Loading...
Loading...
Found 1,195 Skills
Searches and retrieves MLflow documentation from the official docs site. Use when the user asks about MLflow features, APIs, integrations (LangGraph, LangChain, OpenAI, etc.), tracing, tracking, or requests to look up MLflow documentation. Triggers on "how do I use MLflow with X", "find MLflow docs for Y", "MLflow API for Z".
Translate PDF documents while preserving original layout, styling, tables, images, and formatting. Supports Simplified Chinese, Traditional Chinese, English, Japanese, Korean, and more. Page-by-page translation with structure preservation.
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra, ru-lite, ru-full, ru-ultra, ru-notes. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Russian mode: "пещерный режим", "режим пещерного", "/caveman ru", "/caveman-ru". Also auto-triggers when token efficiency is requested.
This skill should be used to watch a long-running background job (ffmpeg/media encode, qmd or other embedding/vector-DB run, batch agent/LLM pipeline, or a real-browser/agent-browser daemon) until it finishes or wedges, then deliver a verdict (done, needs-attention, or blocked) plus the exact next command, without burning dozens of manual poll commands. Triggers on "babysit this job", "watch this until it's done", "ping me when the encode/embed/batch finishes", "is this background process stuck", "monitor this ffmpeg/qmd run", or any request to wait on a long-running process and be told when it's complete or hung.
When the user wants to build or improve a sales bot's ability to automatically categorize why deals closed or died. Also use when the user mentions "win/loss analysis," "deal outcome," "loss reason," "closed reason," or "deal categorization."
Recommend and customize Megatron Bridge recipes for a user's model, GPU count, and training goal. Indexes library recipes (pretrain/SFT/PEFT) and performance recipes.
Use when working on the Evaluator plugin CLI, jobs, SDK-backed specs, or plugin-owned Evaluator skills.