Comprehensive guide for implementing code incrementally following established patterns, conventions, and quality standards
Scanned 9/10/2026
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---
name: incremental-implementation
description: Comprehensive guide for implementing code incrementally following established patterns, conventions, and quality standards
languages: [python, typescript, javascript, go, rust, java, csharp, php, ruby]
subagents: [code/feature, code/bug-fix, code/refactor]
tools_needed: [edit, write, read]
---
## Instructions
When implementing features or changes, follow this incremental, quality-focused approach:
### Step 1: Follow Core Conventions Exactly
**Purpose:** Maintain codebase consistency and avoid introducing technical debt.
**How:**
- Read `core-conventions.md` (or equivalent project conventions) before starting
- Check language-specific conventions (Python, TypeScript, etc.)
- Follow established patterns for:
- Naming (variables, functions, classes, files)
- Error handling (throw vs return, typed errors)
- Imports (ordering, absolute vs relative)
- Testing (framework, coverage, structure)
- Database (ORM, migrations, queries)
**Why this matters:**
- Inconsistent code confuses maintainers
- Deviations from conventions create review friction
- Following patterns reduces cognitive load when reading code
**Example:**
```python
# ✅ Good - follows Python conventions
def calculate_total_price(items: list[Item]) -> Decimal:
"""Calculate total price including tax."""
subtotal = sum(item.price for item in items)
return subtotal * Decimal("1.08") # 8% tax
# ❌ Bad - violates conventions
def calcTotalPrice(items): # camelCase (wrong for Python), no types
sub = 0 # unclear variable name
for i in items:
sub = sub + i.price # verbose when comprehension works
return sub * 1.08 # magic number, float instead of Decimal
```
---
### Step 2: Match Existing Patterns in the Same Layer
**Purpose:** Keep similar code similar; don't introduce new patterns without reason.
**How:**
1. **Read 2-3 existing files** in the same layer before writing new code
- Same layer = same part of architecture (e.g., all API routes, all services, all models)
2. **Identify patterns:**
- How are functions/classes organized?
- How are dependencies injected?
- How are errors handled?
- What naming patterns are used?
3. **Copy patterns, don't invent:**
- If existing routes use `@router.get("/resource")`, use that
- If existing services use constructor injection, use that
- If existing models use `created_at`/`updated_at`, use that
**Why this matters:**
- Consistency makes code easier to navigate
- New patterns increase maintenance burden
- Patterns embody past decisions and domain knowledge
**Example:**
If existing API routes look like this:
```python
# Existing pattern in routes/user_routes.py
@router.get("/users/{user_id}")
async def get_user(
user_id: str,
user_service: UserService = Depends(get_user_service),
) -> UserResponse:
user = await user_service.get_by_id(user_id)
if not user:
raise HTTPException(status_code=404, detail="User not found")
return UserResponse.from_model(user)
```
Then new routes should match:
```python
# ✅ Good - matches existing pattern
@router.get("/orders/{order_id}")
async def get_order(
order_id: str,
order_service: OrderService = Depends(get_order_service),
) -> OrderResponse:
order = await order_service.get_by_id(order_id)
if not order:
raise HTTPException(status_code=404, detail="Order not found")
return OrderResponse.from_model(order)
# ❌ Bad - introduces new pattern without justification
@router.route("/orders/<order_id>", methods=["GET"]) # Different decorator style
def get_order_sync(order_id): # Not async when others are
service = OrderService() # Direct instantiation, not dependency injection
result = service.find(order_id) # Different method name (find vs get_by_id)
return jsonify(result) # Different response pattern
```
---
### Step 3: Add Inline Comments for Non-Obvious Logic
**Purpose:** Explain the WHY, not the WHAT. Help future readers (including yourself) understand intent.
**When to add comments:**
- ✅ **Complex algorithms** - explain the approach
- ✅ **Magic numbers** - explain what they represent
- ✅ **Workarounds** - explain why the workaround is needed
- ✅ **Invariants** - explain assumptions callers must maintain
- ✅ **Performance optimizations** - explain why optimization is needed
- ✅ **External dependencies** - explain API quirks or limitations
**When NOT to add comments:**
- ❌ Restating what the code does (redundant)
- ❌ Explaining obvious standard library functions
- ❌ Translating code to English line-by-line
**Examples:**
```python
# ✅ Good comments (explain WHY)
# Use exponential backoff to avoid overwhelming the API during rate limit recovery
for attempt in range(max_retries):
delay = 2 ** attempt # 1s, 2s, 4s, 8s, 16s
await asyncio.sleep(delay)
# 86400 = seconds in a day (cache expires daily at midnight)
cache_ttl = 86400
# Intentionally not awaited - fire and forget analytics event
asyncio.create_task(track_user_action(user_id, "login"))
# WORKAROUND: API returns 200 with error in body instead of 4xx/5xx
# Remove this check when API v2 is deployed (see JIRA-1234)
if response.status == 200 and "error" in response.json():
raise APIError(response.json()["error"])
```
```python
# ❌ Bad comments (restate code)
# Get user by ID
user = await user_service.get_by_id(user_id)
# Check if user is None
if user is None:
# Raise 404 error
raise HTTPException(status_code=404)
# Return user response
return UserResponse.from_model(user)
```
---
### Step 4: Add TODO Comments for Judgment Calls
**Purpose:** Flag decisions that need user review or future attention.
**When to add TODOs:**
- ✅ **Temporary workarounds** - "This will break if X happens"
- ✅ **Incomplete implementations** - "Add validation for edge case Y"
- ✅ **Performance concerns** - "This is O(n²), optimize if dataset grows"
- ✅ **Missing error handling** - "Handle timeout case"
- ✅ **Unclear requirements** - "Confirm with user if this behavior is correct"
- ✅ **Technical debt** - "Refactor to use repository pattern"
**Format:**
```python
# TODO: [Category] Description (Owner, Date)
# TODO: Performance - Cache this query result (Alice, 2026-04-10)
# TODO: Security - Add rate limiting to this endpoint (Bob, 2026-04-10)
# TODO: Validation - Handle case where email is None (Charlie, 2026-04-10)
```
**Categories:**
- `TODO: Incomplete` - Feature not fully implemented
- `TODO: Bug` - Known issue to fix
- `TODO: Performance` - Optimization needed
- `TODO: Security` - Security concern
- `TODO: Refactor` - Code quality improvement
- `TODO: Validation` - Missing input validation
- `TODO: Testing` - Missing test coverage
- `TODO: Documentation` - Missing docs
**Examples:**
```python
def process_payment(amount: Decimal, card_token: str) -> PaymentResult:
# TODO: Security - Add fraud detection check before processing (Alice, 2026-04-10)
# TODO: Performance - This calls payment API synchronously; make async (Bob, 2026-04-10)
result = payment_gateway.charge(amount, card_token)
# TODO: Incomplete - Handle gateway timeout (returns None currently) (Charlie, 2026-04-10)
if result is None:
return PaymentResult(status="failed", error="Gateway error")
return result
```
---
### Step 5: Implement One File at a Time
**Purpose:** Reduce context switching, make reviews easier, minimize merge conflicts.
**How:**
1. **Complete one file fully** before moving to the next
- Write the implementation
- Add inline comments
- Add TODOs if needed
- Verify it compiles/passes type checks
2. **Commit frequently** (optional, but recommended)
- One commit per file or logical change
- Makes rollback easier if needed
3. **Don't jump between files** during implementation
- Finish what you started
- Reduces mental context switching
**Why this matters:**
- **Easier to review:** Reviewers can focus on one file at a time
- **Fewer merge conflicts:** Changes are localized
- **Better focus:** Less context switching improves code quality
- **Easier rollback:** If one file has issues, only that file needs rework
**Anti-pattern:**
```
# ❌ Bad - jumping between files
1. Start implementing user_service.py
2. Realize you need UserRepository, switch to user_repository.py
3. Realize repository needs User model, switch to models.py
4. Go back to user_service.py, half-implement
5. Switch to user_routes.py to add API endpoint
6. Back to user_service.py to finish
```
**Good pattern:**
```
# ✅ Good - one file at a time
1. Implement models.py (User model) - COMPLETE
2. Implement user_repository.py (UserRepository) - COMPLETE
3. Implement user_service.py (UserService) - COMPLETE
4. Implement user_routes.py (API routes) - COMPLETE
5. Implement tests/test_user_service.py - COMPLETE
```
---
## Common Mistakes
### ❌ Mistake 1: Ignoring Existing Patterns
**Problem:** Introducing a new pattern when an existing one works.
**Example:**
```python
# Existing pattern (constructor injection)
class UserService:
def __init__(self, repo: UserRepository):
self.repo = repo
# ❌ New code introduces different pattern (property injection)
class OrderService:
@property
def repo(self) -> OrderRepository:
return get_repository() # Global lookup instead of injection
```
**Fix:** Match the existing pattern (constructor injection).
---
### ❌ Mistake 2: Over-Commenting
**Problem:** Commenting what the code already says.
**Example:**
```python
# ❌ Bad
# Loop through items
for item in items:
# Add item price to total
total += item.price
# ✅ Good (no comment needed - code is self-explanatory)
for item in items:
total += item.price
# ✅ Good (comment explains WHY, not WHAT)
# Sum prices excluding items marked as promotional (they're free)
for item in items:
if not item.is_promotional:
total += item.price
```
---
### ❌ Mistake 3: Implementing Multiple Files in Parallel
**Problem:** Jumping between files before completing any.
**Why it's bad:**
- Half-finished files are harder to review
- Increases merge conflict risk
- Harder to track progress
- More mental context switching
**Fix:** Finish one file completely before starting the next.
---
### ❌ Mistake 4: Not Reading Existing Code First
**Problem:** Writing code without understanding existing patterns.
**Example:**
- Writing sync code in an async codebase
- Using different error handling than the rest of the codebase
- Naming variables differently than existing conventions
**Fix:** Read 2-3 similar files before writing new code.
---
### ❌ Mistake 5: TODOs Without Context
**Problem:** Writing vague TODOs that don't explain what needs to be done.
**Bad:**
```python
# TODO: fix this
# TODO: improve
# TODO: check
```
**Good:**
```python
# TODO: Performance - Cache this query result to avoid N+1 problem (Alice, 2026-04-10)
# TODO: Security - Add rate limiting to prevent brute force (Bob, 2026-04-10)
# TODO: Validation - Check that email is not already registered (Charlie, 2026-04-10)
```
---
## Examples
### Example 1: Implementing a New Service
**Context:** Adding OrderService to an existing codebase
**Step 1: Read existing services**
```bash
# Read 2-3 existing services to understand patterns
cat services/user_service.py
cat services/product_service.py
cat services/payment_service.py
```
**Step 2: Match pattern**
```python
# ✅ Good - matches existing pattern
class OrderService:
"""Service for managing orders."""
def __init__(self, repo: OrderRepository):
"""Initialize with repository dependency."""
self.repo = repo
async def create_order(self, user_id: str, items: list[OrderItem]) -> Order:
"""Create new order for user.
Args:
user_id: ID of user placing order
items: List of items in order
Returns:
Created order
Raises:
ValidationError: If items list is empty
UserNotFoundError: If user doesn't exist
"""
if not items:
raise ValidationError("Order must have at least one item")
# TODO: Validation - Check that all items are in stock (Alice, 2026-04-10)
# Calculate total (excluding promotional items per business rules)
total = sum(item.price for item in items if not item.is_promotional)
order = Order(
user_id=user_id,
items=items,
total=total,
status=OrderStatus.PENDING,
)
return await self.repo.create(order)
```
---
### Example 2: Adding Inline Comments
**Without comments (unclear intent):**
```python
def calculate_discount(price: Decimal, user: User) -> Decimal:
if user.created_at < datetime.now() - timedelta(days=365):
return price * Decimal("0.9")
return price
```
**With good comments (intent is clear):**
```python
def calculate_discount(price: Decimal, user: User) -> Decimal:
"""Apply loyalty discount for long-term users.
Users who joined > 1 year ago get 10% discount as loyalty reward.
This is a business requirement from Product (see PRD-2024-Q3-05).
"""
one_year_ago = datetime.now() - timedelta(days=365)
if user.created_at < one_year_ago:
return price * Decimal("0.9") # 10% discount
return price
```
---
## Summary
**Key Principles:**
1. **Consistency over cleverness** - Match existing patterns
2. **Explain why, not what** - Comment intent, not implementation
3. **One thing at a time** - Complete files before moving on
4. **Flag uncertainties** - Use TODOs for judgment calls
5. **Read before writing** - Understand context first
**Benefits:**
- Easier code reviews
- Fewer merge conflicts
- Better maintainability
- Higher code quality
- Reduced cognitive load
**Next Steps:**
- After implementing, use `post-implementation-checklist` skill
- Before implementing, use `feature-planning` skill
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