kotlin-exposed-patterns
Comprehensive patterns for database access with JetBrains Exposed ORM, including DSL queries, DAO, transactions, and production-ready configuration.
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Installation Guide
How to use kotlin-exposed-patterns on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
kotlin-exposed-patterns
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches kotlin-exposed-patterns from affaan-m/everything-claude-code and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate kotlin-exposed-patterns. Access via /kotlin-exposed-patterns in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
Kotlin Exposed Patterns
Comprehensive patterns for database access with JetBrains Exposed ORM, including DSL queries, DAO, transactions, and production-ready configuration.
When to Use
- Setting up database access with Exposed
- Writing SQL queries using Exposed DSL or DAO
- Configuring connection pooling with HikariCP
- Creating database migrations with Flyway
- Implementing the repository pattern with Exposed
- Handling JSON columns and complex queries
How It Works
Exposed provides two query styles: DSL for direct SQL-like expressions and DAO for entity lifecycle management. HikariCP manages a pool of reusable database connections configured via HikariConfig. Flyway runs versioned SQL migration scripts at startup to keep the schema in sync. All database operations run inside newSuspendedTransaction blocks for coroutine safety and atomicity. The repository pattern wraps Exposed queries behind an interface so business logic stays decoupled from the data layer and tests can use an in-memory H2 database.
Examples
DSL Query
suspend fun findUserById(id: UUID): UserRow? =
newSuspendedTransaction {
UsersTable.selectAll()
.where { UsersTable.id eq id }
.map { it.toUser() }
.singleOrNull()
}
DAO Entity Usage
suspend fun createUser(request: CreateUserRequest): User =
newSuspendedTransaction {
UserEntity.new {
name = request.name
email = request.email
role = request.role
}.toModel()
}
HikariCP Configuration
val hikariConfig = HikariConfig().apply {
driverClassName = config.driver
jdbcUrl = config.url
username = config.username
password = config.password
maximumPoolSize = config.maxPoolSize
isAutoCommit = false
transactionIsolation = "TRANSACTION_READ_COMMITTED"
validate()
}
Database Setup
HikariCP Connection Pooling
// DatabaseFactory.kt
object DatabaseFactory {
fun create(config: DatabaseConfig): Database {
val hikariConfig = HikariConfig().apply {
driverClassName = config.driver
jdbcUrl = config.url
username = config.username
password = config.password
maximumPoolSize = config.maxPoolSize
isAutoCommit = false
transactionIsolation = "TRANSACTION_READ_COMMITTED"
validate()
}
return Database.connect(HikariDataSource(hikariConfig))
}
}
data class DatabaseConfig(
val url: String,
val driver: String = "org.postgresql.Driver",
val username: String = "",
val password: String = "",
val maxPoolSize: Int = 10,
)
Flyway Migrations
// FlywayMigration.kt
fun runMigrations(config: DatabaseConfig) {
Flyway.configure()
.dataSource(config.url, config.username, config.password)
.locations("classpath:db/migration")
.baselineOnMigrate(true)
.load()
.migrate()
}
// Application startup
fun Application.module() {
val config = DatabaseConfig(
url = environment.config.property("database.url").getString(),
username = environment.config.property("database.username").getString(),
password = environment.config.property("database.password").getString(),
)
runMigrations(config)
val database = DatabaseFactory.create(config)
// ...
}
Migration Files
-- src/main/resources/db/migration/V1__create_users.sql
CREATE TABLE users (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
name VARCHAR(100) NOT NULL,
email VARCHAR(255) NOT NULL UNIQUE,
role VARCHAR(20) NOT NULL DEFAULT 'USER',
metadata JSONB,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_users_role ON users(role);
Table Definitions
DSL Style Tables
// tables/UsersTable.kt
object UsersTable : UUIDTable("users") {
val name = varchar("name", 100)
val email = varchar("email", 255).uniqueIndex()
val role = enumerationByName<Role>("role", 20)
val metadata = jsonb<UserMetadata>("metadata", Json.Default).nullable()
val createdAt = timestampWithTimeZone("created_at").defaultExpression(CurrentTimestampWithTimeZone)
val updatedAt = timestampWithTimeZone("updated_at").defaultExpression(CurrentTimestampWithTimeZone)
}
object OrdersTable : UUIDTable("orders") {
val userId = uuid("user_id"List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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Reviews
- KKofi Chen★★★★★Dec 28, 2024
I recommend kotlin-exposed-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- SShikha Mishra★★★★★Dec 16, 2024
kotlin-exposed-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- CCarlos Okafor★★★★★Dec 16, 2024
Solid pick for teams standardizing on skills: kotlin-exposed-patterns is focused, and the summary matches what you get after install.
- IIsabella Reddy★★★★★Dec 12, 2024
Registry listing for kotlin-exposed-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
- CCarlos Mensah★★★★★Nov 19, 2024
kotlin-exposed-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- YYash Thakker★★★★★Nov 7, 2024
Useful defaults in kotlin-exposed-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- MMichael Gupta★★★★★Nov 7, 2024
kotlin-exposed-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.
- IIsabella Khan★★★★★Nov 3, 2024
kotlin-exposed-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.
- DDhruvi Jain★★★★★Oct 26, 2024
Registry listing for kotlin-exposed-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
- HHarper Nasser★★★★★Oct 26, 2024
kotlin-exposed-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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