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Found 1,700 Skills
Writes, reviews, and debugs idiomatic Rust code with memory safety and zero-cost abstractions. Implements ownership patterns, manages lifetimes, designs trait hierarchies, builds async applications with tokio, and structures error handling with Result/Option. Use when building Rust applications, solving ownership or borrowing issues, designing trait-based APIs, implementing async/await concurrency, creating FFI bindings, or optimizing for performance and memory safety. Invoke for Rust, Cargo, ownership, borrowing, lifetimes, async Rust, tokio, zero-cost abstractions, memory safety, systems programming.
Luau architectural patterns: OOP with metatables, inheritance, async (promises, coroutines, pcall), module structure, service pattern, and Roblox-specific idioms.
Clone a ready-to-run Deepgram demo app and start building on top of it. Use whenever someone wants a quick working demo, needs to prototype with Deepgram, or is starting a new project that uses speech-to-text, text-to-speech, voice agents, audio intelligence, or live streaming. Match the user's language, framework, and desired Deepgram feature to the right starter.
Upload a local file to AceData Cloud CDN and get back a public URL. Use whenever you produce a local artifact (image, audio, video, doc) that another API needs as a URL, or that you need to return/persist (e.g. feed a generated image into an image-to-video API, or publish a finished video).
Use when building or editing any AI feature in n8n: AI Agents, Text Classifier, Information Extractor, Sentiment Analysis, Summarization Chain, Basic LLM Chain, embeddings, vector stores, single one-shot LLM calls, or AI media generation (image / audio / video) via the native LangChain provider nodes. Triggers on any `@n8n/n8n-nodes-langchain.*` node, "agent", "chat assistant", "LLM with tools", "tool calling", "fromAi", "system prompt", "memory window", "structured output", "outputParser", "function calling", "RAG", "vector store", "embeddings", "classify with AI", "extract fields with LLM", "sentiment analysis", "summarize with LLM", "single LLM call", chat triggers with files, AI image / video / audio generation, or any multi-turn or one-shot LLM behavior.
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.
Vue.js 3 best practices guidelines covering Composition API, component design, reactivity patterns, Tailwind CSS utility-first styling, PrimeVue component library integration, and code organization. This skill should be used when writing, reviewing, or refactoring Vue.js code to ensure idiomatic patterns and maintainable code.
ElevenLabs TTS integration for video narration. Use when generating voiceover audio, selecting voices, or building script-to-audio pipelines
Use when asking "code like [expert]", "what would [expert] say", "idiomatic", "best practice", "panel", "debate", or needing domain guidance. Triggers on expert names, style requests, tradeoff questions, or "stuck on".
Extract YouTube video transcripts with metadata and save as Markdown to Obsidian vault. Use this skill when the user requests downloading YouTube transcripts, converting YouTube videos to text, or extracting video subtitles. Does not download video/audio files, only metadata and subtitles.
Implements media and file management components including file upload (drag-drop, multi-file, resumable), image galleries (lightbox, carousel, masonry), video players (custom controls, captions, adaptive streaming), audio players (waveform, playlists), document viewers (PDF, Office), and optimization strategies (compression, responsive images, lazy loading, CDN). Use when handling files, displaying media, or building rich content experiences.
Idiomatic Go 1.25+ development. Use when writing Go code, designing APIs, discussing Go patterns, or reviewing Go implementations. Emphasizes stdlib, concrete types, simple error handling, and minimal dependencies.