Designs and verifies skilld CLI output, terminal pickers, and full-screen flows. Use for terminal colours, loading feedback, keyboard controls, layout, errors, or end-to-end CLI UX reviews.
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
Designs and verifies skilld CLI output, terminal pickers, and full-screen flows. Use for terminal colours, loading feedback, keyboard controls, layout, errors, or end-to-end CLI UX reviews.
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 revise Godot UI from an approved design, separated art, or a visual reference when scene structure, gameplay binding, and runtime visual verification all matter. Use for complete Godot UI integration; use ordinary Godot UI guidance for isolated node or layout questions that do not require an end-to-end visual workflow.
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 screenshot coverage for screen-level Compose previews from the current diff or a specific target, check required visual and data variations, and produce a compact visual report
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。
Main app Jetpack Compose UI patterns (WooTheme, Fragment hosting, composeView/legacyComposeView helpers, preview annotations, WC components). Use when writing, editing, exploring, debugging, or reviewing Compose UI in the store management app. NOT for POS (WooPos*) code — use the `pos` skill 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。
Run the Android AI Assistant headless smoke regression harness without launching UI.
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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
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 build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about AI coding agents, agent runtimes, or similar internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
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 a new Claude Code skill from scratch through a relentless, evidence-based interview that walks the skill's design tree decision-by-decision — entity fit, use cases, name, description, workflow steps, tools, and progressive-disclosure layout — then reviews the finished skill against the plugin-building guidance and applies every fix it finds. Use when creating, authoring, scaffolding, designing, or drafting a new skill or slash command. Does not build an agent or subagent — use agent-builder. Does not serve, vendor, or refresh the authoring guidance itself — use guidance.
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。
Authoritative guidance for building Claude Code skills, agents, and plugins, plus init and update steps that install and refresh the plugin-building skills in the current repository. Use when you need the rules or best practices for a skill, agent, hook, or plugin — designing, reviewing, hardening, or checking one against the guidance. Run with `init` to vendor the guidance, skill-builder, and agent-builder skills into the current repository (so they run with no dependency on this plugin) plus a path-scoped rule index, or `update` to refresh an already-vendored copy. Does not run an interview to build a new skill or agent from scratch — use skill-builder or agent-builder. Does not write feature code, review application code, or build non-plugin features.
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 a new Claude Code agent (subagent) from scratch through a relentless, evidence-based interview that walks the agent's design tree decision-by-decision — entity fit, domain focus and vocabulary, role identity, anti-patterns, description, model tier, tools, and self-containment — then reviews the finished agent against the plugin-building guidance and applies every fix it finds. Use when creating, authoring, scaffolding, designing, or drafting a new agent or subagent. Does not build a skill or slash command — use skill-builder. Does not serve, vendor, or refresh the authoring guidance itself — use guidance.
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, extract, or convert an ADR (architectural decision record) using the ADR template. Use when creating new ADRs, extracting an ADR from existing documentation, converting a document into an ADR, recording an architecture or design decision, or updating the status of an existing ADR. Does not create or update enforceable coding standards or conventions — use coding-standard for that. Does not write feature or system documentation — use project-documentation 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。
Designs the contract for an API change inside one codebase — a component's props, a function surface, URL or query parameters, an event payload, or a module boundary — through a discovery pass, an options document with one recommendation, a question round, and an adversarial validation round, with every element of the contract justified from one stated goal. Use when you want to design, shape, decide, or nail down an interface, contract, signature, or API change for a capability you can already describe, sized for roughly one pull request. Produces a design document and changes no code. Does not specify what a feature should do — use plan-a-feature. Does not plan delivery or sequencing — use plan-implementation. Does not assess the architecture of existing code — use architectural-analysis. Does not write the code — use tdd. Does not restructure existing code — use refactor. Runs its rounds without pausing for review; to review each round as it lands, use pairing.
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 GDPR Article 12 transparent information and communication requirements, covering concise, intelligible, and plain language obligations, response timelines, fee and refusal provisions, and layered notice design. Activate for transparent communication, Art. 12, privacy notice, plain language, response timeline queries.
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 privacy API patterns including data subject API for DSAR endpoints, consent API for preference management, deletion API with cascading delete orchestration, and audit API for compliance reporting. Provides OpenAPI specifications, error handling, rate limiting, and authentication patterns.
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。
Architecture guide for GDPR-compliant federated learning systems. Covers horizontal and vertical FL, aggregation strategies (FedAvg, FedProx), communication efficiency, secure aggregation, and differential privacy integration. Includes privacy guarantees analysis and deployment patterns for cross-organizational ML without data sharing.
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。
Designs and implements privacy notices for children that comply with GDPR Articles 12-14, UK AADC Standard 4, and COPPA Section 312.4. Covers plain language, visual explanations, layered information, age-appropriate vocabulary, and interactive notice elements. Keywords: children privacy notice, transparency, plain language, visual, age-appropriate, layered notice.
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 GDPR Art. 22 automated decision-making and AI Act Art. 14 human oversight requirements for AI systems. Covers identification of solely automated decisions, meaningful human intervention design, logic explanation mechanisms, and contestation procedures. Keywords: Art. 22, automated decision, human oversight, AI Act, profiling, contestation.
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。
Systematic application of the eight privacy design patterns per Hoepman: minimize, hide, separate, abstract, inform, control, enforce, and demonstrate. Covers pattern selection methodology per processing activity, mapping to GDPR principles, and practical implementation guidance for privacy-by-design system architecture.
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。
Guidelines for modern Avalonia UI layout using Zafiro.Avalonia, emphasizing shared styles, generic components, and avoiding XAML redundancy.
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 patterns for building autonomous coding agents, inspired by [Cline](https://github.com/cline/cline) and [OpenAI Codex](https://github.com/openai/codex).
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。
Triage Monte Carlo alerts interactively or build an automated workflow. Fetch, score, and troubleshoot alerts using MCP tools now, or design a reusable workflow that runs on a schedule.
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。
Mandatory skills, conventions, and behavioral rules for Avalonia UI development using the Zafiro toolkit.
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。
Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design.
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。
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
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。