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Structured diagnostic code library for JavaScript/TypeScript. Turns errors and other conditions into typed, machine-readable `Diagnostic` instances with stable codes, docs URLs, and actionable fields. Use this skill whenever the project imports `nostics`, or works with `defineDiagnostics`/`defineProdDiagnostics`, the `Diagnostic` class, diagnostic code registries, or structured error handling. Also covers reporters (`createConsoleReporter`, `createFetchReporter` from nostics/reporters/fetch, `createFileReporter` from nostics/reporters/node, `createDevReporter` from nostics/reporters/dev), formatters (`formatDiagnostic`, `ansiFormatter`, `jsonFormatter`), and Vite plugins (`nosticsStrip` from @nostics/unplugin/strip-transform, `nosticsCollector` from @nostics/unplugin/dev-server-collector). Also use when migrating a library's existing `console.warn`/`console.error`/`warn()` helpers or thrown `Error`s to diagnostics: follow `references/migration.md`.

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 SDK for Python (the `ai` package). Use for Python model calls (LLMs, image, video, speech, embedding, transcription, reranking, or evaluation), agents, model interaction tests, tool calling, subagents, approvals, durable execution, telemetry, AI SDK UI backends, and custom providers.

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 konsistent CLI, review all reported violations, and fix them in the codebase. Use when the user wants to "fix konsistent violations", "resolve konsistent errors", "clean up konsistent diagnostics", "make konsistent pass", "address structural convention violations", or asks to run konsistent and act on the results. The skill is interactive: it requires explicit user decisions when many violations stem from the same rule (rule vs. code question), explicit user confirmation before modifying any code, and a triage step for non-trivial violations. For editing `konsistent.json`, this skill defers to the `konsistent-config` skill.

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。

Create or modify a konsistent.json configuration file that enforces structural conventions in a TypeScript codebase. Use when the user wants to enforce consistent code structure, validate exports/imports across files, ensure directories contain required files, enforce naming patterns, add/remove/update convention rules, configure case map overrides for acronyms or special casing (kebabToPascalMap, kebabToCamelMap), or troubleshoot why konsistent is reporting violations. Triggers on: "konsistent", "konsistent.json", "enforce conventions", "structural consistency", "consistent exports", "consistent structure", "code conventions config", "add convention", "update convention", "fix konsistent errors", "case map", "case override", "acronym casing".

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。

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

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。

Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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, review, and edit developer documentation for SDKs, libraries, and frameworks, including sites such as ai-sdk.dev and chat-sdk.dev. Use for getting-started guides, tutorials, API references, conceptual explanations, integration guides, migration guides, troubleshooting, and code examples.

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。

Give an AI agent GitHub access via @github-tools/sdk. Mount as an eve extension, or use with the AI SDK, TanStack AI, Vercel Workflow, and Chat SDK. Covers tools, presets, approval control, token scoping, and durable agents.

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。

Status-first routing, bounded evidence collection, and safety guidance for issue-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。

Read-only context for issues, pull requests, and backlogs. Use to trace related work, check PR counts, prioritize follow-ups, filter saved captures, open exact dashboard views, replay triage queries, or compare snapshots.

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 optimizing, auditing, or preparing to ship web animations or rendering performance work: frame loops, scroll/viewport reveals, mount/unmount transitions, canvas/WebGL lifecycles, reduced motion, lazy rendering, and deferred off-screen work. Use for jank, per-frame allocations, forced reflows, render loops, animations that do not pause off-screen, content-visibility, requestIdleCallback, analyzing Chrome DevTools performance traces for animation or rendering issues, or choosing between browser-driven CSS/WAAPI, minimal JS, phase, and Motion/GSAP. Use when the user explicitly asks about phase APIs or behavior. Do not use during exploratory animation ideation, prototyping, visual iteration, or trying variants, even when the code already imports phase; wait until the user asks for performance guidance, an audit, production implementation, ship-readiness review, or about phase itself.

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。

Repository-local audit instructions.

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 the trackcn CLI to sync files, directories, commits, pull requests, and agent skills from GitHub into a codebase while preserving local edits. Read this before running trackcn commands or modifying trackcn-managed files.

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。

Shape, implement, review, copy-edit, or harden Arcade user interfaces. Use for the website, terminal UI, game HUDs, interaction flows, responsive behavior, accessibility, Geist consistency, and any change affecting what a user sees, understands, chooses, or does. Skip backend-only, telemetry-only, generated-file, and test-only work with no shipped UI impact.

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 @vercel/error to design, implement, migrate, audit, or review structured TypeScript errors. Trigger when a project uses or adopts the package, or when work involves its codes, fields, factories, HTTP APIs, telemetry, or terminal output. Use native Error for local failures that need no stable identity, recovery guidance, observability, or transport.

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 adding durable execution to AI SDK for Python, building durable agent loops, or serializing messages across workflow steps.

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 connecting AI SDK for Python streams to AI SDK UI useChat clients.

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。

Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn/ui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for "shadcn init", "create an app with --preset", or "switch to --preset".

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 for implementing custom providers in AI SDK for Python.

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 for AI SDK for Python basics. Configure a model, make messages, stream, declare tools, build a basic agent.

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 building custom agent loops. Modify tool dispatch, history management, hooks, control flow.

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 building serverless AI SDK for Python endpoints, handling hook approvals, deferring hooks, or resuming runs across requests.

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 for AI SDK for Python async-generator tools, streaming tool output, subagent tools, PartialToolCallResult events, and custom tool aggregation.

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。