gh-xbklairith-kisune-dev-workflow/skills/documentation/SKILL.md

name, description

name	description
documentation	Use when writing or updating documentation - generates function docs, API specs, architecture diagrams (Mermaid), READMEs, code explanations. Activates when user says "document this", "write README", "explain this code", mentions "docs", "documentation", "API docs", or asks "how does this work?".

Documentation Skill

Purpose

Generate comprehensive, maintainable documentation including code docstrings, API specifications, architecture diagrams, README files, and clear code explanations. Makes code understandable for future developers (including future you).

Activation Triggers

Activate this skill when:

• User says "document this"
• User asks "how does this work?"
• User asks "explain this code"
• User mentions "README", "docs", or "documentation"
• After completing a feature
• When API endpoints are created
• User says "write comments for this"
• User asks "what does this function do?"

Documentation Types

1. Code Documentation (Docstrings)

Goal: Clear, comprehensive function/class documentation

Example Format:

def function_name(param1: Type, param2: Type) -> ReturnType:
    """
    Brief one-line description.

    Detailed explanation of purpose, behavior, and context.

    Args:
        param1: Description with type and example values
        param2: Description with constraints

    Returns:
        Description of return value and meaning

    Example:
        >>> function_name(example_value1, example_value2)
        expected_output

    Raises:
        ErrorType: When and why this error occurs

    Note:
        Important details, gotchas, performance considerations
    """

Key Components:

• Brief description (one line)
• Detailed explanation (purpose and behavior)
• Args/Parameters (types, constraints, examples)
• Returns (type and meaning)
• Example (realistic usage)
• Raises/Throws (error conditions)
• Note (implementation details)

Language-Specific:

• Python: Use """triple quotes""", Args/Returns/Raises format
• JavaScript/TypeScript: Use JSDoc /** */, @param/@returns/@throws tags
• Java: Use Javadoc /** */, @param/@return/@throws tags
• C#: Use XML comments /// <summary>

2. API Documentation

Goal: Complete API reference for endpoints

REST API Example:

## Authentication API

### POST /api/auth/login

Authenticate user and return JWT access token.

**Request:**

```json
{
  "email": "user@example.com",
  "password": "SecureP@ss123"
}

Request Schema:

• email (string, required): Valid email address
• password (string, required): User password, min 8 characters

Response (200 OK):

{
  "success": true,
  "data": {
    "accessToken": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...",
    "refreshToken": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...",
    "expiresIn": 3600,
    "user": {
      "id": "uuid-here",
      "email": "user@example.com",
      "name": "John Doe"
    }
  }
}

Response Schema:

• success (boolean): Operation status
• data.accessToken (string): JWT access token (1 hour expiry)
• data.refreshToken (string): Refresh token (30 days expiry)
• data.expiresIn (number): Access token expiry in seconds
• data.user (object): User profile information

Error Responses:

401 Unauthorized - Invalid Credentials:

{
  "success": false,
  "error": {
    "code": "INVALID_CREDENTIALS",
    "message": "Email or password is incorrect"
  }
}

400 Bad Request - Validation Error:

{
  "success": false,
  "error": {
    "code": "VALIDATION_ERROR",
    "message": "Invalid email format",
    "details": {
      "field": "email",
      "value": "invalid-email"
    }
  }
}

429 Too Many Requests - Rate Limited:

{
  "success": false,
  "error": {
    "code": "RATE_LIMITED",
    "message": "Too many login attempts. Try again in 15 minutes.",
    "retryAfter": 900
  }
}

Example Usage:

# cURL
curl -X POST https://api.example.com/api/auth/login \
  -H "Content-Type: application/json" \
  -d '{"email":"user@example.com","password":"SecureP@ss123"}'

# JavaScript (fetch)
const response = await fetch('https://api.example.com/api/auth/login', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    email: 'user@example.com',
    password: 'SecureP@ss123'
  })
});

const data = await response.json();
console.log(data.data.accessToken);

Security Notes:

• Always use HTTPS in production
• Passwords must never be logged
• Rate limiting: 5 attempts per 15 minutes per IP
• Access tokens expire in 1 hour
• Refresh tokens expire in 30 days

### 3. Architecture Documentation

**Goal:** Clear system overview and component relationships

**Example:**

```markdown
# System Architecture: Trading Platform

## Overview

High-performance trading platform built with microservices architecture,
supporting real-time market data, automated strategy execution, and
portfolio management.

## System Diagram

                       ┌──────────────┐
                       │   Frontend   │
                       │  (React SPA) │
                       └──────┬───────┘
                              │
                              │ HTTPS/WSS
                              │
                ┌─────────────▼──────────────┐
                │     API Gateway            │
                │   (Auth, Rate Limiting)    │
                └─────────────┬──────────────┘
                              │
                ┌─────────────┴──────────────┐
                │                            │
     ┌──────────▼─────────┐      ┌──────────▼─────────┐
     │  Auth Service      │      │  Trading Service   │
     │  (JWT, Sessions)   │      │  (Orders, Trades)  │
     └──────────┬─────────┘      └──────────┬─────────┘
                │                            │
                │                            │
     ┌──────────▼─────────┐      ┌──────────▼─────────┐
     │  User Database     │      │  Trading Database  │
     │  (PostgreSQL)      │      │  (PostgreSQL)      │
     └────────────────────┘      └────────────────────┘
                                          │
                                 ┌────────▼─────────┐
                                 │  Market Data     │
                                 │  (WebSocket)     │
                                 └──────────────────┘

## Core Components

### 1. API Gateway
**Responsibility:** Entry point for all client requests

**Functions:**
- Request routing to appropriate service
- JWT token validation
- Rate limiting (100 req/min per user)
- Request/response logging
- CORS handling

**Technology:** Node.js + Express
**Scaling:** Horizontal (3+ instances behind load balancer)

### 2. Auth Service
**Responsibility:** User authentication and session management

**Functions:**
- User registration and login
- JWT token generation (access + refresh)
- Session management with Redis
- Password hashing with bcrypt
- OAuth integration (Google, GitHub)

**Technology:** Node.js + PostgreSQL + Redis
**Scaling:** Stateless, horizontal scaling

### 3. Trading Service
**Responsibility:** Order execution and portfolio management

**Functions:**
- Place/cancel orders
- Real-time position tracking
- P&L calculations
- Risk management checks
- Strategy execution

**Technology:** Node.js + PostgreSQL + WebSocket
**Scaling:** Horizontal with sticky sessions

## Data Flow

### Login Flow
1. User submits email/password to Frontend
2. Frontend sends POST /api/auth/login to API Gateway
3. API Gateway routes to Auth Service
4. Auth Service validates credentials against User Database
5. Auth Service generates JWT tokens
6. Tokens cached in Redis for fast validation
7. Tokens returned to Frontend
8. Frontend stores tokens in memory/localStorage

### Order Placement Flow
1. User creates order in Frontend
2. Frontend sends POST /api/orders with JWT
3. API Gateway validates JWT
4. Request routed to Trading Service
5. Trading Service validates order parameters
6. Trading Service checks account balance/positions
7. Trading Service applies risk management rules
8. Order saved to Trading Database
9. Order sent to market via Market Data service
10. Confirmation returned to Frontend
11. WebSocket update sent to Frontend with execution status

## Integration Points

### External Services
- **Alpaca API**: Market data and order execution
- **Redis Cloud**: Session caching (512MB)
- **Supabase**: Database hosting (PostgreSQL)
- **Vercel**: Frontend hosting and API routes

### Internal APIs
- Auth Service → Trading Service: User validation
- Trading Service → Market Data: Real-time prices
- All Services → API Gateway: Centralized routing

## Security Architecture

### Authentication
- JWT tokens with RS256 signing
- Access tokens: 1 hour expiry
- Refresh tokens: 30 days expiry
- Tokens stored in httpOnly cookies (production)

### Authorization
- Role-based access control (user, admin)
- Resource-level permissions
- API key authentication for service-to-service

### Data Protection
- All passwords hashed with bcrypt (cost 12)
- PII encrypted at rest (AES-256)
- TLS 1.3 for all external communication
- Database connection pooling with SSL

## Performance Considerations

### Caching Strategy
- Session tokens cached in Redis (1 hour TTL)
- Market data cached in memory (1 second TTL)
- User profiles cached (5 minute TTL)

### Database Optimization
- Indexes on frequently queried columns
- Connection pooling (max 20 connections)
- Read replicas for reporting queries

### Scaling Strategy
- Horizontal scaling for stateless services
- Vertical scaling for database
- CDN for static assets
- Background jobs for heavy computations

## Monitoring & Observability

### Metrics
- Request latency (p50, p95, p99)
- Error rates by endpoint
- Active user sessions
- Order execution time

### Logging
- Structured JSON logs
- Centralized logging (CloudWatch)
- Correlation IDs for request tracing

### Alerts
- High error rate (>1% for 5 minutes)
- Slow responses (>500ms p95)
- Database connection pool exhaustion
- Failed authentication attempts spike

4. README Generation

Goal: Comprehensive project README

Essential Sections:

# [Project Name]

[One-line description] - [What problem it solves]

## Features
- Key feature 1
- Key feature 2
- Key feature 3

## Installation
\`\`\`bash
git clone [repo-url]
cd [repo-name]
npm install  # or pip install -r requirements.txt
cp .env.example .env  # Configure environment
npm run dev
\`\`\`

## Usage
\`\`\`javascript
// Basic example showing main functionality
const result = await mainFunction(params);
\`\`\`

## Configuration
| Variable | Description | Required |
|----------|-------------|----------|
| `DATABASE_URL` | DB connection string | Yes |
| `API_KEY` | External API key | Yes |

## Development
\`\`\`bash
npm test           # Run tests
npm run lint       # Check code style
npm run build      # Production build
\`\`\`

## License
MIT - see [LICENSE](LICENSE)

Optional Sections (add as needed):

• Demo: Link to live demo or screenshots
• API Reference: Detailed API docs
• Project Structure: Directory layout
• Deployment: Docker/cloud deployment steps
• Contributing: How to contribute
• Acknowledgments: Credits and thanks

5. Code Explanations

Goal: Clear explanations of complex code

Process:

1. High-Level Purpose

   • What problem does this solve?
   • Where does it fit in the system?

2. Step-by-Step Logic

   • Break down into phases
   • Explain each step clearly
   • Use analogies when helpful

3. Key Algorithms/Patterns

   • Identify important algorithms
   • Explain why this approach
   • Note time/space complexity

4. Edge Cases

   • What unusual inputs are handled?
   • What assumptions are made?
   • What validation is performed?

Example Explanation:

## Explanation: Position Size Calculator

### Purpose
This function calculates how many shares to buy based on risk management
principles. It ensures that no single trade risks more than a specified
percentage of the account balance.

### How It Works

**Step 1: Validate Inputs**
First, we check that all inputs make sense:
- Account balance must be positive (can't trade with $0)
- Risk percentage must be between 0-100% (but really should be 1-5%)
- Entry price can't equal stop loss (would mean no risk defined)

**Step 2: Calculate Dollar Risk**
We determine how much money we're willing to lose:

risk_amount = account_balance * risk_percentage

Example: $10,000 account × 2% = $200 risk

**Step 3: Calculate Risk Per Share**
We figure out how much we'd lose per share if stopped out:

risk_per_share = |entry_price - stop_loss|

Example: |$150.50 - $148.00| = $2.50 per share

**Step 4: Calculate Position Size**
Divide total risk by per-share risk:

position_size = risk_amount / risk_per_share

Example: $200 ÷ $2.50 = 80 shares

### Why This Approach?

This is the "fixed percentage risk" method, which is standard in trading
because:
1. **Consistency**: Every trade risks the same percentage
2. **Scalability**: Works as account grows/shrinks
3. **Protection**: Limits damage from losing trades
4. **Simplicity**: Easy to understand and implement

### Edge Cases Handled

- **Entry equals stop**: Raises error (infinite position size)
- **Negative prices**: Absolute value prevents issues
- **Fractional shares**: Rounds down to whole shares
- **Zero risk**: Would cause division by zero, caught by validation

### Alternative Approaches

We could also use:
1. **Fixed dollar risk**: Risk same $ amount every trade (doesn't scale)
2. **Kelly Criterion**: Math-based optimal position (requires win rate data)
3. **Volatility-based**: Use ATR instead of stop distance (more complex)

We chose fixed percentage for simplicity and reliability.

When to Document

Always Document:

• Public APIs and endpoints
• Complex algorithms
• Non-obvious logic
• Security-sensitive code
• Performance-critical sections
• Error handling strategies

Consider Documenting:

• Helper functions with multiple params
• Class constructors
• Configuration options
• Database schema

Don't Bother Documenting:

• Trivial getters/setters
• Self-explanatory code
• Temporary/experimental code

Best Practices

1. Write for Future You: Assume you'll forget everything in 6 months
2. Explain Why, Not What: Code shows what, docs explain why
3. Keep Examples Current: Update examples when code changes
4. Use Consistent Format: Follow language conventions
5. Be Concise: Every word should add value
6. Use Active Voice: "Returns user" not "User is returned"
7. Include Edge Cases: Document unusual inputs and outputs
8. Update With Code: Outdated docs are worse than no docs

Integration Points

• Works with spec-driven skill for feature documentation
• Works with code-quality skill to verify docs exist
• Auto-triggered after feature completion

Notes

• Default to clear code over comments (code is always correct, comments lie)
• Good naming reduces need for documentation
• Complex logic deserves explanation
• APIs require comprehensive documentation
• When in doubt, document it