Total 55,498 skills, AI & Machine Learning has 9231 skills
Showing 12 of 9231 skills
Generate high-quality 3D human and humanoid robot motions using Kimodo, a kinematic motion diffusion model controlled via text prompts and kinematic constraints.
AnyGen: AI-powered content creation suite. Create slides/PPT, documents, diagrams, websites, data visualizations, research reports, storybooks, financial analysis, and images. Supports: pitch decks, keynotes, technical docs, PRDs, white papers, architecture diagrams, flowcharts, mind maps, org charts, ER diagrams, sequence diagrams, UML, landing pages, CSV analysis, earnings research, posters, banners, comics, and more. Also trigger when: 做PPT, 写文档, 画流程图, 做网站, 分析数据, 帮我调研, 做绘本, 分析财报, 生成图片, 做海报, 思维导图, 做个架构图, 季度汇报, 竞品调研, 技术方案, 建个落地页, 做个估值, 画个故事.
This skill should be used when the user wants to build an "MCP app", add "interactive UI" or "widgets" to an MCP server, "render components in chat", build "MCP UI resources", make a tool that shows a "form", "picker", "dashboard" or "confirmation dialog" inline in the conversation, or mentions "apps SDK" in the context of MCP. Use AFTER the build-mcp-server skill has settled the deployment model, or when the user already knows they want UI widgets.
Use this skill when crafting, iterating, or optimizing prompts for LLMs including zero-shot, few-shot, chain-of-thought, role prompting, structured output, and prompt chaining. Not for fine-tuning or training models. Not for evaluating model quality across benchmarks.
Critique-and-rewrite enforcement loop for voice fidelity. Validates generated content against negative prompt checklists and forces revision until it passes. Use when content has been generated in a target voice, voice output feels off, long-form content risks voice drift, or before final delivery of voice content. Use for "validate voice", "check voice", "voice feels wrong", "voice drift", or "rewrite for voice". Do NOT use for initial voice generation, voice profile creation, or content that has no voice target.
Collaborative coding with enforced micro-steps: announce, show diff, wait for confirmation, apply, verify. User controls pace with commands. Works with any domain agent as the executor. Use when: "pair program", "pair with me", "let's code together", "step by step coding", "walk me through implementing", "code with me"
Capture a user's real writing voice from 5-20 prior samples, store a local voice.yaml fingerprint, and enforce it on newsjack drafts so AI tells disappear. Measures voice with named stylometry lenses (Burrows's Delta function-word vector, MATTR lexical diversity, sentence-length burstiness, Biber Dimension-1 register, opener-POS profile, punctuation rates) and gates drafts against the fingerprint as bands, not vibes.
Pick Jetson-compatible containers, vLLM runtime images, and Jetson AI Lab PyPI indexes; maps Orin SM 8.7 vs Thor SM 11.0 and JetPack-specific package choices.
What the? Use when the user wants a plain-English breakdown of something technical — the who, what, where, why, and when.
Ultra-compressed communication mode. Cuts output tokens 65% (measured) by speaking like hui while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "hui mode", "talk like hui", "use hui", "less tokens", "be brief", or invokes /hui. Also auto-triggers when token efficiency is requested.
Select available tools based on research tasks, data, and operating environment; works without a preset local research-lab. Use when the user asks for "which tool to use for research tasks", "help me choose research tools", "is this repo useful", or requests the rw-research-lab-router workflow. Runs without a private local workspace or preset research-lab; uses user-provided materials and bundled public-source methods.
AI SDLC evidence-backed retrospective workflow. Use when delivery work is complete or paused and an AI assistant needs to capture observations, connect them to validation or artifact evidence, formulate reviewable process or policy improvement proposals, assign ownership, and preserve the rule that policy changes require an accepted decision. Supports `--quick-flow` for focused learning and `--full-flow` for strict evidence and decision gates.