Prisma Schema Analyzer

Analyze Prisma schemas for performance, relation design, index strategy, migration safety, and query optimization — audit schema.prisma for production readiness.

Analyze Prisma schemas for performance issues, relation design problems, missing indexes, migration risks, and query optimization opportunities. Audit schema.prisma for production readiness and recommend improvements.

Usage

"Analyze my Prisma schema for issues"
"Check for missing indexes in my Prisma schema"
"Review Prisma relations for N+1 risks"
"Audit migration safety for my schema changes"

How It Works

1. Schema Discovery

cat prisma/schema.prisma 2>/dev/null
find . -name "schema.prisma" 2>/dev/null
# Check migrations
ls prisma/migrations/ 2>/dev/null | tail -10

2. Model Analysis

Field design:

• Proper types for each field (String vs Int vs DateTime)
• Missing @default values where applicable
• @updatedAt on models that need update tracking
• Optional fields (?) that should be required
• Enum usage vs string for fixed-value fields
• JSON fields where structured models would be better

ID strategy:

• @id type: autoincrement vs cuid vs uuid
• Composite keys where appropriate (@@id)
• Performance implications of UUID PKs vs integer

Naming conventions:

• Model names: PascalCase
• Field names: camelCase
• Relation names: descriptive
• @@map and @map for DB-native naming

3. Index Strategy

• Missing indexes on foreign key fields
• Missing indexes on fields used in where clauses
• Composite indexes for multi-column queries (@@index)
• Unique constraints for business rules (@@unique)
• Full-text indexes for search fields
• Index on createdAt / updatedAt for time-based queries

4. Relation Analysis

• Implicit many-to-many (Prisma auto-creates join table — OK for simple cases)
• Explicit many-to-many needed for extra fields on the relation
• One-to-one relations: which side owns the FK?
• Cascade delete configuration (onDelete: Cascade vs SetNull vs Restrict)
• Self-relations (tree structures, followers)
• Relation loading patterns (include vs select)

5. Query Optimization

Review Prisma Client usage in codebase:

grep -rn "prisma\.\w\+\.find\|prisma\.\w\+\.create\|prisma\.\w\+\.update" src/ | head -30
grep -rn "include:" src/ | head -20

• N+1 queries: loops with individual findUnique
• Over-fetching: findMany without select
• Missing pagination: findMany without take/skip
• Raw queries that could use Prisma Client
• Transaction usage for multi-step operations

6. Migration Safety

npx prisma migrate diff --from-schema-datamodel prisma/schema.prisma --to-schema-datasource prisma/schema.prisma --script 2>/dev/null

• Destructive changes: dropped columns, renamed fields
• Locking operations: new indexes on large tables
• Data migration needed: type changes, default additions
• Backward compatibility: can old code run with new schema?

Output

## Prisma Schema Analysis

**Models:** 14 | **Relations:** 22 | **Indexes:** 8 | **Enums:** 5

### 🔴 Critical (2)
1. **Missing index on Order.userId** — prisma/schema.prisma:45
   `userId String` without `@@index([userId])`
   Orders table has FK queries on every page load
   → Add `@@index([userId])` to Order model

2. **Cascade delete on User → Orders** — prisma/schema.prisma:12
   Deleting a user cascades to all orders (financial records!)
   → Change to `onDelete: Restrict` or `SetNull`

### 🟡 Improvements (4)
3. Missing `@updatedAt` on 8 models
4. Using String for `status` fields — use enum OrderStatus
5. Implicit many-to-many Tag-Post — add explicit for metadata
6. No composite index on `[userId, createdAt]` (common query pattern)

### 📊 Schema Metrics
- Average fields per model: 8.2
- Models with indexes: 6/14 (43%)
- Relations with explicit cascade: 4/22 (18%)
- Optional fields: 23 (review if all truly optional)

### ✅ Good Practices
- cuid() for all primary keys (distributed-safe)
- Enum types for status fields
- @map/@@ for Postgres naming conventions
- Proper DateTime fields with @default(now())