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design

Design component architecture, REST API contracts, and data models (Pydantic schemas) before implementation. Use when planning how to build a feature, defining endpoints, or modeling data. Trigger on "design the architecture", "design the API", "data model", "how should I structure this feature".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(17)

  • SKILL.md4.5 KB
  • api-design-guide.md15.1 KB
  • architecture-patterns.md13.4 KB
  • reference/api-design-guide.md12.1 KB
  • reference/architecture-patterns.md14.7 KB
  • reference/component-design-guide.md15.4 KB
  • reference/data-model-guide.md14.3 KB
  • reference/function-design-patterns.md14.6 KB
  • reference/pydantic-patterns.md20.5 KB
  • reference/schema-examples.py12.3 KB
  • templates/api/patterns.md2.9 KB
  • templates/api/summary.md1.1 KB
  • templates/architecture-doc.md12.6 KB
  • templates/architecture/patterns.md2.6 KB
  • templates/architecture/summary.md1.2 KB
  • templates/data/patterns.md2.8 KB
  • templates/data/summary.md1.2 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Design — Architecture, API & Data Models

Unified design guidance for feature implementation. Auto-detects context from project files or accepts explicit mode.

Usage

/design                    # Auto-detect from project, show summary
/design architecture       # Component architecture, SOLID, patterns
/design api                # REST API design, auth, rate limiting
/design data               # Pydantic schemas, validators, relationships
/design full               # All three in sequence (architecture → data → API)

Workflow

Step 1: Determine Mode

Parse $ARGUMENTS for explicit mode. If no arguments provided, detect context:

DETECTED=$(bash "$HOME/.claude/skills/design/lib/design-detector.sh")

Map detection results to recommended mode:

  • pydantic,fastapi → suggest api + data
  • pydantic only → suggest data
  • fastapi or flask or django → suggest api
  • Generic Python/Node → suggest architecture
  • Unknown → show all summaries, let user choose

Step 2: Show Relevant Guidance

Based on detected or explicit mode, use progressive disclosure:

Level 1 — Summary (default, ~15 lines): Read and present the summary template for the chosen domain:

  • templates/architecture/summary.md
  • templates/api/summary.md
  • templates/data/summary.md

Level 2 — Patterns (on request for more detail, ~50 lines): Read the patterns template with decision guidance and examples:

  • templates/architecture/patterns.md
  • templates/api/patterns.md
  • templates/data/patterns.md

Level 3 — Full Reference (on request for complete SOP): Read the deep reference documents on demand:

  • reference/architecture-patterns.md + reference/component-design-guide.md
  • reference/api-design-guide.md + reference/function-design-patterns.md
  • reference/data-model-guide.md + reference/pydantic-patterns.md

Step 3: Handle Multiple Domains

If context suggests multiple domains (e.g., new feature with API + data):

  • Show summary for each detected domain
  • Let user choose which to dive deeper into
  • Or use /design full for the complete sequence

Step 4: No Context Detected

If detection returns "unknown" and no explicit mode:

  • Show all three summaries as overview
  • List available modes for user to choose

/design full Sequence

When running the full design workflow:

  1. Architecture first: Component boundaries, layers, patterns, DI
  2. Data models second: Pydantic schemas based on architecture components
  3. API contracts third: Endpoints and schemas using data models

Output uses templates/architecture-doc.md as the final document template.

Output

Write documents to docs/architecture/ in the project root:

SubcommandOutput Path
/design architecturedocs/architecture/architecture-{feature}.md
/design apidocs/architecture/api-{feature}.md
/design datadocs/architecture/data-{feature}.md
/design fulldocs/architecture/{feature}.md (combined)

Use templates/architecture-doc.md as the document template with sections:

  • Overview, Architecture Pattern, Component Design, Data Model, API Specification
  • Data Flows, Module Structure, Error Handling, Configuration
  • Testing Strategy, Security Considerations, Performance Considerations

Create docs/architecture/ if it doesn't exist.

Integration

Invoked by: User directly (/design), /story prp workflow (design phase) Invokes: Nothing directly — produces architecture docs consumed by prp-generator Connected skills:

  • /story create → requirements → /design → architecture doc → /story prp → PRP
  • /implementation consumes design output

Progressive Disclosure Rules

  • Never load reference/ docs unless user explicitly asks for full SOP or L3 detail
  • Default to L1 summary — enough to orient and decide
  • L2 patterns when user asks "how", "what pattern", "show me examples"
  • L3 full when user asks for "complete guide", "full reference", or specific deep topic

리뷰

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같은 저장소의 스킬

Validate WCAG 2.1 Level AA compliance and accessibility best practices. Use when performing accessibility audits and WCAG certification.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matteocervelli/llms252026년 5월 22일 업데이트

analysis

무료

Analyze feature requirements, dependencies, and security considerations. Use when starting feature implementation from GitHub issues to understand scope, technical feasibility, and risks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matteocervelli/llms252026년 5월 22일 업데이트

analytics

무료

Run SQL queries against psql, BigQuery, or MySQL from the terminal, including natural-language-to-SQL and schema exploration. Use when analyzing data, inspecting DB state, or debugging tables. Trigger on "query the database", "SQL", "show me data from", "explore table".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matteocervelli/llms252026년 5월 22일 업데이트

Design REST APIs or function contracts with clear request/response specifications, error handling patterns, authentication strategies, and comprehensive documentation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matteocervelli/llms252026년 5월 22일 업데이트

Generate comprehensive API endpoint tests for REST and GraphQL APIs. Creates tests for all HTTP methods, status codes, authentication, and validation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matteocervelli/llms252026년 5월 22일 업데이트

Design component architecture and module structure using established architectural patterns for clean, maintainable, and scalable systems.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matteocervelli/llms252026년 5월 22일 업데이트

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