Architecture Aware Init

name: architecture-aware-init description: |

Triggers: decision-making, research, aware, architecture, initialization Architecture-aware project initialization combining online research with archetype selection.

Triggers: project initialization, new project, architecture decision, project setup, which architecture, choose architecture, project architecture

Use when: initializing a new project and need to select an appropriate architecture based on project type, team size, domain complexity, and current best practices

DO NOT use when: architecture is already decided - use project-init instead. DO NOT use when: exploring multiple architectures - use architecture-paradigms instead. version: 1.0.0 category: project-initialization tags: [architecture, initialization, research, decision-making, best-practices] dependencies: [architecture-paradigms] tools: [web-search, paradigm-matcher, template-advisor] usage_patterns: - new-project-setup - architecture-selection - best-practices-research - template-customization complexity: advanced estimated_tokens: 1800

Table of Contents

• Overview
• When to Use This Skill
• Required TodoWrite Items
• 5-Step Workflow
• Step 1: Gather Project Context
• Step 2: Research Best Practices (arch-init:research-completed)
• Step 3: Select Architecture Paradigm (arch-init:paradigm-selected)
• Step 4: Customize Templates (arch-init:templates-customized)
• Step 5: Create Architecture Decision Record (arch-init:decision-recorded)
• Date
• Status
• Context
• Decision
• Rationale
• Research Findings
• Key Considerations
• Alternatives Considered
• Consequences
• Positive
• Negative
• Implementation
• References
• Output: Complete Initialization Package
• Script Integration
• Architecture Research
• Template Customization
• Full Interactive Flow
• Using as Library (within Claude Code)
• Integration with Existing Commands
• Example Session
• Related Skills
• See Also

Architecture-Aware Project Initialization

Overview

Enhanced project initialization that combines:

• Deep online research into current best practices for your project type
• Archetype selection from the 14 paradigms in the archetypes plugin
• Template customization based on chosen architecture
• Decision documentation for future reference

When to Use This Skill

Use this skill when:

• Starting a new project and unsure which architecture fits best
• Want modern, industry-standard architecture choices
• Need justification for architectural decisions
• Want templates customized to your chosen paradigm

Use instead of project-init when architecture is undecided. Use before project-specification to establish architectural foundation.

Required TodoWrite Items

1. arch-init:research-completed - Online research completed
2. arch-init:paradigm-selected - Architecture paradigm chosen
3. arch-init:templates-customized - Templates adapted to paradigm
4. arch-init:decision-recorded - ADR created

5-Step Workflow

Step 1: Gather Project Context

Essential Information (ask user):

1. **Project Type**: What are you building?
   - Web API, CLI tool, data pipeline, desktop app, library, etc.

2. **Domain Complexity**: How complex are the business rules?
   - Simple (CRUD), Moderate (some business logic), Complex (many rules),
     Highly Complex (domain-specific language needed)

3. **Team Context**: Who will build and maintain this?
   - Team size: < 5 | 5-15 | 15-50 | 50+
   - Experience: Junior | Mixed | Senior | Expert
   - Distribution: Co-located | Remote | Distributed

4. **Non-Functional Requirements**:
   - Scalability needs (users, requests/sec, data volume)
   - Performance requirements
   - Security/compliance needs
   - Integration points (external systems, databases, APIs)

5. **Timeline & Constraints**:
   - Time to market: Rapid | Normal | Not urgent
   - Budget constraints
   - Technology constraints (must-use or must-avoid technologies)

Verification: Run the command with --help flag to verify availability.

Step 2: Research Best Practices (arch-init:research-completed)

Online Research Queries (use WebSearch):

For the project type, search for:

# Primary: Architecture patterns for [project type] [year]
WebSearch("[project type] architecture best practices 2026")

# Secondary: Language-specific patterns
WebSearch("[language] [project type] architecture patterns 2026")

# Tertiary: Framework-specific guidance
WebSearch("[framework] architecture patterns [project type]")

Verification: Run the command with --help flag to verify availability.

Research Focus Areas:

1. Current Industry Standards: What are practitioners recommending in 2026?
2. Emerging Patterns: Any new architectural approaches gaining traction?
3. Anti-Patterns: What practices are being actively discouraged?
4. Technology Alignment: Which patterns work best with your chosen stack?
5. Case Studies: Real-world examples of similar projects

Synthesize Findings into:

• Recommended architecture(s) for this project type
• Key trade-offs to consider
• Red flags or anti-patterns to avoid
• Technology-specific considerations

Step 3: Select Architecture Paradigm (arch-init:paradigm-selected)

Option A: Manual Selection Using archetypes Plugin

Invoke the architecture paradigms skill:

**Verification:** Run the command with `--help` flag to verify availability.
Skill(architecture-paradigms)

Verification: Run the command with --help flag to verify availability.

This will guide you through selecting from the 14 available paradigms:

• Layered Architecture
• Functional Core, Imperative Shell
• Hexagonal (Ports & Adapters)
• Modular Monolith
• Microservices
• Service-Based Architecture
• Event-Driven Architecture
• CQRS + Event Sourcing
• Serverless
• Space-Based Architecture
• Pipeline Architecture
• Microkernel Architecture
• Client-Server Architecture

Option B: Automated Paradigm Matching

Use the decision matrix below to recommend a paradigm based on project context:

**Verification:** Run the command with `--help` flag to verify availability.
┌─────────────────────┬─────────┬─────────┬──────────┬─────────────┐
│ Project Context     │ Simple  │ Moderate│ Complex  │ Highly      │
│                     │ Domain  │ Domain  │ Domain   │ Complex     │
├─────────────────────┼─────────┼─────────┼──────────┼─────────────┤
│ < 5 engineers       │ Layered │ Layered │ Hexagonal│ Functional  │
│                     │         │ Hexag. │ Functional│ Core        │
├─────────────────────┼─────────┼─────────┼──────────┼─────────────┤
│ 5-15 engineers      │ Layered │ Modular │ Modular  │ Hexagonal   │
│                     │         │ Monolith│ Monolith │ + FC, IS    │
├─────────────────────┼─────────┼─────────┼──────────┼─────────────┤
│ 15-50 engineers     │ Modular │ Micro-  │ Micro-   │ CQRS/ES     │
│                     │ Monolith│ services│ services │ + Event     │
├─────────────────────┼─────────┼─────────┼──────────┼─────────────┤
│ 50+ engineers       │ Micro-  │ Micro-  │ Event-   │ Microkernel │
│                     │ services│ services│ Driven   │ or Space-   │
│                     │         │ + Event │          │ Based       │
└─────────────────────┴─────────┴─────────┴──────────┴─────────────┘

Verification: Run the command with --help flag to verify availability.

Special Cases:

• Real-time/Streaming: Event-Driven + Pipeline
• Bursty/Cloud-Native: Serverless
• Extensible Platform: Microkernel
• Data Processing: Pipeline + Event-Driven
• Legacy Integration: Hexagonal
• High-Throughput Stateful: Space-Based

Step 4: Customize Templates (arch-init:templates-customized)

Template Adaptation Strategy:

1. Load Base Templates for the chosen language (Python/Rust/TypeScript)
2. Apply Architecture-Specific Modifications based on selected paradigm
3. Generate Custom Configuration reflecting architectural choices
4. Create Documentation explaining the architecture

Example Adaptations:

For Functional Core, Imperative Shell:

**Verification:** Run the command with `--help` flag to verify availability.
src/
├── core/                    # Pure business logic
│   ├── domain.py           # Domain models
│   ├── operations.py       # Pure functions
│   └── commands.py         # Command objects
└── adapters/               # Side effects
    ├── database.py         # DB operations
    ├── api.py              # HTTP operations
    └── filesystem.py       # File operations

Verification: Run the command with --help flag to verify availability.

For Hexagonal Architecture:

**Verification:** Run the command with `--help` flag to verify availability.
src/
├── domain/                 # Business logic (no framework deps)
│   ├── models.py
│   ├── services.py
│   └── ports/             # Interfaces
│       ├── input.py       # Use cases
│       └── output.py      # Repository interfaces
└── infrastructure/        # Framework-specific code
    ├── persistence/       # Repositories
    ├── web/               # Controllers
    └── messaging/         # Event handlers

Verification: Run the command with --help flag to verify availability.

For Microservices:

**Verification:** Run the command with `--help` flag to verify availability.
project/
├── services/
│   ├── service-a/         # Independent service
│   │   ├── src/
│   │   ├── tests/
│   │   ├── Dockerfile
│   │   └── pyproject.toml
│   └── service-b/         # Independent service
│       ├── src/
│       ├── tests/
│       ├── Dockerfile
│       └── pyproject.toml
├── api-gateway/
├── shared/
│   └── events/
└── docker-compose.yml

Verification: Run pytest -v to verify tests pass.

Step 5: Create Architecture Decision Record (arch-init:decision-recorded)

Generate ADR documenting the architecture choice:

# Architecture Decision Record: [Paradigm Name]

## Date
[Current date]

## Status
Accepted | Proposed | Deprecated | Superseded by [link]

## Context
[Project type, team size, domain complexity, key requirements]

## Decision
[Chosen architecture paradigm]

## Rationale
### Research Findings
[Summarize online research results]

### Key Considerations
- **Team Fit**: [Why this matches team size/experience]
- **Domain Fit**: [Why this matches problem complexity]
- **Technology Fit**: [Why this works with chosen stack]
- **Scalability**: [How this addresses scaling needs]

### Alternatives Considered
1. **[Alternative 1]**: Rejected because [reason]
2. **[Alternative 2]**: Rejected because [reason]

## Consequences
### Positive
- [Benefit 1]
- [Benefit 2]

### Negative
- [Trade-off 1] with mitigation: [strategy]
- [Trade-off 2] with mitigation: [strategy]

## Implementation
- **Templates**: [Which templates were customized]
- **Key Patterns**: [Patterns to follow]
- **Anti-Patterns**: [What to avoid]
- **Resources**: [Links to paradigm skill, examples, etc.]

## References
- [Paradigm skill link]
- [Research sources]
- [Example projects]

Verification: Run the command with --help flag to verify availability.

Output: Complete Initialization Package

After completing this workflow, you'll have:

1. Project Structure: Customized to chosen architecture
2. Configuration: Architecture-appropriate tooling and dependencies
3. Documentation: ADR explaining the architecture choice
4. Guidance: Links to relevant paradigm skill for implementation
5. Examples: Reference projects using similar architecture

Script Integration

Claude Code can invoke the architecture research and template customization scripts:

Architecture Research

# Run architecture researcher for recommendations
uv run python plugins/attune/scripts/architecture_researcher.py \
  --project-type web-api \
  --domain-complexity complex \
  --team-size 5-15 \
  --language python \
  --output-json

Verification: Run python --version to verify Python environment.

The researcher returns a recommendation with:

• Primary paradigm and rationale
• Trade-offs and mitigations
• Alternative paradigms considered
• Confidence level

Template Customization

# Generate architecture-specific directory structure
uv run python plugins/attune/scripts/template_customizer.py \
  --paradigm cqrs-es \
  --language python \
  --project-name my-project \
  --output-dir ./my-project

Verification: Run python --version to verify Python environment.

This creates the paradigm-appropriate structure (e.g., commands/, queries/, events/ for CQRS).

Full Interactive Flow

# Interactive architecture-aware initialization
uv run python plugins/attune/scripts/attune_arch_init.py \
  --name my-project \
  --lang python

# Non-interactive with explicit architecture
uv run python plugins/attune/scripts/attune_arch_init.py \
  --name my-project \
  --lang python \
  --arch hexagonal \
  --accept-recommendation

Verification: Run python --version to verify Python environment.

Using as Library (within Claude Code)

# Import and use programmatically
from architecture_researcher import ArchitectureResearcher, ProjectContext
from template_customizer import TemplateCustomizer

# Create context and get recommendation
context = ProjectContext(
    project_type="web-api",
    domain_complexity="complex",
    team_size="5-15",
    language="python"
)
researcher = ArchitectureResearcher(context)
recommendation = researcher.recommend()

# Apply template customization
customizer = TemplateCustomizer(
    paradigm=recommendation.primary,
    language="python",
    project_name="my-project"
)
customizer.apply_structure(Path("./my-project"))

Verification: Run the command with --help flag to verify availability.

Integration with Existing Commands

This skill enhances /attune:init by adding an architecture selection phase:

# Standard initialization (no architecture decision)
/attune:init --lang python --name my-project

# Architecture-aware initialization
/attune:brainstorm           # Explore project needs
Skill(architecture-aware-init) # Select architecture based on research
/attune:init --arch <paradigm> # Initialize with chosen architecture

Verification: Run python --version to verify Python environment.

Example Session

User: I'm creating a Python web API for a fintech application. Team of 8 developers, complex business rules, need high security and audit trails.

Step 1 - Context: Project type=Web API, Domain=Highly Complex, Team=5-15, Requirements=Security, Auditability

Step 2 - Research:

WebSearch("Python fintech API architecture patterns 2026")
WebSearch("financial services API audit trail architecture")
WebSearch("CQRS Event Sourcing Python examples")

Verification: Run python --version to verify Python environment.

Step 3 - Selection: Research + Decision Matrix → CQRS + Event Sourcing

Step 4 - Templates: Customized structure for CQRS/ES with:

• Command handling module
• Query handling module
• Event store configuration
• Aggregate patterns
• Projection handlers

Step 5 - ADR: Documenting why CQRS/ES for fintech (auditability, complex business rules, regulatory compliance)

Result: Project initialized with architecture-appropriate structure and clear decision rationale.

Related Skills

• Skill(architecture-paradigms) - Comprehensive paradigm selection
• Skill(architecture-paradigm-*) - Specific paradigm implementation guidance
• Skill(attune:project-brainstorming) - Project ideation before architecture
• Skill(attune:project-specification) - Requirements after architecture chosen

See Also

• /attune:init - Basic project initialization
• /attune:plan - Architecture planning after paradigm selection
• Architecture paradigms README for paradigm details

Troubleshooting

Common Issues

Command not found Ensure all dependencies are installed and in PATH

Permission errors Check file permissions and run with appropriate privileges

Unexpected behavior Enable verbose logging with --verbose flag