# Tech Architecture Doc

> Tech Architecture Doc is an Agent Skill for documents published in the majiayu000/claude-skill-registry repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Create comprehensive technical architecture documentation for the saxjaxTunerIntelligent audio processing pipeline. Use this when onboarding developers, documenting system architecture, or explaining the audio data flow and settings integration.

- Skill name: `tech-architecture-doc`
- Category: [Documents](https://www.openparable.com/skill/documents/1)
- Source: https://github.com/majiayu000/claude-skill-registry/blob/HEAD/skills/data/tech-architecture-doc/SKILL.md
- Repository: majiayu000/claude-skill-registry (498 GitHub stars when collected)

## SKILL.md

# Technical Architecture Documentation Generator

Write comprehensive technical architecture documents for the saxjaxTunerIntelligent project, focusing on audio processing pipeline and settings integration.

## Document Structure

### Part 1: Core Audio Architecture & Data Flow

1. **Technology Stack & High-Level Design**
   - Core technologies: Swift, SwiftUI, AudioKit
   - High-level audio flow: Microphone → AudioKit Engine → Pitch Tap → Detection → ViewModel → View
   - **Include Mermaid.js flow diagram**

2. **TunerEngine.swift Deep Dive**
   - **Role & Responsibility**: Central audio operations manager
   - **AudioKit Integration**: How it uses AudioEngine, InputDevice, Mixer nodes
   - **Input and Pitch Tap**: 
     - How audio is captured from microphone
     - Explain tap concept (`installTap`) for real-time, non-destructive analysis
   - **Pitch Detection Algorithm**:
     - Which algorithm is used (YIN, DYWA, HPS, etc.)
     - Reference `PitchDetectorType.swift` for abstraction
   - **Output Data Flow**:
     - Data structure (PitchResult, DetectedNote)
     - How results pass to TunerViewModel (delegate, Combine, callback)

### Part 2: Settings Integration & Functional Impact

**Include high-level Mermaid diagram** showing how settings influence main data flow

For each setting, provide:
1. **Setting Name**
2. **User Interface (UI)**: Where configured (SettingsView, QuickAccessBar)
3. **Data Model & State**: Where stored (TuningProfile, TunerViewModel)
4. **Core Logic Integration**: How TunerEngine uses this value
5. **Functional Impact & Purpose**: Effect on algorithm/UI, why musicians use it, practical example

### Settings to Analyze
- Transposition
- A4 Frequency / Kammertone
- Tuning Tolerance
- Sound Playback (reference tone)

## Mermaid Diagram Examples

### Audio Flow
```mermaid
graph LR
    A[Microphone] --> B[AudioKit Engine]
    B --> C[Pitch Tap]
    C --> D[Pitch Detection Algorithm]
    D --> E[TunerViewModel]
    E --> F[SwiftUI View]
```

### Settings Integration
```mermaid
graph TB
    A[Audio Input] --> B[TunerEngine]
    C[TuningProfile Settings] -.influences.-> B
    B --> D[Pitch Detection]
    C -.influences.-> D
    D --> E[Display Calculation]
    C -.influences.-> E
```

## Writing Guidelines
- Be exceptionally specific and clear
- Reference actual file names and component names
- Include code locations where relevant
- Explain data flow with precision
- Use visual diagrams to clarify complex flows
- Target audience: Senior engineer new to the project

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