Total 50,962 skills, AI & Machine Learning has 8536 skills
Showing 12 of 8536 skills
Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.
어떤 주제/과제든 받아서 스스로 팀을 구성하고 조사·분석·검토·결과도출까지 처리하는 범용 에이전트 팀 오케스트레이터. "팀으로 분석해줘", "에이전트 팀으로 조사해줘", "다각도로 검토해줘", "심층 분석 부탁해", "여러 관점으로 봐줘", "think-team", "think team" 키워드로 트리거. 단순 질문이 아닌 복합적 판단, 조사, 전략 결정이 필요한 모든 상황에서 사용.
Connect AI coding agents (Claude Code, Cursor, VS Code, OpenAI Codex) to Grafana Cloud via the Model Context Protocol (MCP) server. Use when the user asks to connect Claude Code to Grafana, set up MCP for Grafana, use Grafana tools in Cursor, query Grafana from an AI agent, configure the Grafana MCP server, or make AI agents interact with Grafana Cloud APIs. Triggers on phrases like "MCP server", "connect Claude Code to Grafana", "Grafana MCP", "AI agent Grafana", "Claude Grafana tools", "Cursor Grafana", or "agent observability".
Transync AI platform help — real-time AI meeting translation with near-zero latency (<0.5s) dual-screen bilingual display across 60+ languages, AI voice broadcast, AI meeting notes with summaries, custom domain terminology via AI Assistant, system audio sharing (no bot/plugin) for Zoom/Teams/Meet/WhatsApp. Use when setting up Transync AI for multilingual meetings, Transync AI translation accuracy dropping with accents or technical terms, Transync AI dual-screen display not showing translations, Transync AI meeting notes not generating summaries, choosing between Transync AI Personal Premium vs Enterprise plan, Transync AI time card top-up running out mid-meeting, Transync AI voice broadcast not working, or Transync AI vs JotMe or Talo or Langfinity for real-time meeting translation. Do NOT use for general note-taker comparison across all platforms (use /sales-note-taker) or enterprise RSI with human interpreters (use /sales-kudo or /sales-interprefy).
Coconote platform help — Quizlet's AI note-taker that records lectures and auto-generates study guides, flashcards, quizzes, and AI-narrated podcasts from recordings. Use when setting up Coconote for recording lectures and generating study materials, troubleshooting recordings that crash or fail to save on long lectures, figuring out why Coconote requires payment info before accessing the free plan, choosing between Coconote free and Pro subscription tiers, comparing Coconote to Voicenotes or AudioPen or Cleft Notes for voice capture, evaluating Coconote for student lecture note-taking across iOS and Android, or understanding why Coconote only generates one quiz and one flashcard set per note. Do NOT use for comparing AI meeting note-takers for sales teams (use /sales-note-taker) or reviewing a sales call for coaching (use /sales-call-review).
Control macOS applications with Pi agents using semantic Accessibility API targets and optional screenshots
Read production traces, identify what's failing, and build failure taxonomies using open coding and axial coding methodology. Use when debugging agent or pipeline quality, investigating "why are my outputs bad?", or before building any evaluator — error analysis must come first. Do NOT use when you already have identified failure modes and need evaluators (use build-evaluator) or datasets (use generate-synthetic-dataset).
NVIDIA RAG Blueprint — deploy, configure, troubleshoot, and manage. Handles any RAG action: deploy, install, start, enable, disable, toggle, change, configure, troubleshoot, debug, fix, shutdown, stop, or tear down any RAG feature or service (VLM, guardrails, query rewriting, models, search, ingestion, observability, summarization, and more).
Design, implement, and debug autonomous AI agents and multi-agent systems using the Google Antigravity (AGY) SDK. ACTIVATE this skill when the user wants to create, configure, or orchestrate Google Antigravity agents.
AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.
Resume the most recent agent session for the current working directory. Use when the user says "where were we", "resume", "handoff", "pick up where I left off", or starts a session with no fresh context.
Start Here. Use when the user asks about Narev Cloud, the Pricing API, model pricing (API reference skill vs applied workflows on top of that API), live LLM pricing, token costs, cost calculation, pinning or snapshotting model rates, Narev SDK, @ai-billing/core, provider middleware packages, Vercel AI SDK billing, Next.js App Router route handlers, framework-specific billing patterns, usage-based billing, billing integrations (Polar, Stripe, Lago, OpenMeter), FOCUS format, Narev Self-Hosted (ThinOps), deployment, COGS, customer tagging, FinOps for AI, or this documentation site. Guides you to the right skill or documentation path based on their task.