N+1 Query Pattern Detection
Activation Announcement
IMPORTANT: When this skill activates, ALWAYS start your response with:
code
🔍 **N+1 Pattern Detection Scan** Scanning codebase for loop + query anti-patterns...
This provides a visual indicator to the user that systematic detection is running.
What is N+1?
An N+1 query problem occurs when code:
- •Fetches a list of N items
- •Then makes 1 additional query per item in a loop
Instead of 1 batch query, you get N+1 queries. For 100 items = 101 DB roundtrips.
Detection Strategy
Phase 1: Semantic Search for Loop + Query Patterns
Run these searches to find suspicious code:
code
fast_search("for loop database query execute", method="semantic", limit=30)
fast_search("foreach await repository find", method="semantic", limit=30)
fast_search("loop api call fetch request", method="semantic", limit=30)
fast_search("iterate collection query each", method="semantic", limit=30)
Phase 2: Pattern Search for Language-Specific Idioms
code
# C# / Entity Framework
fast_search("foreach await context", method="text", limit=20)
fast_search("for var in FirstOrDefault", method="text", limit=20)
# TypeScript / Prisma / TypeORM
fast_search("for of await prisma findUnique", method="text", limit=20)
fast_search("forEach await fetch", method="text", limit=20)
# Python / SQLAlchemy / Django
fast_search("for in session query", method="text", limit=20)
fast_search("for in objects get filter", method="text", limit=20)
# General patterns
fast_search("for each get by id", method="semantic", limit=20)
Phase 3: Trace Suspicious Functions
For each suspicious result, trace the call path:
code
trace_call_path(symbol_name="<function_name>", direction="downstream", max_depth=3)
Look for paths that lead to:
- •Database access (repository, context, connection, cursor)
- •HTTP calls (fetch, axios, http client)
- •Cache lookups without batching
Phase 4: Verify with Code Inspection
code
get_symbols(file_path="<file>", target="<function>", mode="full")
Confirm the pattern by checking:
- •Is there a loop construct (for, foreach, while, map)?
- •Is there a query/fetch inside the loop body?
- •Could this be batched into a single query?
Output Format
IMPORTANT: Always present findings in this structured format:
code
## N+1 Pattern Detection Results
### Summary
- Files scanned: X
- Potential N+1 patterns found: Y
- Confidence: High/Medium/Low
### Findings
#### 1. [HIGH] file/path.ts:42 - `processOrders`
**Pattern**: foreach loop with individual DB fetch
**Code**:
```typescript
for (const order of orders) {
const customer = await db.customers.findUnique({ where: { id: order.customerId }});
}
Fix: Batch fetch all customers upfront with findMany({ where: { id: { in: customerIds }}})
2. [MEDIUM] file/path.cs:128 - LoadUserDetails
Pattern: LINQ with lazy loading inside loop ...
Recommendations
- •Replace individual queries with batch operations
- •Use Include/ThenInclude for eager loading (EF Core)
- •Consider caching for frequently accessed data
code
## Red Flags to Look For ### High Confidence Indicators - `await` inside `for`/`foreach`/`for...of` with DB method name - Loop variable used as query parameter - `.Find()`, `.Get()`, `.FirstOrDefault()`, `.findUnique()` inside loops - Multiple queries returning single items in sequence ### Medium Confidence Indicators - Lazy loading patterns (accessing navigation properties in loops) - `.Select()` with async operations - Nested loops with any data access ### Language-Specific Patterns | Language | High-Risk Patterns | |----------|-------------------| | C# | `foreach` + `await context.X.FindAsync()` | | TypeScript | `for...of` + `await prisma.x.findUnique()` | | Python | `for x in` + `session.query().filter().first()` | | Java | `for` + `repository.findById()` | | Go | `for range` + `db.Query()` or `db.QueryRow()` | ## Success Criteria This skill succeeds when: - Clear visual announcement at start - Systematic search across semantic + pattern modes - Findings presented with file:line locations - Confidence levels assigned to each finding - Actionable fix suggestions provided - Results are language-appropriate