug Python: pdb REPL + debugpy remote (DAP).",
      "platforms": [
        "linux",
        "macos"
      ],
      "conditions": {
        "fallback_for_toolsets": [],
        "requires_toolsets": [],
        "fallback_for_tools": [],
        "requires_tools": []
      }
    },
    {
      "skill_name": "requesting-code-review",
      "category": "software-development",
      "frontmatter_name": "requesting-code-review",
      "description": "Pre-commit review: security scan, quality gates, auto-fix.",
      "platforms": [
        "linux",
        "macos",
        "windows"
      ],
      "conditions": {
        "fallback_for_toolsets": [],
        "requires_toolsets": [],
        "fallback_for_tools": [],
        "requires_tools": []
      }
    },
    {
      "skill_name": "spike",
      "category": "software-development",
      "frontmatter_name": "spike",
      "description": "Throwaway experiments to validate an idea before build.",
      "platforms": [
        "linux",
        "macos",
        "windows"
      ],
      "conditions": {
        "fallback_for_toolsets": [],
        "requires_toolsets": [],
        "fallback_for_tools": [],
        "requires_tools": []
      }
    },
    {
      "skill_name": "subagent-driven-development",
      "category": "software-development",
      "frontmatter_name": "subagent-driven-development",
      "description": "Execute plans via delegate_task subagents (2-stage review).",
      "platforms": [
        "linux",
        "macos",
        "windows"
      ],
      "conditions": {
        "fallback_for_toolsets": [],
        "requires_toolsets": [],
        "fallback_for_tools": [],
        "requires_tools": []
      }
    },
    {
      "skill_name": "systematic-debugging",
      "category": "software-development",
      "frontmatter_name": "systematic-debugging",
      "description": "4-phase root cause debugging: understand bugs before fixing.",
      "platforms": [
        "linux",
        "macos",
        "windows"
      ],
      "conditions": {
        "fallback_for_toolsets": [],
        "requires_toolsets": [],
        "fallback_for_tools": [],
        "requires_tools": []
      }
    },
    {
      "skill_name": "test-driven-development",
      "category": "software-development",
      "frontmatter_name": "test-driven-development",
      "description": "TDD: enforce RED-GREEN-REFACTOR, tests before code.",
      "platforms": [
        "linux",
        "macos",
        "windows"
      ],
      "conditions": {
        "fallback_for_toolsets": [],
        "requires_toolsets": [],
        "fallback_for_tools": [],
        "requires_tools": []
      }
    },
    {
      "skill_name": "writing-plans",
      "category": "software-development",
      "frontmatter_name": "writing-plans",
      "description": "Write implementation plans: bite-sized tasks, paths, code.",
      "platforms": [
        "linux",
        "macos",
        "windows"
      ],
      "conditions": {
        "fallback_for_toolsets": [],
        "requires_toolsets": [],
        "fallback_for_tools": [],
        "requires_tools": []
      }
    },
    {
      "skill_name": "yuanbao",
      "category": "yuanbao",
      "frontmatter_name": "yuanbao",
      "description": "Yuanbao (元宝) groups: @mention users, query info/members.",
      "platforms": [
        "linux",
        "macos",
        "windows"
      ],
      "conditions": {
        "fallback_for_toolsets": [],
        "requires_toolsets": [],
        "fallback_for_tools": [],
        "requires_tools": []
      }
    }
  ],
  "category_descriptions": {
    "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.",
    "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. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.",
    "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/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 — image segmentation (Segment Anything / SAM) and audio generation (AudioCraft / MusicGen). Additional model skills (CLIP, Stable Diffusion, Whisper, LLaVA) are available as optional skills.",
    "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."
  }
}