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Golang Database

Samuel BertheCommunityCreated by samberDistributed by Samuel Berthe

  • Skill
  • Tool integration
  • Software development
  • MIT
  • No issues found

From the author

Comprehensive guide for Go database access — parameterized queries, struct scanning, NULLable columns, transactions, isolation levels, SELECT FOR UPDATE, connection pool, batch processing, context propagation, and migration tooling. Use when writing, reviewing, or debugging Golang code that interacts with PostgreSQL, MariaDB, MySQL, or SQLite; for database testing; or for questions about database/sql, sqlx, or pgx. Does NOT generate database schemas or migration SQL.
— the description by samber

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a set of best practices for interacting with databases in Go using standard libraries like database/sql, sqlx, or pgx. It emphasizes explicit SQL usage over ORMs, focusing on security, performance, and maintainability. The guide covers essential topics including parameterized queries to prevent SQL injection, proper context propagation, transaction management, connection pool configuration, and robust error handling. It is designed for backend engineers who prioritize observable and reliable database code.

What it does

  • Provides patterns for secure, parameterized SQL queries to prevent injection.
  • Outlines best practices for struct scanning and handling NULLable database columns.
  • Defines standards for transaction management and isolation levels.
  • Explains how to configure and monitor database connection pools for performance.
  • Details proper error handling and context propagation for database operations.
  • Offers guidance on choosing between database/sql, sqlx, and pgx.

When to use it

  • When writing new repository functions or query helpers in Go.
  • When auditing existing Go code for database-related bugs or security vulnerabilities.
  • When debugging performance issues related to connection pooling or query execution.
  • When determining the best approach for mapping database rows to Go structs.

Advantages

  • Promotes explicit, readable SQL that is easier to debug and test.
  • Reduces the risk of SQL injection through mandatory parameterization.
  • Improves application reliability by enforcing proper resource management like closing rows.
  • Helps optimize database performance through correct connection pool settings.

Usage examples

“How do I safely query a user by email in Go without using an ORM?”
The agent will provide a code snippet using db.GetContext with a parameterized placeholder ($1 or ?) to ensure the query is safe from SQL injection.
“Review this code for database connection leaks.”
The agent will scan the provided code for missing defer rows.Close() calls or improper use of db.Query instead of db.Exec.
“How should I handle a NULLable column in my database struct?”
The agent will recommend using pointer fields (e.g., *string) for struct members and explain how they interact with database scanning and JSON marshaling.
“What are the recommended settings for my database connection pool?”
The agent will provide a configuration block for SetMaxOpenConns, SetMaxIdleConns, and related methods, explaining the trade-offs for each.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/samber/golang-database/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip golang-database.zip -d .agents/skills

Documentation by samber

Persona: You are a Go backend engineer who writes safe, explicit, and observable database code. You treat SQL as a first-class language — no ORMs, no magic — and you catch data integrity issues at the boundary, not deep in the application.

Modes:

  • Write mode — generating new repository functions, query helpers, or transaction wrappers: follow the skill's sequential instructions; launch a background agent to grep for existing query patterns and naming conventions in the codebase before generating new code.

  • Review/debug mode — auditing or debugging existing database code: use a sub-agent to scan for missing rows.Close(), un-parameterized queries, missing context propagation, and absent error checks in parallel with reading the business logic.

Community default. A company skill that explicitly supersedes samber/cc-skills-golang@golang-database skill takes precedence.

Go Database Best Practices

Go's database/sql provides a solid foundation for database access. Use sqlx or pgx on top of it for ergonomics — never an ORM.

When using sqlx or pgx, refer to the library's official documentation and code examples for current API signatures.

Best Practices Summary

  1. Use sqlx or pgx, not ORMs — ORMs hide SQL, generate unpredictable queries, and make debugging harder

  2. Queries MUST use parameterized placeholders — NEVER concatenate user input into SQL strings

  3. Context MUST be passed to all database operations — use *Context method variants (QueryContext, ExecContext, GetContext)

  4. sql.ErrNoRows MUST be handled explicitly — distinguish "not found" from real errors using errors.Is

  5. Rows MUST be closed after iteration — defer rows.Close() immediately after QueryContext calls

  6. NEVER use db.Query for statements that don't return rows — Query returns *Rows which must be closed; if you forget, the connection leaks back to the pool. Use db.Exec instead

  7. Use transactions for multi-statement operations — wrap related writes in BeginTxx/Commit

  8. Use SELECT ... FOR UPDATE when reading data you intend to modify — prevents race conditions

  9. Set custom isolation levels when default READ COMMITTED is insufficient (e.g., serializable for financial operations)

  10. Handle NULLable columns with pointer fields (*string, *int) or sql.NullXxx types

  11. Connection pool MUST be configured — SetMaxOpenConns, SetMaxIdleConns, SetConnMaxLifetime, SetConnMaxIdleTime

  12. Use external tools for migrations — golang-migrate or Flyway, never hand-rolled or AI-generated migration SQL

  13. Batch operations in reasonable sizes — not row-by-row (too many round trips), not millions at once (locks and memory)

  14. Never create or modify database schemas — a schema that looks correct on toy data can create hotspots, lock contention, or missing indexes under real production load. Schema design requires understanding of data volumes, access patterns, and production constraints that AI does not have

  15. Avoid hidden SQL features — do not rely on triggers, views, materialized views, stored procedures, or row-level security in application code

Library Choice

LibraryBest forStruct scanningPostgreSQL-specific
database/sqlPortability, minimal depsManual ScanNo
sqlxMulti-database projectsStructScanNo
pgxPostgreSQL (30-50% faster)pgx.RowToStructByNameYes (COPY, LISTEN, arrays)
GORM/entAvoidMagicAbstracted away

Why NOT ORMs:

  • Unpredictable query generation — N+1 problems you cannot see in code

  • Magic hooks and callbacks (BeforeCreate, AfterUpdate) make debugging harder

  • Schema migrations coupled to application code

  • Learning the ORM API is harder than learning SQL, and the abstraction leaks

Parameterized Queries

// ✗ VERY BAD — SQL injection vulnerability
query := fmt.Sprintf("SELECT * FROM users WHERE email = '%s'", email)

// ✓ Good — parameterized (PostgreSQL)
var user User
err := db.GetContext(ctx, &user, "SELECT id, name, email FROM users WHERE email = $1", email)

// ✓ Good — parameterized (MySQL)
err := db.GetContext(ctx, &user, "SELECT id, name, email FROM users WHERE email = ?", email)
Dynamic IN clauses
query, args, err := sqlx.In("SELECT * FROM users WHERE id IN (?)", ids)
if err != nil {
    return fmt.Errorf("building IN clause: %w", err)
}
query = db.Rebind(query) // adjust placeholders for your driver
err = db.SelectContext(ctx, &users, query, args...)
Dynamic column names

Never interpolate column names from user input. Use an allowlist:

allowed := map[string]bool{"name": true, "email": true, "created_at": true}
if !allowed[sortCol] {
    return fmt.Errorf("invalid sort column: %s", sortCol)
}
query := fmt.Sprintf("SELECT id, name, email FROM users ORDER BY %s", sortCol)

For more injection prevention patterns, see the samber/cc-skills-golang@golang-security skill.

Struct Scanning and NULLable Columns

Use db:"column_name" tags for sqlx, pgx.CollectRows with pgx.RowToStructByName for pgx. Handle NULLable columns with pointer fields (*string, *time.Time) — they work cleanly with both scanning and JSON marshaling. See Scanning Reference for examples of all approaches.

Error Handling

func GetUser(id string) (*User, error) {
    var user User

    err := db.GetContext(ctx, &user, "SELECT id, name FROM users WHERE id = $1", id)
    if err != nil {
        if errors.Is(err, sql.ErrNoRows) {
            return nil, ErrUserNotFound // translate to domain error
        }
        return nil, fmt.Errorf("querying user %s: %w", id, err)
    }

    return &user, nil
}

or:

func GetUser(id string) (u *User, exists bool, err error) {
    var user User

    err := db.GetContext(ctx, &user, "SELECT id, name FROM users WHERE id = $1", id)
    if err != nil {
        if errors.Is(err, sql.ErrNoRows) {
            return nil, false, nil // "no user" is not a technical error, but a domain error
        }
        return nil, false, fmt.Errorf("querying user %s: %w", id, err)
    }

    return &user, true, nil
}
Always close rows
rows, err := db.QueryContext(ctx, "SELECT id, name FROM users")
if err != nil {
    return fmt.Errorf("querying users: %w", err)
}
defer rows.Close() // prevents connection leaks

for rows.Next() {
    // ...
}
if err := rows.Err(); err != nil { // always check after iteration
    return fmt.Errorf("iterating users: %w", err)
}
Common database error patterns
ErrorHow to detectAction
Row not founderrors.Is(err, sql.ErrNoRows)Return domain error
Unique constraintCheck driver-specific error codeReturn conflict error
Connection refusederr != nil on db.PingContextFail fast, log, retry with backoff
Serialization failurePostgreSQL error code 40001Retry the entire transaction
Context cancelederrors.Is(err, context.Canceled)Stop processing, propagate

Context Propagation

Always use the *Context method variants to propagate deadlines and cancellation:

// ✗ Bad — no context, query runs until completion even if client disconnects
db.Query("SELECT ...")

// ✓ Good — respects context cancellation and timeouts
db.QueryContext(ctx, "SELECT ...")

For context patterns in depth, see the samber/cc-skills-golang@golang-context skill.

Transactions, Isolation Levels, and Locking

For transaction patterns, isolation levels, SELECT FOR UPDATE, and locking variants, see Transactions.

Connection Pool

db.SetMaxOpenConns(25)              // limit total connections
db.SetMaxIdleConns(10)              // keep warm connections ready
db.SetConnMaxLifetime(5 * time.Minute)  // recycle stale connections
db.SetConnMaxIdleTime(1 * time.Minute)  // close idle connections faster

For sizing guidance and formulas, see Database Performance.

Migrations

Use an external migration tool. Schema changes require human review with understanding of data volumes, existing indexes, foreign keys, and production constraints.

Recommended tools:

  • golang-migrate — CLI + Go library, supports all major databases

  • Flyway — JVM-based, widely used in enterprise environments

  • Atlas — modern, declarative schema management

Migration SQL should be written and reviewed by humans, versioned in source control, and applied through CI/CD pipelines.

Avoid Hidden SQL Features

Do not rely on triggers, views, materialized views, stored procedures, or row-level security in application code — they create invisible side effects and make debugging impossible. Keep SQL explicit and visible in Go where it can be tested and version-controlled.

Schema Creation

This skill does NOT cover schema creation. AI-generated schemas are often subtly wrong — missing indexes, incorrect column types, bad normalization, or missing constraints. Schema design requires understanding data volumes, access patterns, query profiles, and business constraints. Use dedicated database tooling and human review.

Deep Dives

  • Transactions — Transaction boundaries, isolation levels, deadlock prevention, SELECT FOR UPDATE

  • Testing Database Code — Mock connections, integration tests with containers, fixtures, schema setup/teardown

  • Database Performance — Connection pool sizing, batch processing, indexing strategy, query optimization

  • Struct Scanning — Struct tags, NULLable column handling, JSON marshaling patterns

Cross-References

  • → See samber/cc-skills-golang@golang-security skill for SQL injection prevention patterns

  • → See samber/cc-skills-golang@golang-context skill for context propagation to database operations

  • → See samber/cc-skills-golang@golang-error-handling skill for database error wrapping patterns

  • → See samber/cc-skills-golang@golang-testing skill for database integration test patterns

References

Files

references/performance.md

Database Performance

Table of Contents

  • Connection Pool Sizing

    • Configuration

    • Monitoring

    • Prometheus Metrics

  • Batch Processing

    • Sweet spot: 100–1,000 rows per batch

    • Batch INSERT with sqlx

    • Bulk INSERT with pgx (PostgreSQL COPY protocol)

    • Cursor-based pagination (avoid OFFSET)

  • Indexing Strategy

    • Use SQL MCP to check existing indexes

    • When to suggest adding indexes

    • When to suggest removing indexes

  • Query Performance Tips

Connection Pool Sizing

Configuration
db, err := sqlx.Connect("postgres", dsn)
if err != nil {
    return fmt.Errorf("connecting to database: %w", err)
}

db.SetMaxOpenConns(25)                  // total connections (match your DB capacity)
db.SetMaxIdleConns(10)                  // keep connections warm, reduce handshake overhead
db.SetConnMaxLifetime(5 * time.Minute)  // recycle connections (DNS changes, server restarts)
db.SetConnMaxIdleTime(1 * time.Minute)  // release idle connections back to the pool
SettingToo lowToo high
MaxOpenConnsRequests queue waiting for connDB overwhelmed, context switches
MaxIdleConnsCold connections, slow queriesWasted memory holding idle conns
ConnMaxLifetimeFrequent reconnection overheadStale connections after failover
ConnMaxIdleTimeSame as MaxIdleConns too lowIdle conns consume server memory
Monitoring

Check pool stats in production to detect exhaustion:

stats := db.Stats()
slog.Info("db pool",
    "open", stats.OpenConnections,
    "in_use", stats.InUse,
    "idle", stats.Idle,
    "wait_count", stats.WaitCount,        // total waits for a connection
    "wait_duration", stats.WaitDuration,  // total wait time
)

If WaitCount keeps climbing, increase MaxOpenConns or optimize slow queries.

Prometheus Metrics

Use a custom Prometheus collector to export pool metrics on-demand (scales to multiple pools automatically):

type DBCollector struct {
    pools map[string]*sqlx.DB
}

func NewDBCollector(pools map[string]*sqlx.DB) *DBCollector {
    return &DBCollector{pools: pools}
}

func (c *DBCollector) Describe(ch chan<- *prometheus.Desc) {
    ch <- prometheus.NewDesc("db_open_connections", "Number of open connections", []string{"pool"}, nil)
    ch <- prometheus.NewDesc("db_in_use_connections", "Connections currently in use", []string{"pool"}, nil)
    ch <- prometheus.NewDesc("db_idle_connections", "Idle connections in pool", []string{"pool"}, nil)
    ch <- prometheus.NewDesc("db_total_latency_seconds", "Total latency for a connection", []string{"pool"}, nil)
}

func (c *DBCollector) Collect(ch chan<- prometheus.Metric) {
    for poolName, db := range c.pools {
        stats := db.Stats()

        ch <- prometheus.MustNewConstMetric(
            prometheus.NewDesc("db_open_connections", "Number of open connections", []string{"pool"}, nil),
            prometheus.GaugeValue, float64(stats.OpenConnections), poolName)

        ch <- prometheus.MustNewConstMetric(
            prometheus.NewDesc("db_in_use_connections", "Connections currently in use", []string{"pool"}, nil),
            prometheus.GaugeValue, float64(stats.InUse), poolName)

        ch <- prometheus.MustNewConstMetric(
            prometheus.NewDesc("db_idle_connections", "Idle connections in pool", []string{"pool"}, nil),
            prometheus.GaugeValue, float64(stats.Idle), poolName)

        ch <- prometheus.MustNewConstMetric(
            prometheus.NewDesc("db_wait_duration_seconds_total", "Total connection wait duration", []string{"pool"}, nil),
            prometheus.CounterValue, stats.WaitDuration.Seconds(), poolName)
    }
}

func init() {
    pools := map[string]*sqlx.DB{
        "primary": mainDB,
        "replica": replicaDB,
    }
    prometheus.MustRegister(NewDBCollector(pools))
}

Collector advantages:

  • Metrics are collected on-demand during scrapes (no background goroutine)

  • Always returns current state (no stale data between scrapes)

  • Scales to multiple pools automatically

  • Lower memory footprint (no metric state in memory)

Alert thresholds:

  • Open connections approaching MaxOpenConns → risk of request queuing

  • Wait count climbing steadily → pool is exhausted, increase MaxOpenConns

  • Idle connections too high → reduce MaxIdleConns or lower ConnMaxIdleTime

Batch Processing

Avoid two extremes:

  • Row-by-row — N round trips for N rows, extremely slow

  • One giant batch — locks tables, consumes memory, can timeout and block other queries

Sweet spot: 100–1,000 rows per batch

Adjust based on row size and database load. Larger rows → smaller batches.

Batch INSERT with sqlx
func insertUsersBatch(ctx context.Context, db *sqlx.DB, users []User) error {
    const batchSize = 500
    for i := 0; i < len(users); i += batchSize {
        end := min(i+batchSize, len(users))
        batch := users[i:end]

        _, err := db.NamedExecContext(ctx, `INSERT INTO users (name, email) VALUES (:name, :email)`, batch)
        if err != nil {
            return fmt.Errorf("inserting users batch %d-%d: %w", i, end, err)
        }
    }
    return nil
}
Bulk INSERT with pgx (PostgreSQL COPY protocol)

For maximum throughput on PostgreSQL, use pgx.CopyFrom which uses the binary COPY protocol — significantly faster than multi-row INSERT:

rows := make([][]any, len(users))
for i, u := range users {
    rows[i] = []any{u.Name, u.Email}
}
_, err := pool.CopyFrom(ctx,
    pgx.Identifier{"users"},
    []string{"name", "email"},
    pgx.CopyFromRows(rows),
)
Cursor-based pagination (avoid OFFSET)

For reading large datasets, use cursor-based pagination instead of OFFSET. OFFSET re-scans skipped rows, getting slower as you paginate deeper:

// ✗ Bad — OFFSET re-scans rows, O(offset + limit)
SELECT * FROM events ORDER BY created_at LIMIT 100 OFFSET 10000

// ✓ Good — cursor-based, O(limit) regardless of depth
SELECT * FROM events WHERE created_at > $1 ORDER BY created_at LIMIT 100

Indexing Strategy

Never create or drop indexes yourself. Index changes affect production query performance and write throughput. Always suggest to the developer and let them decide.

Use SQL MCP to check existing indexes

When a SQL MCP tool is available, query the database to check existing indexes before suggesting new ones:

-- PostgreSQL: list indexes on a table
SELECT indexname, indexdef
FROM pg_indexes
WHERE tablename = 'users';

-- Check for unused indexes (low scan count relative to writes)
SELECT schemaname, relname, indexrelname, idx_scan, idx_tup_read
FROM pg_stat_user_indexes
WHERE idx_scan < 10
ORDER BY idx_scan;
When to suggest adding indexes
  • Foreign key columns (PostgreSQL does NOT auto-index foreign keys)

  • Columns frequently used in WHERE, JOIN, or ORDER BY

  • Composite indexes for multi-column queries (leftmost column is most selective)

  • Partial indexes for filtered queries (WHERE active = true)

When to suggest removing indexes
  • Indexes with near-zero idx_scan count (nobody reads them)

  • Duplicate indexes (same columns in same order)

  • Indexes on write-heavy tables that slow down INSERT/UPDATE/DELETE

  • Wide composite indexes where a narrower one would suffice

Always present findings as suggestions with data (scan counts, table size), never execute DDL yourself.

Query Performance Tips

  • EXPLAIN ANALYZE before optimizing — measure, don't guess

  • List columns explicitly — avoid SELECT *, it fetches unnecessary data and breaks struct scanning when schema changes

  • Use LIMIT for pagination, always with an ORDER BY

  • Prefer EXISTS over COUNT for existence checks — EXISTS stops at the first match

  • Avoid N+1 queries — use JOIN or batch WHERE id IN (...) instead of querying in a loop

  • Suggest improvements, never execute them — performance changes (indexes, query rewrites, configuration) need human review in context of production data and workload patterns

Rules:

  • Batch operations SHOULD use 100–1,000 rows per batch — adjust based on row size and database load.

  • Cursor-based pagination MUST replace OFFSET for large datasets — the cursor column MUST be chosen based on actual indexes (e.g., created_at, user_id).

  • NEVER create indexes blindly — check existing indexes, measure with EXPLAIN ANALYZE, and present findings as suggestions.

  • N+1 queries MUST be eliminated — use JOIN or batch WHERE id IN (...).

→ See samber/cc-skills-golang@golang-observability skill for database metrics and query monitoring. → See samber/cc-skills@promql-cli skill for querying pool metrics (db_open_connections, db_in_use_connections, db_idle_connections) via CLI.

Requirements and compatibility

Written for: Claude Code, OpenAI Codex

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Claude Code frontmatter

The author says: Designed for Claude Code, Codex or similar harness, and for projects using Golang.

Security

No issues found by our static scan· No issues found

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Attribution and licence

Created by
samber
Publisher
Samuel Berthe (Community)
Distributed by
Samuel Berthe
Source
samber/cc-skills-golang · skills/golang-database · commit bb1d43d
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

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Download ZIP

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