Comprehensive patterns for database access with JetBrains Exposed ORM, including DSL queries, DAO, transactions, and production-ready configuration.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionkotlin-exposed-patternsExecute 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.
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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.
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.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Comprehensive patterns for database access with JetBrains Exposed ORM, including DSL queries, DAO, transactions, and production-ready configuration.
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.
suspend fun findUserById(id: UUID): UserRow? =
newSuspendedTransaction {
UsersTable.selectAll()
.where { UsersTable.id eq id }
.map { it.toUser() }
.singleOrNull()
}
suspend fun createUser(request: CreateUserRequest): User =
newSuspendedTransaction {
UserEntity.new {
name = request.name
email = request.email
role = request.role
}.toModel()
}
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()
}
// 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,
)
// 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)
// ...
}
-- 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);
// 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"Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
I recommend kotlin-exposed-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
kotlin-exposed-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: kotlin-exposed-patterns is focused, and the summary matches what you get after install.
Registry listing for kotlin-exposed-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
kotlin-exposed-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in kotlin-exposed-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
kotlin-exposed-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.
kotlin-exposed-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for kotlin-exposed-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
kotlin-exposed-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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