---
title: "SQL Database Assistant - POWERFUL Tier Skill — Agent Skill for Codex & OpenClaw"
description: "Use when the user asks to write SQL queries, optimize database performance, generate migrations, explore database schemas, or work with ORMs like. Agent skill for Claude Code, Codex CLI, Gemini CLI, OpenClaw."
---

# SQL Database Assistant - POWERFUL Tier Skill

<div class="page-meta" markdown>
<span class="meta-badge">:material-rocket-launch: Engineering - POWERFUL</span>
<span class="meta-badge">:material-identifier: `sql-database-assistant`</span>
<span class="meta-badge">:material-github: <a href="https://github.com/alirezarezvani/claude-skills/tree/main/engineering/sql-database-assistant/SKILL.md">Source</a></span>
</div>

<div class="install-banner" markdown>
<span class="install-label">Install:</span> <code>claude /plugin install engineering-advanced-skills</code>
</div>


## Overview

The operational companion to database design. While **database-designer** focuses on schema architecture and **database-schema-designer** handles ERD modeling, this skill covers the day-to-day: writing queries, optimizing performance, generating migrations, and bridging the gap between application code and database engines.

### Core Capabilities

- **Natural Language to SQL** — translate requirements into correct, performant queries
- **Schema Exploration** — introspect live databases across PostgreSQL, MySQL, SQLite, SQL Server
- **Query Optimization** — EXPLAIN analysis, index recommendations, N+1 detection, rewrite patterns
- **Migration Generation** — up/down scripts, zero-downtime strategies, rollback plans
- **ORM Integration** — Prisma, Drizzle, TypeORM, SQLAlchemy patterns and escape hatches
- **Multi-Database Support** — dialect-aware SQL with compatibility guidance

### Tools

| Script | Purpose |
|--------|---------|
| `scripts/query_optimizer.py` | Static analysis of SQL queries for performance issues |
| `scripts/migration_generator.py` | Generate migration file templates from change descriptions |
| `scripts/schema_explorer.py` | Generate schema documentation from introspection queries |

---

## Natural Language to SQL

### Translation Patterns

When converting requirements to SQL, follow this sequence:

1. **Identify entities** — map nouns to tables
2. **Identify relationships** — map verbs to JOINs or subqueries
3. **Identify filters** — map adjectives/conditions to WHERE clauses
4. **Identify aggregations** — map "total", "average", "count" to GROUP BY
5. **Identify ordering** — map "top", "latest", "highest" to ORDER BY + LIMIT

### Common Query Templates

**Top-N per group (window function)**
```sql
SELECT * FROM (
  SELECT *, ROW_NUMBER() OVER (PARTITION BY department_id ORDER BY salary DESC) AS rn
  FROM employees
) ranked WHERE rn <= 3;
```

**Running totals**
```sql
SELECT date, amount,
  SUM(amount) OVER (ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS running_total
FROM transactions;
```

**Gap detection**
```sql
SELECT curr.id, curr.seq_num, prev.seq_num AS prev_seq
FROM records curr
LEFT JOIN records prev ON prev.seq_num = curr.seq_num - 1
WHERE prev.id IS NULL AND curr.seq_num > 1;
```

**UPSERT (PostgreSQL)**
```sql
INSERT INTO settings (key, value, updated_at)
VALUES ('theme', 'dark', NOW())
ON CONFLICT (key) DO UPDATE SET value = EXCLUDED.value, updated_at = EXCLUDED.updated_at;
```

**UPSERT (MySQL)**
```sql
INSERT INTO settings (key_name, value, updated_at)
VALUES ('theme', 'dark', NOW())
ON DUPLICATE KEY UPDATE value = VALUES(value), updated_at = VALUES(updated_at);
```

> See references/query_patterns.md for JOINs, CTEs, window functions, JSON operations, and more.

---

## Schema Exploration

### Introspection Queries

**PostgreSQL — list tables and columns**
```sql
SELECT table_name, column_name, data_type, is_nullable, column_default
FROM information_schema.columns
WHERE table_schema = 'public'
ORDER BY table_name, ordinal_position;
```

**PostgreSQL — foreign keys**
```sql
SELECT tc.table_name, kcu.column_name,
  ccu.table_name AS foreign_table, ccu.column_name AS foreign_column
FROM information_schema.table_constraints tc
JOIN information_schema.key_column_usage kcu ON tc.constraint_name = kcu.constraint_name
JOIN information_schema.constraint_column_usage ccu ON tc.constraint_name = ccu.constraint_name
WHERE tc.constraint_type = 'FOREIGN KEY';
```

**MySQL — table sizes**
```sql
SELECT table_name, table_rows,
  ROUND(data_length / 1024 / 1024, 2) AS data_mb,
  ROUND(index_length / 1024 / 1024, 2) AS index_mb
FROM information_schema.tables
WHERE table_schema = DATABASE()
ORDER BY data_length DESC;
```

**SQLite — schema dump**
```sql
SELECT name, sql FROM sqlite_master WHERE type = 'table' ORDER BY name;
```

**SQL Server — columns with types**
```sql
SELECT t.name AS table_name, c.name AS column_name,
  ty.name AS data_type, c.max_length, c.is_nullable
FROM sys.columns c
JOIN sys.tables t ON c.object_id = t.object_id
JOIN sys.types ty ON c.user_type_id = ty.user_type_id
ORDER BY t.name, c.column_id;
```

### Generating Documentation from Schema

Use `scripts/schema_explorer.py` to produce markdown or JSON documentation:

```bash
python scripts/schema_explorer.py --dialect postgres --tables all --format md
python scripts/schema_explorer.py --dialect mysql --tables users,orders --format json --json
```

---

## Query Optimization

### EXPLAIN Analysis Workflow

1. **Run EXPLAIN ANALYZE** (PostgreSQL) or **EXPLAIN FORMAT=JSON** (MySQL)
2. **Identify the costliest node** — Seq Scan on large tables, Nested Loop with high row estimates
3. **Check for missing indexes** — sequential scans on filtered columns
4. **Look for estimation errors** — planned vs actual rows divergence signals stale statistics
5. **Evaluate JOIN order** — ensure the smallest result set drives the join

### Index Recommendation Checklist

- Columns in WHERE clauses with high selectivity
- Columns in JOIN conditions (foreign keys)
- Columns in ORDER BY when combined with LIMIT
- Composite indexes matching multi-column WHERE predicates (most selective column first)
- Partial indexes for queries with constant filters (e.g., `WHERE status = 'active'`)
- Covering indexes to avoid table lookups for read-heavy queries

### Query Rewriting Patterns

| Anti-Pattern | Rewrite |
|-------------|---------|
| `SELECT * FROM orders` | `SELECT id, status, total FROM orders` (explicit columns) |
| `WHERE YEAR(created_at) = 2025` | `WHERE created_at >= '2025-01-01' AND created_at < '2026-01-01'` (sargable) |
| Correlated subquery in SELECT | LEFT JOIN with aggregation |
| `NOT IN (SELECT ...)` with NULLs | `NOT EXISTS (SELECT 1 ...)` |
| `UNION` (dedup) when not needed | `UNION ALL` |
| `LIKE '%search%'` | Full-text search index (GIN/FULLTEXT) |
| `ORDER BY RAND()` | Application-side random sampling or `TABLESAMPLE` |

### N+1 Detection

**Symptoms:**
- Application loop that executes one query per parent row
- ORM lazy-loading related entities inside a loop
- Query log shows hundreds of identical SELECT patterns with different IDs

**Fixes:**
- Use eager loading (`include` in Prisma, `joinedload` in SQLAlchemy)
- Batch queries with `WHERE id IN (...)`
- Use DataLoader pattern for GraphQL resolvers

### Static Analysis Tool

```bash
python scripts/query_optimizer.py --query "SELECT * FROM orders WHERE status = 'pending'" --dialect postgres
python scripts/query_optimizer.py --query queries.sql --dialect mysql --json
```

> See references/optimization_guide.md for EXPLAIN plan reading, index types, and connection pooling.

---

## Migration Generation

### Zero-Downtime Migration Patterns

**Adding a column (safe)**
```sql
-- Up
ALTER TABLE users ADD COLUMN phone VARCHAR(20);

-- Down
ALTER TABLE users DROP COLUMN phone;
```

**Renaming a column (expand-contract)**
```sql
-- Step 1: Add new column
ALTER TABLE users ADD COLUMN full_name VARCHAR(255);
-- Step 2: Backfill
UPDATE users SET full_name = name;
-- Step 3: Deploy app reading both columns
-- Step 4: Deploy app writing only new column
-- Step 5: Drop old column
ALTER TABLE users DROP COLUMN name;
```

**Adding a NOT NULL column (safe sequence)**
```sql
-- Step 1: Add nullable
ALTER TABLE orders ADD COLUMN region VARCHAR(50);
-- Step 2: Backfill with default
UPDATE orders SET region = 'unknown' WHERE region IS NULL;
-- Step 3: Add constraint
ALTER TABLE orders ALTER COLUMN region SET NOT NULL;
ALTER TABLE orders ALTER COLUMN region SET DEFAULT 'unknown';
```

**Index creation (non-blocking, PostgreSQL)**
```sql
CREATE INDEX CONCURRENTLY idx_orders_status ON orders (status);
```

### Data Backfill Strategies

- **Batch updates** — process in chunks of 1000-10000 rows to avoid lock contention
- **Background jobs** — run backfills asynchronously with progress tracking
- **Dual-write** — write to old and new columns during transition period
- **Validation queries** — verify row counts and data integrity after each batch

### Rollback Strategies

Every migration must have a reversible down script. For irreversible changes:

1. **Backup before execution** — `pg_dump` the affected tables
2. **Feature flags** — application can switch between old/new schema reads
3. **Shadow tables** — keep a copy of the original table during migration window

### Migration Generator Tool

```bash
python scripts/migration_generator.py --change "add email_verified boolean to users" --dialect postgres --format sql
python scripts/migration_generator.py --change "rename column name to full_name in customers" --dialect mysql --format alembic --json
```

---

## Multi-Database Support

### Dialect Differences

| Feature | PostgreSQL | MySQL | SQLite | SQL Server |
|---------|-----------|-------|--------|------------|
| UPSERT | `ON CONFLICT DO UPDATE` | `ON DUPLICATE KEY UPDATE` | `ON CONFLICT DO UPDATE` | `MERGE` |
| Boolean | Native `BOOLEAN` | `TINYINT(1)` | `INTEGER` | `BIT` |
| Auto-increment | `SERIAL` / `GENERATED` | `AUTO_INCREMENT` | `INTEGER PRIMARY KEY` | `IDENTITY` |
| JSON | `JSONB` (indexed) | `JSON` | Text (ext) | `NVARCHAR(MAX)` |
| Array | Native `ARRAY` | Not supported | Not supported | Not supported |
| CTE (recursive) | Full support | 8.0+ | 3.8.3+ | Full support |
| Window functions | Full support | 8.0+ | 3.25.0+ | Full support |
| Full-text search | `tsvector` + GIN | `FULLTEXT` index | FTS5 extension | Full-text catalog |
| LIMIT/OFFSET | `LIMIT n OFFSET m` | `LIMIT n OFFSET m` | `LIMIT n OFFSET m` | `OFFSET m ROWS FETCH NEXT n ROWS ONLY` |

### Compatibility Tips

- **Always use parameterized queries** — prevents SQL injection across all dialects
- **Avoid dialect-specific functions in shared code** — wrap in adapter layer
- **Test migrations on target engine** — `information_schema` varies between engines
- **Use ISO date format** — `'YYYY-MM-DD'` works everywhere
- **Quote identifiers** — use double quotes (SQL standard) or backticks (MySQL)

---

## ORM Patterns

### Prisma

**Schema definition**
```prisma
model User {
  id        Int      @id @default(autoincrement())
  email     String   @unique
  name      String?
  posts     Post[]
  createdAt DateTime @default(now())
}

model Post {
  id       Int    @id @default(autoincrement())
  title    String
  author   User   @relation(fields: [authorId], references: [id])
  authorId Int
}
```

**Migrations**: `npx prisma migrate dev --name add_user_email`
**Query API**: `prisma.user.findMany({ where: { email: { contains: '@' } }, include: { posts: true } })`
**Raw SQL escape hatch**: `prisma.$queryRaw\`SELECT * FROM users WHERE id = ${userId}\``

### Drizzle

**Schema-first definition**
```typescript
export const users = pgTable('users', {
  id: serial('id').primaryKey(),
  email: varchar('email', { length: 255 }).notNull().unique(),
  name: text('name'),
  createdAt: timestamp('created_at').defaultNow(),
});
```

**Query builder**: `db.select().from(users).where(eq(users.email, email))`
**Migrations**: `npx drizzle-kit generate:pg` then `npx drizzle-kit push:pg`

### TypeORM

**Entity decorators**
```typescript
@Entity()
export class User {
  @PrimaryGeneratedColumn()
  id: number;

  @Column({ unique: true })
  email: string;

  @OneToMany(() => Post, post => post.author)
  posts: Post[];
}
```

**Repository pattern**: `userRepo.find({ where: { email }, relations: ['posts'] })`
**Migrations**: `npx typeorm migration:generate -n AddUserEmail`

### SQLAlchemy

**Declarative models**
```python
class User(Base):
    __tablename__ = 'users'
    id = Column(Integer, primary_key=True)
    email = Column(String(255), unique=True, nullable=False)
    name = Column(String(255))
    posts = relationship('Post', back_populates='author')
```

**Session management**: Always use `with Session() as session:` context manager
**Alembic migrations**: `alembic revision --autogenerate -m "add user email"`

> See references/orm_patterns.md for side-by-side comparisons and migration workflows per ORM.

---

## Data Integrity

### Constraint Strategy

- **Primary keys** — every table must have one; prefer surrogate keys (serial/UUID)
- **Foreign keys** — enforce referential integrity; define ON DELETE behavior explicitly
- **UNIQUE constraints** — for business-level uniqueness (email, slug, API key)
- **CHECK constraints** — validate ranges, enums, and business rules at the DB level
- **NOT NULL** — default to NOT NULL; make nullable only when genuinely optional

### Transaction Isolation Levels

| Level | Dirty Read | Non-Repeatable Read | Phantom Read | Use Case |
|-------|-----------|-------------------|-------------|----------|
| READ UNCOMMITTED | Yes | Yes | Yes | Never recommended |
| READ COMMITTED | No | Yes | Yes | Default for PostgreSQL, general OLTP |
| REPEATABLE READ | No | No | Yes (InnoDB: No) | Financial calculations |
| SERIALIZABLE | No | No | No | Critical consistency (billing, inventory) |

### Deadlock Prevention

1. **Consistent lock ordering** — always acquire locks in the same table/row order
2. **Short transactions** — minimize time between first lock and commit
3. **Advisory locks** — use `pg_advisory_lock()` for application-level coordination
4. **Retry logic** — catch deadlock errors and retry with exponential backoff

---

## Backup & Restore

### PostgreSQL
```bash
# Full backup
pg_dump -Fc --no-owner dbname > backup.dump
# Restore
pg_restore -d dbname --clean --no-owner backup.dump
# Point-in-time recovery: configure WAL archiving + restore_command
```

### MySQL
```bash
# Full backup
mysqldump --single-transaction --routines --triggers dbname > backup.sql
# Restore
mysql dbname < backup.sql
# Binary log for PITR: mysqlbinlog --start-datetime="2025-01-01 00:00:00" binlog.000001
```

### SQLite
```bash
# Backup (safe with concurrent reads)
sqlite3 dbname ".backup backup.db"
```

### Backup Best Practices
- **Automate** — cron or systemd timer, never manual-only
- **Test restores** — untested backups are not backups
- **Offsite copies** — S3, GCS, or separate region
- **Retention policy** — daily for 7 days, weekly for 4 weeks, monthly for 12 months
- **Monitor backup size and duration** — sudden changes signal issues

---

## Anti-Patterns

| Anti-Pattern | Problem | Fix |
|-------------|---------|-----|
| `SELECT *` | Transfers unnecessary data, breaks on schema changes | Explicit column list |
| Missing indexes on FK columns | Slow JOINs and cascading deletes | Add indexes on all foreign keys |
| N+1 queries | 1 + N round trips to database | Eager loading or batch queries |
| Implicit type coercion | `WHERE id = '123'` prevents index use | Match types in predicates |
| No connection pooling | Exhausts connections under load | PgBouncer, ProxySQL, or ORM pool |
| Unbounded queries | No LIMIT risks returning millions of rows | Always paginate |
| Storing money as FLOAT | Rounding errors | Use `DECIMAL(19,4)` or integer cents |
| God tables | One table with 50+ columns | Normalize or use vertical partitioning |
| Soft deletes everywhere | Complicates every query with `WHERE deleted_at IS NULL` | Archive tables or event sourcing |
| Raw string concatenation | SQL injection | Parameterized queries always |

---

## Cross-References

| Skill | Relationship |
|-------|-------------|
| **database-designer** | Schema architecture, normalization analysis, ERD generation |
| **database-schema-designer** | Visual ERD modeling, relationship mapping |
| **migration-architect** | Complex multi-step migration orchestration |
| **api-design-reviewer** | Ensuring API endpoints align with query patterns |
| **observability-platform** | Query performance monitoring, slow query alerts |
