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概要と使いどころ
Transform an output-focused roadmap (feature list) into an outcome-focused one. Rewrites initiatives as outcome statements reflecting user and business impact. Use when a roadmap lists features instead of results, when making a roadmap more strategic, or when communicating what success looks like vs what will be built.
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。
The definition of done. Run before calling any change done, fixed, verified, ready or shippable, for features and bug fixes alike. Checks the pre-mortem was answered, proves the tests fail on the old code, gets a fresh breaker review, runs CI's own checks in a clean checkout, checks the user-facing words, and writes the evidence report. Also use when asked "is it done", "is it ready", "did you verify it" or "can we merge".
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。
Applies production AI integration patterns for chat, structured output, guardrails, provider routing, and AI UX. Use when adding LLM-powered features to an application.
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。
Builds ML pipelines: EDA, features, leakage checks, evaluation. Use when doing data science or explaining fairness, privacy, speech, vision-language, or diffusion mechanics.
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 implementing PlainTab features or bug fixes with test-first development, red-green-refactor, regression scripts, browser checks, or behavior-focused validation before production code changes.
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。
Map test coverage to GDD critical paths, identify fixed bugs without regression tests, flag coverage drift from new features, and maintain tests/regression-suite.md. Run after implementing a bug fix or before a release gate.
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-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score 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。
Refactoring code: variable naming, function extraction, magic number constants, dead code removal. Does not change behavior. Not for bugs/security (Judge), tests (Radar), or features (Builder).
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。
Quantifying priority by scoring competing items with ICE/RICE/WSJF/MoSCoW/Cost of Delay/Kano. No code. Use to prioritize features/bugs/initiatives or arbitrate Must vs Should at MVP scoping.
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。
Enumerating failure modes via pre-mortem analysis. Systematically identifies failure scenarios for plans, designs, and features, scoring them with RPN/AP. Does not write 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。
Building rapid prototypes for frontend (UI components/pages) and backend (API mocks, simple servers). Use to validate new features or turn ideas into working demos. Working software over perfection.
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。
Implementing production iOS/Android/macOS native features (SwiftUI, Compose) and iterating a screen against a reference design. Not for cross-platform RN/Flutter (Port) or web (Artisan).
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。
Adapt a historical primary source for classroom use — modifying complexity and length while preserving features for sourcing, close reading, and corroboration. Use when a primary source is too complex for the target age group.
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。
Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", and whenever they complain about over-engineering, bloat, boilerplate, or unnecessary dependencies.
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。
Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
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 deprecation and migration. Use when removing old systems, APIs, or features. Use when migrating users from one implementation to another. Use when migrating a database schema in production, such as renaming or dropping a column without downtime (expand/contract). Use when deciding whether to maintain or sunset existing 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。
Validate built features through conversational UAT
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 automated API and end-to-end tests for implemented features. Use when the user says "create qa automated tests for [feature]"
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。
LLMOps Architect: Run LLM features in production: model routing, evals, observability, caching, cost, safety.
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。
Implement bounded features and fixes in existing or new mini-program codebases while preserving repository rules, user-owned changes, approved behavior, assets, framework conventions, and evidence boundaries. Use when users ask to write or modify mini-program code, implement a confirmed specification or architecture, add a scoped feature, remove behavior semantically, update internal documentation required by a change, or carry out a well-defined small fix that does not require root-cause investigation. Establishes a baseline and change boundary, applies test-driven small steps, distinguishes source from generators and build artifacts, verifies the affected contract, and never reports source completion as device validation, formal acceptance, upload, or release.
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 end to end automated tests for existing features. Use when the user says "create qa automated tests for [feature]"
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 this skill when building, debugging, or answering questions about Liveblocks. Liveblocks gives you the building blocks and infrastructure to enable people and AI to work together inside your app, powering realtime collaboration. Liveblocks features include collaboration, rooms, organizations, workspaces, comments, composer, threads, notifications, multiplayer, conflict resolution, realtime presence, avatar stacks, AI collaborators, AI agents, text editors, Tiptap, BlockNote, Lexical, React Flow, Chat SDK. Common components include AiChat, Thread, InboxNotification, Composer, Toolbar (for Lexical Tiptap), FloatingToolbar, FloatingComposer, FloatingThreads, AnchoredThreads. Common hooks include useThreads, useStorage, useMutation, useOthers, useInboxNotifications, useAiChats. Common issues are related to authentication (ID tokens vs access tokens), permissions, room limits, connection errors, user info.
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。
Clone, port, or convert features from any GitHub repo into your project. Use when stealing patterns from external repos or porting proven code. Understand before copy, challenge before implement. 4 modes: port (rewrite), compare (analysis), copy (transplant), improve (copy + optimize).
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 minimal, abstract, UI-inspired illustrations for software product features — as deterministic SVG. Use when asked for a feature illustration, product illustration, spot illustration, empty-state graphic, feature-card artwork, docs or developer-portal illustration, or a consistent illustration set/family for a product. Also use to turn a feature description or a product screenshot into an abstract UI illustration, to add a new illustration to an existing family, or to retheme an existing set.
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。