Use for full system-state snapshot + diff + HTTP:8898.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Use for full system-state snapshot + diff + HTTP:8898.
日本語の概要は準備中です。原文の説明を表示しています。
Generate docs from live git+skills+cron state.
日本語の概要は準備中です。原文の説明を表示しています。
Training Details of the Second RL Stage 4 Experiment 5 Ethics and Safety Statement 6 Conclusion, Limitation, and Future Work 7 Author List A Backgroun
日本語の概要は準備中です。原文の説明を表示しています。
An advanced agent for de novo antibody design and optimization using state-of-the-art protein language models (MAGE, RFdiffusion).
日本語の概要は準備中です。原文の説明を表示しています。
Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.
日本語の概要は準備中です。原文の説明を表示しています。
Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.
日本語の概要は準備中です。原文の説明を表示しています。
Guide for implementing smooth, native-feeling animations using React's View Transition API (`<ViewTransition>` component, `addTransitionType`, and CSS view transition pseudo-elements). Use this skill whenever the user wants to add page transitions, animate route changes, create shared element animations, animate enter/exit of components, animate list reorder, implement directional (forward/back) navigation animations, or integrate view transitions in Next.js. Also use when the user mentions view transitions, `startViewTransition`, `ViewTransition`, transition types, or asks about animating between UI states in React without third-party animation libraries.
日本語の概要は準備中です。原文の説明を表示しています。
Store and retrieve unstructured objects, file uploads, and cache-like state on Netlify using the @netlify/blobs key/value API from Functions, Edge Functions, and Build Plugins. Use when a task involves saving user file or image uploads, persisting form or contact-form submissions, storing generated output from Background Functions (sitemaps/processed media/bulk-email results), building read-only asset stores, adding client-side blob expiration, or wiring file-based blob uploads at deploy time. Not for per-user, transactional, or relational data (counters/balances/sessions) — reach for Netlify DB there instead.
日本語の概要は準備中です。原文の説明を表示しています。
Build a throwaway prototype to answer a design question. Use when the user wants to sanity-check whether a state model or logic feels right, or explore what a UI should look like.
日本語の概要は準備中です。原文の説明を表示しています。
Build or update a professional-grade design system in Figma from a codebase. Use when the user wants to create variables/tokens, build component libraries, create individual components with proper variant sets and variable bindings, set up theming (light/dark modes), document foundations, or reconcile gaps between code and Figma. Also use when the user asks to create or generate any component in Figma — even a single one — since components require proper variable foundations, variant states, and design token bindings to be production-quality. This skill teaches WHAT to build and in WHAT ORDER — it complements the `figma-use` skill which teaches HOW to call the Plugin API. Both skills should be loaded together.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
Design and implement context-fit frontend interfaces with deliberate art direction, accessible interaction, responsive behavior, complete states, and rendered verification. Use when creating or substantially reworking pages, components, product workspaces, dashboards, marketing sites, editorial surfaces, commerce flows, or justified immersive experiences.
日本語の概要は準備中です。原文の説明を表示しています。
Drive the Codex in-app browser (open, navigate, click, type, screenshot, read page state) through the app's own node_repl runtime. Use when the session uses a custom (non-OpenAI) model, for example deepseek-v4-flash or mimo-v2.5, and the user asks to use the in-app browser, open or navigate a page in it, test a local app in a browser, or click, type, or take a screenshot in the Codex browser panel.
日本語の概要は準備中です。原文の説明を表示しています。
Consistent radii, pixel-perfect alignment, state coverage, and the details that signal design quality. Use when polishing designs, auditing quality, or evaluating whether a design is ready to ship.
日本語の概要は準備中です。原文の説明を表示しています。
Micro-decision analysis. Catalog the border radii, spacing scales, type sizes, and state coverage that most people miss. Use when auditing design systems, evaluating craft quality, or training granular perception.
日本語の概要は準備中です。原文の説明を表示しています。
Develops an implementation plan ready for wave-orchestration to execute. Takes the user's goal or rough plan as input, mines the codebase for facts, grills the user one question at a time for the decisions, drafts the planning/ artifacts (task DAG, wave table, worker prompt template, state file), then reviews its own plan on two axes before seeking approval. Use when the user wants to turn a feature idea, master plan, or backlog into a wave-orchestration execution plan.
日本語の概要は準備中です。原文の説明を表示しています。
Decomposes a large implementation plan into small-model-sized tasks executed by supervised worker agents (e.g. Haiku) in dependency-ordered parallel waves, with a plan-first approval gate inside every task, file-based state for context compaction, and a hard escalation ladder. Use when a master plan or multi-workstream feature is too large for one session and should be executed cheaply by many small agents under frontier-model supervision.
日本語の概要は準備中です。原文の説明を表示しています。
Solves UI lock-in. Reverse engineers your existing UI, strips all layout/token decisions, preserves every hook, handler, and API call untouched, then rebuilds the UI from scratch with a fresh design system. Use /ui-restructure to fully redesign, --style apple|linear|minimal|dashboard for named styles, --mode layout|theme|grid for partial rebuilds, --god-mode to redesign from the user's perspective using 100-user mindset simulation and 6 UX principles, --keep-tokens to preserve your token system, --prompt for custom redesigns. Applies mandatory world-class polish: spring motion, 5-state micro-interactions, 8pt spacing grid, WCAG accessibility. Supports Next.js, React, Vue 3, Tailwind, CSS Modules, styled-components, shadcn.
日本語の概要は準備中です。原文の説明を表示しています。
Run the startcycle-graph pipeline: durable state, repair loop, quality gate, escalation. Generated from plugin-commands.json; invoke as $bdb-aos:graph.
日本語の概要は準備中です。原文の説明を表示しています。
Write a handover note for a colleague from the state of a project folder: what is done, what is open, what is risky, the next 3 steps and where things live. Sent only after your GO. Use for "handover note", "hand this project over", "I'm going on leave, brief my colleague".
日本語の概要は準備中です。原文の説明を表示しています。
Expert in TanStack Query (React Query) — asynchronous state management. Covers data fetching, stale time configuration, mutations, optimistic updates, and Next.js App Router (SSR) integration.
日本語の概要は準備中です。原文の説明を表示しています。
Move issues and external PRs through a state machine of triage roles, categorise, verify, and write agent-ready briefs.
日本語の概要は準備中です。原文の説明を表示しています。
Use when facing 2+ independent tasks — "in parallel", "independent tasks", "multiple unrelated failures", "different test files or subsystems" — that can be worked on without shared state or sequential dependencies. Dispatch one agent per independent slice, each with only the context it needs, even when the user did not ask for subagents explicitly.
日本語の概要は準備中です。原文の説明を表示しています。