golang-database-patterns

bobmatnyc/claude-mpm-skills · updated Apr 8, 2026

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$npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill golang-database-patterns
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summary

Go's database ecosystem provides multiple layers of abstraction for SQL database integration. From the standard library's database/sql to enhanced libraries like sqlx and PostgreSQL-optimized pgx, developers can choose the right tool for their performance and ergonomics needs.

skill.md

Go Database Patterns

Overview

Go's database ecosystem provides multiple layers of abstraction for SQL database integration. From the standard library's database/sql to enhanced libraries like sqlx and PostgreSQL-optimized pgx, developers can choose the right tool for their performance and ergonomics needs.

Key Features:

  • 🔌 database/sql: Standard interface for any SQL database
  • 🚀 sqlx: Convenience methods with struct scanning and named queries
  • 🐘 pgx: PostgreSQL-native driver with maximum performance
  • 📦 Repository Pattern: Interface-based data access for testability
  • 🔄 Migrations: Schema versioning with golang-migrate
  • Connection Pooling: Production-ready connection management
  • 🔒 Transaction Safety: Context-aware transaction handling

When to Use This Skill

Activate this skill when:

  • Building CRUD operations with type safety
  • Implementing data access layers for web services
  • Managing database schema evolution across environments
  • Optimizing database connection pooling for production
  • Testing database code with mock repositories
  • Handling concurrent database access patterns
  • Migrating from ORMs to SQL-first approaches
  • Integrating PostgreSQL-specific features (COPY, LISTEN/NOTIFY)

Core Database Libraries

Decision Tree: Choosing Your Database Library

┌─────────────────────────────────────┐
│ What database are you using?       │
└──────────────┬──────────────────────┘
    ┌──────────┴──────────┐
    │                     │
PostgreSQL            Other SQL DB
    │                     │
    ▼                     ▼
┌─────────────────┐   Use database/sql
│ Need max perf?  │   + sqlx for convenience
└─────┬───────────┘
   ┌──┴──┐
  Yes    No
   │      │
  pgx   sqlx + pq driver

Use database/sql when:

  • Working with any SQL database (MySQL, SQLite, PostgreSQL, etc.)
  • Need database portability
  • Want standard library stability with no dependencies

Use sqlx when:

  • Want convenience methods (Get, Select, StructScan)
  • Need named parameter queries
  • Using IN clause expansion
  • Prefer less boilerplate than database/sql

Use pgx when:

  • PostgreSQL-only application
  • Need maximum performance (30-50% faster than lib/pq)
  • Want advanced PostgreSQL features (COPY, LISTEN/NOTIFY, prepared statement caching)
  • Building high-throughput systems

database/sql: The Standard Foundation

Core Concepts:

package main

import (
    "context"
    "database/sql"
    "time"

    _ "github.com/lib/pq" // PostgreSQL driver
)

func setupDB(dsn string) (*sql.DB, error) {
    db, err := sql.Open("postgres", dsn)
    if err != nil {
        return nil, err
    }

    // Connection pooling configuration
    db.SetMaxOpenConns(25)                 // Max open connections
    db.SetMaxIdleConns(5)                  // Max idle connections
    db.SetConnMaxLifetime(5 * time.Minute) // Max connection lifetime
    db.SetConnMaxIdleTime(1 * time.Minute) // Max idle time

    // Verify connection
    ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
    defer cancel()

    if err := db.PingContext(ctx); err != nil {
        return nil, err
    }

    return db, nil
}

Key Patterns:

// Query single row
func GetUserByID(ctx context.Context, db *sql.DB, id int) (*User, error) {
    var user User
    query := `SELECT id, name, email, created_at FROM users WHERE id = $1`

    err := db.QueryRowContext(ctx, query, id).Scan(
        &user.ID, &user.Name, &user.Email, &user.CreatedAt,
    )

    if err == sql.ErrNoRows {
        return nil, ErrUserNotFound // Custom error
    }
    if err != nil {
        return nil, fmt.Errorf("query user: %w", err)
    }

    return &user, nil
}

// Query multiple rows
func ListActiveUsers(ctx context.Context, db *sql.DB) ([]User, error) {
    query := `SELECT id, name, email, created_at FROM users WHERE active = true`

    rows, err := db.QueryContext(ctx, query)
    if err != nil {
        return nil, fmt.Errorf("query users: %w", err)
    }
    defer rows.Close() // CRITICAL: Always close rows

    var users []User
    for rows.Next() {
        var user User
        if err := rows.Scan(&user.ID, &user.Name, &user.Email, &user.CreatedAt); err != nil {
            return nil, fmt.Errorf("scan user: %w", err)
        }
        users = append(users, user)
    }

    // Check for errors during iteration
    if err := rows.Err(); err != nil {
        return nil, fmt.Errorf("iterate users: %w", err)
    }

    return users, nil
}

sqlx: Ergonomic Extensions

Installation:

go get github.com/jmoiron/sqlx

Core Features:

package main

import (
    "context"

    "github.com/jmoiron/sqlx"
    _ "github.com/lib/pq"
)

type User struct {
    ID        int       `db:"id"`
    Name      string    `db:"name"`
    Email     string    `db:"email"`
    CreatedAt time.Time `db:"created_at"`
}

// Get single struct
func GetUserByID(ctx context.Context, db *sqlx.DB, id int) (*User, error) {
    var user User
    query := `SELECT id, name, email, created_at FROM users WHERE id = $1`

    err := db.GetContext(ctx, &user, query, id)
    if err == sql.ErrNoRows {
        return nil, ErrUserNotFound
    }
    return &user, err
}

// Select multiple structs
func ListUsers(ctx context.Context, db *sqlx.DB, limit int) ([]User, error)
how to use golang-database-patterns

How to use golang-database-patterns on Cursor

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1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add golang-database-patterns
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill golang-database-patterns

The skills CLI fetches golang-database-patterns from GitHub repository bobmatnyc/claude-mpm-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/golang-database-patterns

Reload or restart Cursor to activate golang-database-patterns. Access the skill through slash commands (e.g., /golang-database-patterns) or your agent's skill management interface.

Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.826 reviews
  • Dhruvi Jain· Dec 24, 2024

    Registry listing for golang-database-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Omar Li· Dec 12, 2024

    I recommend golang-database-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Kwame Huang· Dec 4, 2024

    Keeps context tight: golang-database-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Henry Perez· Nov 23, 2024

    golang-database-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Oshnikdeep· Nov 15, 2024

    golang-database-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ava Nasser· Nov 15, 2024

    We added golang-database-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Charlotte Garcia· Nov 3, 2024

    golang-database-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Soo Choi· Oct 22, 2024

    Registry listing for golang-database-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.

  • William Wang· Oct 14, 2024

    Useful defaults in golang-database-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Ganesh Mohane· Oct 6, 2024

    I recommend golang-database-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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