Resources

scripts/
  database-checklist.sh
references/
  orm-comparison.md

Database Layer Implementation

This skill guides you through implementing database layers in applications, from initial schema design to query optimization. It leverages GoodVibes precision tools and project analysis tools for type-safe, production-ready database implementations.

When to Use This Skill

Use this skill when you need to:

Set up a new database connection and ORM
Design and implement database schemas
Create and run migrations
Generate type-safe database clients
Write queries and handle relationships
Optimize database performance
Integrate with existing database infrastructure

Workflow

Follow this sequence for database layer implementation:

1. Discover Existing Database Infrastructure

Before implementing any database changes, understand the current state using the

detect_stack

analysis tool:

yaml

detect_stack:
  project_root: "."
  categories: ["database", "orm"]

This identifies:

Existing database technology (PostgreSQL, MySQL, MongoDB, SQLite)
ORM/query builder in use (Prisma, Drizzle, Kysely, Mongoose)
Schema definition files
Migration tooling
Connection management patterns

Check project memory for database decisions:

yaml

precision_read:
  files:
    - path: ".goodvibes/memory/decisions.json"
    - path: ".goodvibes/memory/patterns.json"
  verbosity: minimal

Look for:

Previous database technology choices ("Use Prisma for type safety")
Migration strategies ("Always use reversible migrations")
Performance patterns ("Add indexes for foreign keys")
Known issues ("Avoid N+1 queries in user endpoints")

If database already exists, map the current schema:

yaml

get_database_schema:
  project_root: "."
  include_relations: true
  include_indexes: true

This returns:

Table/collection definitions
Column types and constraints
Relationships (foreign keys, references)
Indexes and unique constraints
Enums and custom types

2. Choose Database Technology

If starting fresh, consult the ORM comparison reference to select the appropriate technology stack.

See: references/orm-comparison.md for decision trees.

Key decision factors:

Factor	Recommendation
Type safety priority	Prisma or Drizzle
Maximum SQL control	Kysely or Drizzle
Document database	Mongoose (MongoDB)
Serverless/edge	Drizzle with libSQL/Turso
Existing PostgreSQL	Prisma or Drizzle
Learning curve	Prisma (best DX)

Record your decision in memory:

After choosing, document the decision in

.goodvibes/memory/decisions.json

for future reference.

3. Design Schema

Identify entities and relationships first:

Entities: User, Post, Comment, Category

Relationships:
- User 1:N Post (author)
- Post N:M Category (through PostCategory)
- Post 1:N Comment
- User 1:N Comment (author)

Create schema files using precision_write:

For Prisma:

yaml

precision_write:
  files:
    - path: "prisma/schema.prisma"
      content: |
        generator client {
          provider = "prisma-client-js"
        }

        datasource db {
          provider = "postgresql"
          url      = env("DATABASE_URL")
        }

        model User {
          id        String   @id @default(cuid())
          email     String   @unique
          name      String?
          posts     Post[]
          comments  Comment[]
          createdAt DateTime @default(now())
          updatedAt DateTime @updatedAt
        }

        model Post {
          id         String     @id @default(cuid())
          title      String
          content    String
          published  Boolean    @default(false)
          author     User       @relation(fields: [authorId], references: [id])
          authorId   String
          categories Category[]
          comments   Comment[]
          createdAt  DateTime   @default(now())
          updatedAt  DateTime   @updatedAt

          @@index([authorId])
          @@index([published, createdAt])
        }

        model Category {
          id    String @id @default(cuid())
          name  String @unique
          posts Post[]
        }

        model Comment {
          id        String   @id @default(cuid())
          content   String
          post      Post     @relation(fields: [postId], references: [id])
          postId    String
          author    User     @relation(fields: [authorId], references: [id])
          authorId  String
          createdAt DateTime @default(now())

          @@index([postId])
          @@index([authorId])
        }
  verbosity: minimal

For Drizzle:

yaml

precision_write:
  files:
    - path: "src/db/schema.ts"
      content: |
        import { pgTable, text, timestamp, boolean, index } from 'drizzle-orm/pg-core';
        import { relations } from 'drizzle-orm';

        export const users = pgTable('users', {
          id: text('id').primaryKey().$defaultFn(() => crypto.randomUUID()),
          email: text('email').notNull().unique(),
          name: text('name'),
          createdAt: timestamp('created_at').defaultNow().notNull(),
          updatedAt: timestamp('updated_at').defaultNow().notNull(),
        });

        export const posts = pgTable('posts', {
          id: text('id').primaryKey().$defaultFn(() => crypto.randomUUID()),
          title: text('title').notNull(),
          content: text('content').notNull(),
          published: boolean('published').default(false).notNull(),
          authorId: text('author_id').notNull().references(() => users.id),
          createdAt: timestamp('created_at').defaultNow().notNull(),
          updatedAt: timestamp('updated_at').defaultNow().notNull(),
        }, (table) => ({
          authorIdx: index('author_idx').on(table.authorId),
          publishedCreatedIdx: index('published_created_idx').on(table.published, table.createdAt),
        }));

        export const usersRelations = relations(users, ({ many }) => ({
          posts: many(posts),
        }));

        export const postsRelations = relations(posts, ({ one }) => ({
          author: one(users, {
            fields: [posts.authorId],
            references: [users.id],
          }),
        }));
  verbosity: minimal

Schema best practices:

Use appropriate ID strategy:
- CUID/UUID for distributed systems
- Auto-increment for simple apps
- Composite keys for join tables
Add timestamps:
- Always include
```
createdAt
```
- Include
```
updatedAt
```
  for mutable entities
- Consider
```
deletedAt
```
  for soft deletes
Index strategically:
- Foreign keys (for joins)
- Frequently queried fields
- Composite indexes for multi-column filters
- Unique constraints where applicable
Plan for scale:
- Text vs VARCHAR limits
- JSONB for flexible data (PostgreSQL)
- Separate tables for large text/blobs

4. Configure Database Connection

Create environment configuration:

yaml

precision_write:
  files:
    - path: ".env.example"
      content: |
        # Database
        DATABASE_URL="postgresql://user:password@localhost:5432/dbname"
        # For Prisma with connection pooling
        # DATABASE_URL="postgresql://user:password@localhost:5432/dbname?pgbouncer=true"
        # DIRECT_URL="postgresql://user:password@localhost:5432/dbname"
      mode: overwrite
  verbosity: minimal

Create database client module:

For Prisma:

yaml

precision_write:
  files:
    - path: "src/lib/db.ts"
      content: |
        import { PrismaClient } from '@prisma/client';

        const globalForPrisma = globalThis as unknown as {
          prisma: PrismaClient | undefined;
        };

        export const db =
          globalForPrisma.prisma ??
          new PrismaClient({
            log:
              process.env.NODE_ENV === 'development'
                ? ['query', 'error', 'warn']
                : ['error'],
          });

        if (process.env.NODE_ENV !== 'production') {
          globalForPrisma.prisma = db;
        }
  verbosity: minimal

For Drizzle:

yaml

precision_write:
  files:
    - path: "src/lib/db.ts"
      content: |
        import { drizzle } from 'drizzle-orm/postgres-js';
        import postgres from 'postgres';
        import * as schema from '@/db/schema';

        const connectionString = process.env.DATABASE_URL!;

        const client = postgres(connectionString, {
          max: process.env.NODE_ENV === 'production' ? 10 : 1,
        });

        export const db = drizzle(client, { schema });
  verbosity: minimal

5. Run Migrations

Use

precision_exec

to run migration commands with expectations:

For Prisma:

yaml

precision_exec:
  commands:
    - cmd: "npx prisma migrate dev --name init"
      timeout_ms: 60000
      expect:
        exit_code: 0
      # Note: Prisma outputs progress to stderr; this is expected behavior
    - cmd: "npx prisma generate"
      expect:
        exit_code: 0
  verbosity: standard

For Drizzle:

yaml

precision_exec:
  commands:
    - cmd: "npx drizzle-kit generate"
      expect:
        exit_code: 0
    - cmd: "npx drizzle-kit push"
      timeout_ms: 60000
      expect:
        exit_code: 0
  verbosity: standard

Migration best practices:

Always review generated migrations before applying
Use reversible migrations (include both up and down)
Test migrations on dev database before production
Backup production data before running migrations
Use transactions for multi-step migrations

6. Generate Type-Safe Client

Use the

generate_types

project tool to generate TypeScript types from your schema:

yaml

generate_types:
  project_root: "."
  source: "database"
  output_path: "src/types/db.ts"

This creates type definitions for:

Table/collection types
Insert types (omitting auto-generated fields)
Update types (all fields optional)
Select types (with relations)

Verify type generation:

yaml

precision_exec:
  commands:
    - cmd: "npm run typecheck"
      expect:
        exit_code: 0
  verbosity: minimal

7. Implement Queries

Start with basic CRUD operations:

yaml

precision_write:
  files:
    - path: "src/db/queries/users.ts"
      content: |
        import { db } from '@/lib/db';

        export async function createUser(data: { email: string; name?: string }) {
          return db.user.create({
            data,
          });
        }

        export async function getUserById(id: string) {
          return db.user.findUnique({
            where: { id },
            include: {
              posts: true,
            },
          });
        }

        export async function updateUser(
          id: string,
          data: { email?: string; name?: string }
        ) {
          return db.user.update({
            where: { id },
            data,
          });
        }

        export async function deleteUser(id: string) {
          return db.user.delete({
            where: { id },
          });
        }
  verbosity: minimal

Check for N+1 query patterns using project tools:

yaml

get_prisma_operations:
  project_root: "."
  analyze_performance: true

This identifies:

N+1 query opportunities (missing
```
include
```
or
```
select
```
)
Missing indexes on frequently queried fields
Inefficient relationship loading

Optimize queries:

Use select to limit fields:

typescript

db.user.findMany({
  select: { id: true, email: true }, // Don't fetch unused fields
});

Eager load relationships:

typescript

db.post.findMany({
  include: { author: true }, // Prevents N+1
});

Use pagination:

typescript

db.post.findMany({
  take: 20,
  skip: (page - 1) * 20,
});

Add database-level constraints:

prisma

@@index([userId, createdAt(sort: Desc)])

8. Implement Transactions

For multi-step operations, use transactions:

Prisma:

typescript

export async function createPostWithCategories(
  postData: { title: string; content: string; authorId: string },
  categoryIds: string[]
) {
  return db.$transaction(async (tx) => {
    const post = await tx.post.create({
      data: {
        ...postData,
        categories: {
          connect: categoryIds.map((id) => ({ id })),
        },
      },
    });

    await tx.user.update({
      where: { id: postData.authorId },
      data: { updatedAt: new Date() },
    });

    return post;
  });
}

Drizzle:

typescript

export async function createPostWithCategories(
  postData: { title: string; content: string; authorId: string },
  categoryIds: string[]
) {
  return db.transaction(async (tx) => {
    const [post] = await tx.insert(posts).values(postData).returning();

    await tx.insert(postCategories).values(
      categoryIds.map((categoryId) => ({
        postId: post.id,
        categoryId,
      }))
    );

    return post;
  });
}

9. Seed Development Data

Create seed script for local development:

yaml

precision_write:
  files:
    - path: "prisma/seed.ts"
      content: |
        import { PrismaClient } from '@prisma/client';

        const prisma = new PrismaClient();

        async function main() {
          // Clear existing data
          await prisma.comment.deleteMany();
          await prisma.post.deleteMany();
          await prisma.user.deleteMany();
          await prisma.category.deleteMany();

          // Create users
          const alice = await prisma.user.create({
            data: {
              email: 'alice@example.com',
              name: 'Alice',
            },
          });

          const bob = await prisma.user.create({
            data: {
              email: 'bob@example.com',
              name: 'Bob',
            },
          });

          // Create categories
          const tech = await prisma.category.create({
            data: { name: 'Technology' },
          });

          const news = await prisma.category.create({
            data: { name: 'News' },
          });

          // Create posts
          await prisma.post.create({
            data: {
              title: 'First Post',
              content: 'This is the first post',
              published: true,
              authorId: alice.id,
              categories: {
                connect: [{ id: tech.id }],
              },
            },
          });

          console.log('Database seeded successfully');
        }

        main()
          .catch((e) => {
            console.error(e);
            process.exit(1);
          })
          .finally(async () => {
            await prisma.$disconnect();
          });
  verbosity: minimal

Update package.json:

yaml

precision_edit:
  edits:
    - path: "package.json"
      find: '"scripts": {'
      hints:
        near_line: 2
      replace: |
        "prisma": {
          "seed": "tsx prisma/seed.ts"
        },
        "scripts": {
  verbosity: minimal

10. Validate Implementation

Run the database checklist script:

bash

./plugins/goodvibes/skills/outcome/database-layer/scripts/database-checklist.sh .

This validates:

Schema file exists and is valid
Migration directory present
Database URL documented in .env.example
Type generation configured
No SQL injection vulnerabilities (string concatenation)
Connection pooling configured
Indexes on foreign keys

Run type checking and tests:

yaml

precision_exec:
  commands:
    - cmd: "npm run typecheck"
      expect:
        exit_code: 0
    - cmd: "npm run test -- db"
      expect:
        exit_code: 0
  verbosity: minimal

Use query_database to verify data integrity:

yaml

query_database:
  project_root: "."
  query: "SELECT COUNT(*) FROM users;"

Common Patterns

Soft Deletes

Add

deletedAt

field and filter in queries:

prisma

model Post {
  id        String    @id
  deletedAt DateTime?
}

typescript

// Soft delete
await db.post.update({
  where: { id },
  data: { deletedAt: new Date() },
});

// Query only active records
await db.post.findMany({
  where: { deletedAt: null },
});

Optimistic Locking

Use version field to prevent concurrent updates:

prisma

model Post {
  id      String @id
  version Int    @default(0)
}

typescript

await db.post.update({
  where: {
    id: postId,
    version: currentVersion,
  },
  data: {
    title: newTitle,
    version: { increment: 1 },
  },
});

Connection Pooling

For serverless environments, use connection pooling:

env

# PgBouncer
DATABASE_URL="postgresql://user:password@localhost:6543/db?pgbouncer=true"
DIRECT_URL="postgresql://user:password@localhost:5432/db"

prisma

datasource db {
  provider  = "postgresql"
  url       = env("DATABASE_URL")
  directUrl = env("DIRECT_URL")
}

Full-Text Search

PostgreSQL:

prisma

@@index([content(ops: raw("gin_trgm_ops"))], type: Gin)

typescript

await db.$queryRaw`
  SELECT * FROM posts
  WHERE to_tsvector('english', content) @@ to_tsquery('search terms')
`;

Security Checklist

Database credentials in environment variables (not committed)
Input validation on all user-provided data
Parameterized queries (no string concatenation)
Row-level security for multi-tenant apps
Rate limiting on expensive queries
Audit logging for sensitive operations
Least privilege database user permissions
SSL/TLS for database connections in production

Performance Checklist

Indexes on foreign keys
Composite indexes for multi-column filters
Connection pooling configured
Query result pagination
Eager loading to prevent N+1 queries
Database query logging in development
Explain/analyze for slow queries
Caching for frequently accessed data

Troubleshooting

Migration fails with constraint violation

Check existing data conflicts with new constraints
Add data migration before schema migration
Use multi-step migrations (add column nullable, populate, make required)

N+1 query detected

Use
```
get_prisma_operations
```
to identify location
Add
```
include
```
or
```
select
```
with relations
Consider using
```
dataloader
```
for complex cases

Connection pool exhausted

Increase pool size in connection string (
```
?pool_timeout=10
```
)
Check for missing
```
await
```
(connections not released)
Use connection pooler (PgBouncer, Prisma Accelerate)

Type generation fails

Verify schema syntax with
```
npx prisma validate
```
Clear generated files and regenerate
Check for circular dependencies in relations

Next Steps

After implementing the database layer:

Add caching - Use Redis for frequently accessed data
Implement search - Add full-text search or Elasticsearch
Add monitoring - Track query performance and slow queries
Write tests - Unit tests for queries, integration tests for transactions
Document schema - Add comments to schema for team reference
Plan backups - Set up automated database backups

For additional reference material and decision trees, see:

references/orm-comparison.md - ORM selection guide
scripts/database-checklist.sh - Validation script

database-layer

NPX Install

Tags

SKILL.md Content

Resources

Database Layer Implementation

When to Use This Skill

Workflow

1. Discover Existing Database Infrastructure

2. Choose Database Technology

3. Design Schema

4. Configure Database Connection

5. Run Migrations

6. Generate Type-Safe Client

7. Implement Queries

8. Implement Transactions

9. Seed Development Data

10. Validate Implementation

Common Patterns

Soft Deletes

Optimistic Locking

Connection Pooling

Full-Text Search

Security Checklist

Performance Checklist

Troubleshooting

Migration fails with constraint violation

N+1 query detected

Connection pool exhausted

Type generation fails

Next Steps