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Render the beat table into alpha overlays. Use at the graphics stage after gate 3, or when the user says "build the graphics" or "render the overlays".

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Distill an already-built or near-launch product into one incisive brand kernel — the "reveal" already hiding in its name, story, or the product itself — then build the name, voice, visual identity, and a developer-ready handoff kit around it. This is LATE-STAGE branding: use it when there is a real, thought-through product that is about to launch, or already live but not explained in a way people grasp in an instant. Use whenever the user wants to name or rename a product, find a tagline or slogan, create a brand identity / brand kit / style guide / design system, design a logo, wordmark, palette, or type system, mock up a homepage for a launch, or hand brand assets to a coding agent (Claude Code, Codex, Cursor). Trigger even when the user only says their product needs to "land" or "feel like" something, or that they can't explain it simply yet. Do NOT use for half-baked, pre-product ideas with nothing to excavate — this skill extracts a kernel that already exists; it does not invent one from a blank canvas.

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Autonomously improve an MCP skill via the skillit audit→draft→review loop (build or runtime mode) Also: skillit, refine, mcp, skill-generation, cli, audit, overlay.

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Bootstrap an AI-agent skill from a TypeScript codebase by running the deterministic skillit generate/audit loop and enriching repo source (JSDoc, README, config-type properties, MCP tool annotations, examples, package.json) until the skill reaches its grade target. Use for cli, typedoc, config, or mcp (build-mode) projects; never edit SKILL.md/references directly.

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Create an Estuary derivation with custom SQLite state (internal tables) to make per-document decisions based on accumulated history — account balances, inventory levels, approval workflows, deduplication. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this. Use when user says "stateful derivation", "derivation to track balance", "transformation to approve based on state", "derive an approval workflow", "deduplication derivation", or "build a stateful derivation".

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Implements responsive and adaptive layouts in Flutter using flutter_screenutil v5.9.x (pixel-perfect scaling from Figma), sizer v3.1.x (percentage-based viewport), and responsive_framework v1.1.x (breakpoint-driven structure changes). Use this skill when building apps for multiple screen sizes (phones, tablets, foldables, desktop, web), fixing layout overflow or sizing issues, implementing breakpoint-based adaptive UI, creating pixel-perfect designs from Figma specs, handling orientation changes, supporting Flutter web or desktop responsive layouts, or any time the words 'responsive', 'screenutil', 'sizer', 'breakpoint', 'adaptive layout', or 'screen size' appear in the request. Includes a decision matrix for selecting the correct package per scenario.

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State management architecture for Flutter using Riverpod, Provider, and BLoC patterns. Use when choosing a state solution, implementing reactive state, resolving rebuild issues, or structuring MVVM/BLoC architecture.

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Automates Flutter iOS and Android deployment using Fastlane. Use when setting up `fastlane match` for iOS certificate and provisioning profile management, automating TestFlight uploads via `upload_to_testflight`, pushing Android releases to Google Play via `upload_to_play_store`, auto-incrementing build numbers, writing Fastfile lanes for Flutter release workflows, integrating Fastlane with GitHub Actions or Codemagic, or configuring App Store Connect API Key and Google Play Service Account JSON credentials.

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Generates immutable Dart data classes, sealed union types, and deep copyWith using Freezed (v3.2.x) with optional json_serializable integration. Use when creating DTOs, API response models, app state classes, or any model requiring immutability, pattern matching, or JSON serialization. Activates on: @freezed annotation, freezed_annotation import, immutable data class request, copyWith deep nesting, union/sealed types for loading/data/error states, generic response wrappers, or build_runner code generation for models.

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Develops full-stack Dart backends using the Serverpod framework with PostgreSQL, Redis, and Docker. Use when building type-safe API endpoints, defining YAML data models, configuring Serverpod auth, writing server-side tests, running database migrations, deploying to Docker/AWS/GCP, or using Serverpod Mini for database-less BFF proxy endpoints.

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Supabase Flutter integration for PostgreSQL, Auth, Realtime subscriptions, Storage, Edge Functions, and Row Level Security. Use when building backend features with supabase_flutter or configuring database policies.

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Reads an OpenAPI 3.0 specification and manually implements a type-safe Dart API layer using Dio for HTTP, Freezed or Equatable for models, and json_serializable for serialisation. Use when given an OpenAPI/Swagger file (JSON or YAML) and asked to implement the API in Flutter/Dart, create Dart models from an API schema, build a Dio API client, implement endpoints from a spec, convert openapi to dart, or set up a data/network layer from an API contract. Handles $ref resolution, oneOf union types, enums, query params, request bodies, and DioException error mapping.

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Configures Codemagic CI/CD pipelines for Flutter using `codemagic.yaml`. Use when setting up automated Flutter builds on Codemagic, configuring iOS code signing without Fastlane Match, deploying to App Store Connect or Google Play from Codemagic, caching pub dependencies in Codemagic, setting up encrypted environment variable groups, running tests with Codemagic's test dashboard, or choosing between Codemagic and GitHub Actions + Fastlane for a Flutter CI/CD pipeline.

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Implements Riverpod (v3.3.x) compile-safe state management for Flutter apps. Use when implementing @riverpod code generation providers, handling AsyncValue loading/error/data states, using ref.watch/ref.read/ref.listen, setting up ProviderScope, writing Notifier/AsyncNotifier classes, using FutureProvider/StreamProvider, applying autoDispose and family modifiers, combining providers, testing providers in isolation, scoping rebuilds with Consumer instead of ConsumerWidget, using ref.watch with select() for field-level precision, migrating from StateNotifierProvider or Riverpod 2.x patterns, handling Notifier resource lifecycle with ref.onDispose, or using experimental Mutation and offline persistence APIs.

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Implements BLoC (v9.x) event-driven state management for Flutter with unidirectional data flow using the flutter_bloc package. Use when implementing Bloc/Cubit classes, mapping Events to States, consuming state with BlocBuilder/BlocListener/BlocConsumer, applying event transformers (restartable/droppable/sequential) for concurrency control, setting up BlocProvider/MultiBlocProvider DI, integrating Freezed for sealed union types and exhaustive pattern matching, or testing with blocTest. Ideal for enterprise apps requiring business logic separation, precise concurrency control (search debouncing, form deduplication), or event replay debugging.

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。

Implements data visualization charts in Flutter using the fl_chart package (v1.2.0). Supports LineChart, BarChart, PieChart, ScatterChart, RadarChart, and CandlestickChart with implicit animations, touch interactivity, and pan/zoom transformations. Use when building any Flutter chart, graph, or data visualization — including line graphs for trends, bar charts for comparisons, pie/donut charts for proportions, scatter plots for distributions, radar charts for multi-axis comparisons, or candlestick charts for financial OHLC data. Also use when customizing chart axes, titles, tooltips, grid lines, touch callbacks, chart animations, or chart zoom/pan behavior.

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。

Generative UI (GenUI) for Flutter using AI models like Google Gemini, Anthropic Claude, or OpenAI via the genui package. Use this skill when building dynamic AI-driven interfaces, conversational UI flows, server-rendered screen layouts, LLM-powered dashboards, chat-based UI generation, or implementing prompt-to-UI systems. Supports AI-generated widgets, reactive data binding, ContentGenerator integration, and A2uiMessageProcessor for real-time UI updates from AI responses. Ideal for apps where UI structure is determined by AI/LLM output rather than hardcoded layouts.

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。

Implements declarative Flutter routing using GoRouter v17 with URL-based navigation, deep linking, and authentication guards. Activates when configuring GoRoute path patterns, setting up StatefulShellRoute for persistent bottom navigation state, implementing ShellRoute for shared nested layouts, adding redirect guards with loop prevention (idempotent redirects), configuring deep links for iOS (FlutterDeepLinkingEnabled) or Android (intent-filters), debugging redirect loops or navigation stack issues, handling 404 error routes with errorBuilder, using named routes with path/query/extra parameters, or migrating from imperative Navigator.push to declarative routing. Ideal for Flutter web apps requiring URL bar synchronization, mobile apps with universal links or app links, or multi-level navigation hierarchies.

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。

Implements type-safe reactive SQL persistence in Flutter using Drift v2.32 (formerly Moor) built on SQLite with automatic code generation. Activates when defining table schemas with Drift DSL, writing type-safe join or subquery operations, handling schema migrations with MigrationStrategy, using reactive watch() streams for live UI updates, implementing ACID transactions, defining foreign key constraints or cascade deletes, enabling WAL mode for write performance, troubleshooting generated .g.dart type mismatches, migrating from sqflite or sqlite3 v2 to v3, using DAOs for query separation, or building offline-first apps requiring strong relational data integrity and compile-time SQL verification.

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。

Declarative animation patterns using flutter_animate v4.5.x with composable effects (fade, scale, slide, shimmer, shake, blur), GLSL fragment shaders, and scroll-synchronized animations. Use this skill for adding UI animations and transitions, building staggered or sequenced effects, creating custom animation effects, fixing animation jank or performance issues, implementing shimmer loading states, or adding scroll-driven animations. Supports delays, curves, adaptive effects, and easy extension method chaining (.animate()).

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。

Implements type-safe Flutter routing using AutoRoute v11 with code generation and @RoutePage annotations. Activates when setting up AutoRoute navigation, configuring AutoRouterConfig or RootStackRouter, generating route files with build_runner, using @RoutePage, @PathParam, or @QueryParam annotations, implementing AutoTabsRouter for bottom navigation tabs, adding navigation guards with AutoRouteGuard, setting up nested or child routes, handling type-safe route parameters, or migrating from string-based Navigator routing to compile-time-verified routes. Ideal for large apps requiring refactoring confidence and zero string-based routing errors.

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 review GitHub Actions workflows for BIRD 2/3 projects using bird-chinese-community/setup-birdcc and @birdcc/cli. Use for pull-request lint/format/parse checks, BIRD2/BIRD3 matrices, BIRD_BIN, changed config files, pnpm/Turbo caching, submodule configs, action pinning, or .github/workflows changes. Route local config work to bird-agent and local editor/CLI installation to birdcc-installer.

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。

사회복지 기관(복지관, 생활시설, 센터, 비영리단체)의 실무자가 업무용 앱을 만들거나, 업무를 자동화하거나, 엑셀·양식을 전산화하고 싶다고 할 때 코드를 만들기 전에 업무의 필요성, 개인정보 등급, 사람에 관한 기록의 윤리, 플랫폼 경로, 운영 조건을 판단하고 DECISION.md로 정리하는 절차. "프로그램일지 앱", "이용자 명부", "출석 체크", "사례관리 기록", "후원자 관리", "차량 운행일지", "복지 앱", "바이브코딩", "희망이음 자동 입력", "에이전트 브라우저로 동기화" 같은 말이 나오거나 사회복지 현장의 행정 업무를 자동화하려 할 때 사용한다. Use before writing any code when a Korean social-welfare practitioner wants to build an app or automate a workflow. Not for general coding tasks.

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。

Inspect, debug, and inject custom code into a running Steam client — desktop (macOS, Linux, Windows) or Steam Deck over the network — through its Chromium Embedded Framework (CEF) Chrome DevTools Protocol endpoint. Use when developing Steam UI plugins, mods, themes, or integrations — injecting CSS/JS to try a change, locating webpack modules and obfuscated class names, reading React or SteamUIStore state, inspecting Big Picture / Quick Access Menu windows, screenshotting what actually rendered, streaming console logs, or diagnosing runtime errors in Steam's UI. The same commands run against either device, or both at once. Injection is per-session and for development only. Not for building a plugin loader or making changes persist across restarts, Steamworks game SDK work, game development, or scraping the public Steam web store.

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。