Provides guided design frameworks for system architecture, API definitions, and data models prior to coding.
Install
mkdir -p .claude/skills/design-matteocervelli && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/15447" && unzip -o skill.zip -d .claude/skills/design-matteocervelli && rm skill.zipInstalls to .claude/skills/design-matteocervelli
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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".Key capabilities
- →Design component architecture.
- →Design REST API contracts.
- →Design data models using Pydantic schemas.
- →Auto-detect context from project files.
- →Provide progressive disclosure of design guidance.
How it works
The skill determines the design mode (architecture, API, or data) from arguments or project context, then provides guidance and writes design documents using templates. It follows a sequence for full design workflows: architecture, then data models, then API contracts.
Inputs & outputs
When to use design
- →Design API architecture
- →Model data schemas
- →Structure new feature
- →Design REST endpoints
About this skill
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→ suggestapi+datapydanticonly → suggestdatafastapiorflaskordjango→ suggestapi- 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.mdtemplates/api/summary.mdtemplates/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.mdtemplates/api/patterns.mdtemplates/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.mdreference/api-design-guide.md+reference/function-design-patterns.mdreference/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 fullfor 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:
- Architecture first: Component boundaries, layers, patterns, DI
- Data models second: Pydantic schemas based on architecture components
- 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:
| Subcommand | Output Path |
|---|---|
/design architecture | docs/architecture/architecture-{feature}.md |
/design api | docs/architecture/api-{feature}.md |
/design data | docs/architecture/data-{feature}.md |
/design full | docs/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/implementationconsumes 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
When not to use it
- →When the user needs implementation rather than design.
- →When the user does not want design documents written to `docs/architecture/`.
- →When the user explicitly asks for full reference documents without progressive disclosure.
Limitations
- →Does not directly invoke other tools for implementation.
- →Requires user input for mode selection if context is unknown.
- →Output documents are written to a specific `docs/architecture/` path.
How it compares
This skill offers structured, context-aware design guidance and document generation, which is more systematic than ad-hoc design processes.
Compared to similar skills
design side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| design (this skill) | 0 | 2mo | Review | Intermediate |
| backend-architect | 10 | 4mo | No flags | Advanced |
| python-pro | 0 | 2mo | No flags | Intermediate |
| fastapi-templates | 520 | 2mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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