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。
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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。
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。
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessar...
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 designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool ...
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 guidance for building modern Android UIs with Jetpack Compose, covering state management, navigation, performance, and Material Design 3.
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。
Modern Angular UI patterns for loading states, error handling, and data display. Use when building UI components, handling async data, or managing component states.
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 REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing...
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 or design FriendlyBet user experience, visual direction, mobile-first flows, premium sports interface, Hebrew/English copy fit, RTL behavior, accessibility, interaction patterns, and product UI polish. Use when a task touches screens, flows, layout, visual hierarchy, onboarding, prediction UX, share UX, or design quality.
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。
Draft IA shard sections from reconciled ideation and architecture sources, with write-as-you-go section locking
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。
Orchestrate IA shard authoring via design and deepen passes, with pipeline-state-driven shard selection and ambiguity gates
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。
Compile architecture draft into dated architecture design and engineering standards with rubric-complete quality gates
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。
Decompose approved architecture design into IA shards and layered spec structure, then validate dependencies and tracking outputs
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 direction interview methodology — SUPERSEDED. The `impeccable` skill's `/impeccable teach` command now handles design direction discovery with a more comprehensive, multi-round interview that writes PRODUCT.md and DESIGN.md. This file is kept for pipeline backward compatibility — all new design work should use `/impeccable teach` 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。
Master error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications. Use when implementing error handling, designing APIs, or improving application reliability.
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 REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
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 database schemas with normalization, relationships, and constraints. Use when creating new database schemas, designing tables, or planning data models for any database paradigm.
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。
Apply the confirmed design direction to all visual surfaces. This skill now bridges the pipeline's placeholder system with the `impeccable` skill's PRODUCT.md and DESIGN.md files. If `{{DESIGN_DIRECTION}}` still appears as a literal placeholder, run `/impeccable teach` to establish design context.
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。
Universal AI design correction rules — SUPERSEDED. The `impeccable` skill now provides 27 deterministic anti-pattern rules plus a 12-rule LLM critique pass, which are more comprehensive and runtime-enforced via the `impeccable` CLI. This file is kept for backward compatibility — the `impeccable` skill's design laws and anti-patterns take precedence.
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 before any creative work — creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements, and design before implementation.
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。
Optimize a single Jetpack Compose @Composable function. Use when the user wants to improve, polish, animate, or refactor ONE Composable — keywords like "optimize this composable", "make this smoother", "add animation to this", "split this composable", "fix recomposition", "this composable is laggy", "polish this UI", or when user pastes/points to a single @Composable function. Analyzes the target for recomposition issues, missing animations, size/concern splits, and stability problems, then iterates with the user via AskUserQuestion to pick which optimizations to apply, then delegates implementation to the kta-compose-developer agent and summarizes changes. Input MUST be exactly one Composable (file path + function name, or function name alone).
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。
Per-screen design spec generator for AI design tools (Stitch / Figma AI / Claude artifacts). Consumes per-feature PRDs from kta-prd-pipeline. Emits tool-agnostic markdown specs. Triggers — design spec, AI design prompt, screen mockup brief, Figma AI input, Stitch prompt, design system tokens, post-PRD design phase, generate design specs, design brief, mockup spec. DOES NOT generate Compose code, Kotlin code, or @Preview stubs.
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。
End-to-end Android indie idea workflow — feature-build phase only (no monetization). Phased — discover (if no idea) → generate 2 candidates → refine scope (offline/online, sharing, MVP vs full, core-value features) → risk/reward/tradeoff analysis when scoping down → emit idea brief. Use for greenfield app concepts, new feature ideation, idea discovery, or pre-design discovery before writing a design document. Triggers — new app idea, feature concept, indie dev brainstorm, validate idea, refine idea, what should I build, find an app idea, idea pipeline, I have no idea, help me find an app idea, scope down, MVP scoping, core value 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。
Create Kotlin Compose design tokens from one of three supported sources — Google Stitch (MCP), Figma (MCP or JSON), or Claude Design (kta-design-spec output, Claude HTML/markdown artifacts). Three-layer architecture (Primitive/Semantic/Component) with code generation. Use when user asks to "generate design tokens", "create theme from Figma/Stitch/Claude design", "build Compose tokens from design spec", or "convert design source to tokens". Refuses any other input source and asks user for correct seed data.
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 Kotlin Compose design tokens from one of three supported sources — Google Stitch (MCP), Figma (MCP or JSON), or Codex Design (kta-design-spec output, Codex HTML/markdown artifacts). Three-layer architecture (Primitive/Semantic/Component) with code generation. Use when user asks to "generate design tokens", "create theme from Figma/Stitch/Codex design", "build Compose tokens from design spec", or "convert design source to tokens". Refuses any other input source and asks user for correct seed data.
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。