sql-x-4

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name: sql slug: sql version: 1.0.4 description: >- Writes, reviews, and optimizes SQL queries; designs schemas, indexes, and constraints; plans migrations for any relational database. Use when a query is slow, EXPLAIN shows a sequential scan, or an index is ignored; when rows come back duplicated, missing, or with inflated totals after a JOIN; on deadlocks, lock timeouts, "too many connections", or transactions that never commit; when designing tables, keys, and column types, normalizing or denormalizing a model, or deciding between a JSON column and real columns; for ALTER TABLE on a live table, expand-migrate-contract rollouts, backups and restores, replication lag, connection pooling, partitioning, bulk CSV imports, and moving data between engines; for window functions, CTEs, keyset pagination, upserts, full-text search, multi-tenancy, row-level security, and timezone handling in MySQL, SQLite, MariaDB, or SQL Server. Not for PostgreSQL server internals such as vacuum tuning and work_mem sizing, and not for ORM schema modeling inside a framework. homepage: https://clawic.com/skills/sql changelog: "Full coverage pass: deeper guides, situation-named files, and per-user configuration" metadata: clawdbot: emoji: 🗄️ requires: anyBins: - sqlite3 - psql - mysql - sqlcmd os: - linux - darwin - win32 displayName: SQL configPaths: - ~/Clawic/data/sql/

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User preferences and memory live in ~/Clawic/data/sql/ (see setup.md on first use, memory-template.md for the file format). If you have data at an old location (~/sql/ or ~/clawic/sql/), move it to ~/Clawic/data/sql/.

When To Use

• Writing, reviewing, or optimizing SQL: queries, joins, CTEs, window functions, upserts
• Designing tables, keys, types, indexes, and constraints, or normalizing an existing model
• Diagnosing a slow query, a deadlock, a lock timeout, wrong totals, or duplicated rows
• Planning migrations and DDL that must not take a live database down
• Operating a database: backups, restores, monitoring, pooling, replication, partitioning
• Moving data in or out: CSV loads, dumps, engine-to-engine migrations
• Not for PostgreSQL server internals (vacuum tuning, work_mem, xid wraparound) — that is pg; not for ORM-level modeling in a framework — that is prisma

Quick Reference

Situation	Play
Query slow, cause unknown	EXPLAIN (ANALYZE, BUFFERS), fix the worst node first (→ Reading EXPLAIN, then performance.md)
Query was fast yesterday	Stats, data growth, or plan flip — the regression chain in debug.md
Index exists but is not used	Function on the column, type mismatch, wrong column order, or low selectivity (→ Traps, performance.md)
Totals inflated after adding a JOIN	1:N fan-out — aggregate before joining (→ Traps)
Rows missing after adding a JOIN	LEFT JOIN filtered in WHERE became an inner join (→ Traps)
Paginating past the first few thousand rows	Keyset, never OFFSET (patterns.md)
Deadlock, lock timeout, or "could not obtain lock"	transactions.md — lock ordering and isolation
"Too many connections" / app hangs on connect	Pool sizing before max_connections (operations.md, orm.md)
Read-modify-write race, job queue	SELECT ... FOR UPDATE, add SKIP LOCKED for queues (patterns.md)
Schema change on a live table	Expand → migrate → contract, lock_timeout first (operations.md)
Designing a model from scratch	Keys, cardinality, normal forms, when to denormalize (modeling.md)
Known shape needed (tenants, tags, audit, state, history)	schemas.md
Storing or querying JSON / semi-structured data	json.md
Cohorts, funnels, retention, rollups, materialized views	analytics.md
Loading a CSV, dump/restore, engine-to-engine move	data-loading.md
Timestamps off by hours, DST, week/fiscal boundaries	datetime.md
Statement works on one engine, fails on another	dialects.md
Grants, least privilege, RLS, PII erasure, encryption	security.md
Seeding fixtures, isolating tests, testing a migration	testing.md
ORM emits terrible SQL, N+1, mystery transactions	orm.md
Single node at its limit: replicas, sharding, caching	scaling.md
Choosing an engine	SQLite embedded/local · PostgreSQL default for servers · MySQL when the platform dictates it · SQL Server in .NET/Windows shops (dialects.md)
Anything else	Reproduce on the smallest table that shows it, then: schema-shaped → modeling.md/schemas.md · query-shaped → patterns.md · slow → performance.md · ops-shaped → operations.md

Core Rules

1. Parameterize values; allowlist identifiers. Placeholders (?, $1) stop injection for values, but table/column names cannot be bound — when those are dynamic, check them against a hardcoded allowlist, never interpolate user input. Full attack surface, including LIKE and ORDER BY injection: security.md.
2. BIGINT (or UUIDv7) primary keys by default. INT overflows at 2,147,483,647 — at a sustained 100 inserts/s that is 2.1B ÷ 100/s ≈ 248 days, and the fix is an outage-grade type change. Random UUIDv4 keys fragment the B-tree; UUIDv7/ULID keep insert locality (modeling.md).
3. Index for the query shape: equality columns first, then range/sort. (user_id, created_at) serves WHERE user_id = ? AND created_at > ? and WHERE user_id = ? alone — never created_at alone. A sequential scan on a filter matching more than roughly 5-10% of rows is the planner being right, not broken.
4. Index every foreign key column yourself. MySQL/InnoDB creates the index automatically; PostgreSQL, SQLite, and SQL Server do not. Without it, every join on the FK and every parent DELETE (worse with ON DELETE CASCADE) scans the whole child table — the slowest delete in most schemas is this one missing index.
5. Transactions stay short and never wait on the outside world. No HTTP calls, no user input inside BEGIN...COMMIT: open transactions hold locks, and in PostgreSQL they also block vacuum, causing table bloat. Anything open past the >1 min monitoring threshold (operations.md) gets investigated.
6. NULL is three-valued. NOT IN (subquery) returns zero rows if the subquery yields a single NULL — use NOT EXISTS. x = NULL is never true — use IS NULL. COUNT(col) skips NULLs; COUNT(*) counts rows. Aggregates over zero rows return NULL, not 0 — wrap in COALESCE when a chart or invariant expects a number.
7. Types that avoid the next migration. Money → NUMERIC/DECIMAL (float money loses cents in aggregation); timestamps → TIMESTAMPTZ stored as UTC (datetime.md); strings → TEXT in PostgreSQL and SQLite (varchar(255) is a cargo-cult limit you will later raise); MySQL charset → utf8mb4 (MySQL's utf8 is 3-byte and rejects emoji).
8. Migrations are additive first. Rename/retype/drop happens over multiple deploys with both versions live in between (expand-migrate-contract, operations.md). A single-deploy column rename breaks every instance still running old code.
9. Rank before you tune. pg_stat_statements ordered by total_exec_time (or the MySQL slow query log digested by pt-query-digest) tells you which query costs the most overall — usually not the one someone complained about. Total cost = mean latency × call count: a 5 ms query called 10,000×/min (50 s/min) outranks a 2 s report run hourly. Optimizing an unranked query is guessing.

Reading EXPLAIN

EXPLAIN (ANALYZE, BUFFERS) SELECT * FROM orders WHERE user_id = 5;  -- PostgreSQL
EXPLAIN ANALYZE SELECT ...;                                         -- MySQL >=8.0.18
EXPLAIN QUERY PLAN SELECT * FROM orders WHERE user_id = 5;          -- SQLite
SET STATISTICS PROFILE ON;                                          -- SQL Server (or the graphical plan)

Read actual behavior, not just the plan. Plain EXPLAIN shows estimates only, and estimates are the part that lies.

• Seq Scan / type: ALL on a large table with a selective filter → missing or unusable index (→ Traps for what disables one)
• Rows Removed by Filter high → the index found candidates but the filter did the work; extend the index to cover the filter
• Estimated vs actual rows off by more than 10× → stale stats: run ANALYZE tablename;. Still off → the planner assumes column independence; declare the correlation (CREATE STATISTICS on PostgreSQL >=10, histogram on MySQL 8)
• Buffers: read large vs hit → data is coming from disk; recheck on a warm cache before concluding
• Nested Loop over thousands of outer rows → usually the >10× misestimate above feeding a bad join choice
• Node-by-node interpretation, join algorithms, and what to change for each: performance.md

Index Strategy

-- Composite: equality columns first, range/sort last (rule 3)
CREATE INDEX idx_orders_user_status ON orders(user_id, status);

-- Covering: index-only scan, no heap fetch (PostgreSQL >=11, SQL Server INCLUDE)
CREATE INDEX idx_orders_user ON orders(user_id) INCLUDE (total);

-- Partial/filtered: index only the rows you query (PostgreSQL, SQLite, SQL Server)
CREATE INDEX idx_orders_pending ON orders(user_id) WHERE status = 'pending';

-- Expression: make a function sargable (MySQL >=8.0.13 supports functional indexes)
CREATE INDEX idx_users_email_lower ON users(LOWER(email));

• A plain B-tree on a low-cardinality column (status with 5 values) rarely helps; a partial index on the rare value you actually query does.
• An index on (a, b) already serves WHERE a = ? — creating a second index on (a) alone adds write cost and reclaims nothing. Check for redundant prefixes before adding.
• PostgreSQL with a non-C locale ignores B-tree indexes for LIKE 'term%' — add the text_pattern_ops opclass for prefix search.
• Index-only scans still hit the heap for pages not marked all-visible; if EXPLAIN shows Heap Fetches high, the table needs a VACUUM (operations.md).
• Every index taxes writes and consumes disk: drop unused ones (pg_stat_user_indexes where idx_scan = 0), but only after uptime covers a full business cycle — month-end reports use indexes nothing else does.

Portability

Feature	PostgreSQL	MySQL	SQLite	SQL Server
Limit	LIMIT n	LIMIT n	LIMIT n	TOP n / OFFSET-FETCH
Upsert	ON CONFLICT	ON DUPLICATE KEY	ON CONFLICT	MERGE
Boolean	true/false	1/0 (TINYINT)	1/0	1/0 (BIT)
Concat	||	CONCAT()	||	+ or CONCAT()
Auto-id	GENERATED / SERIAL	AUTO_INCREMENT	INTEGER PRIMARY KEY	IDENTITY
Returning rows from DML	RETURNING	— (MariaDB has it)	RETURNING (>=3.35)	OUTPUT
Aggregate FILTER	Yes	CASE only	Yes (>=3.30)	CASE only
Transactional DDL	Yes	No (implicit commit)	Yes	Yes
Default string compare	Case-sensitive	Case-insensitive (_ci collations)	Case-sensitive	Case-insensitive by default

Date functions, quoting, NULL sort order, collation, and the rest of the divergences: dialects.md.

Output Gates

Before emitting SQL, verify:

• Every value is a placeholder, and every dynamic identifier came from an allowlist?
• UPDATE/DELETE has a WHERE, or the full-table effect is explicitly intended?
• Destructive DML was previewed as the equivalent SELECT first?
• No 1:N join feeds an aggregate without pre-aggregation, and no DISTINCT is papering over one?
• LIMIT/TOP has a deterministic ORDER BY with a unique tiebreaker?
• New table: primary key type per rule 2, timestamps with zone, uniqueness scoped to the right columns, every FK column indexed (rule 4)?
• DDL against a live table: lock_timeout set, and the change is expand-only?
• Every construct used exists in the target engine (→ Portability, dialects.md)?

Configuration

User-dependent variables. Defaults apply until the user states a preference; store them in ~/Clawic/data/sql/config.yaml.

Variable	Type	Default	Effect
dialect	postgres | mysql | mariadb | sqlite | sqlserver	postgres	Syntax of every emitted statement and which caveats from Portability and dialects.md are surfaced
engine_version	text (e.g. 15, 8.0.35)	none	Gates features with a version floor (RETURNING, functional indexes, NULLS NOT DISTINCT); with none set, the conservative form is emitted
identifier_style	snake_case | camelCase | PascalCase	snake_case	Naming of tables, columns, indexes, and constraints in generated DDL
table_naming	plural | singular	plural	Whether generated tables read users or user
pk_type	bigint-identity | uuidv7 | uuidv4 | natural	bigint-identity	The primary key emitted by every CREATE TABLE (rule 2, modeling.md)
destructive_guard	bool	true	When true, UPDATE/DELETE without WHERE, DROP, and TRUNCATE are emitted as a transaction-wrapped preview with the matching SELECT first
migration_tool	text (flyway, alembic, golang-migrate, sqitch, ...)	none	File naming and up/down structure of generated migrations (operations.md)
timezone_policy	utc | local	utc	Whether timestamps are stored and compared as UTC and how datetime.md examples render
lock_timeout	text (duration: 500ms, 2s, 10s)	2s	The SET lock_timeout emitted before every DDL statement against a live table (→ Traps, operations.md)
batch_size	number (rows, 100-100000)	5000	Chunk size for batched DELETE/UPDATE, backfills, and bulk loads (patterns.md, data-loading.md, json.md)

Preference areas — customizable dimensions; a stated preference gets recorded in config.yaml and applied:

• Tooling — client (psql, mysql, sqlite3, sqlcmd, a GUI), migration runner, SQL linter/formatter, local database as a container vs installed service — affects operations.md and testing.md examples
• Conventions — index and constraint naming, keyword casing, CTE vs subquery preference, comment style in DDL — affects every emitted statement
• Platform — managed service (RDS, Aurora, Cloud SQL, Neon, PlanetScale) vs self-hosted, available extensions, collation and locale — affects which features may be assumed
• Safety posture — how much confirmation destructive DDL/DML needs, whether production credentials are ever used directly, read-only-by-default sessions — affects operations.md and the destructive_guard gate
• Output format — full runnable script vs snippet, whether a down/rollback migration accompanies every up, inline comments — affects the shape of every deliverable
• Work order — schema-first vs query-first design, review gate before a migration reaches production — affects the sequence in modeling.md and operations.md
• Integrations — ORM in use, warehouse/BI target, monitoring stack — affects orm.md and analytics.md advice
• Constraints — vetoed features (no triggers, no stored procedures, no vendor extensions), compliance regime (retention windows, GDPR erasure) — affects schemas.md and security.md choices
• Thresholds — the operational budgets a shop usually standardizes: lock_timeout, batch_size, retry cap on deadlock/serialization failures, pool sizing rule, and the alert levels (connection saturation, disk free, transaction age, backup age) — affects transactions.md retry loops and the Alert Thresholds table in operations.md
• Cadence — how often scheduled work runs: restore drills, rollup and materialized-view refresh, the trailing recompute window, data-quality assertion runs, automated partition creation, backup interval — affects operations.md, analytics.md, schemas.md, and testing.md schedules

Traps

Trap	Why it fails	Do instead
WHERE YEAR(created_at) = 2024	Function on the column hides it from the index	Range: created_at >= '2024-01-01' AND created_at < '2025-01-01'
BETWEEN '2024-01-01' AND '2024-01-31' on a timestamp	Upper bound is midnight — the whole last day is excluded with no error	Half-open range: >= '2024-01-01' AND < '2024-02-01'
WHERE varchar_col = 123	Implicit cast applies to the column, disabling its index	Match types: quote the literal or fix the schema
LEFT JOIN t ... WHERE t.col = x	WHERE runs after the join and filters the NULL rows out → an INNER JOIN, with no error	Move the predicate into ON, or test t.id IS NULL for an anti-join
Join 1:N then SUM/COUNT	Fan-out duplicates left-side rows before aggregation	Aggregate in a subquery/CTE, then join the result
DISTINCT added to make duplicates go away	Hides a fan-out bug and forces a sort of the whole result	Find the join that multiplies rows; DISTINCT is a diagnosis, not a fix
LIKE '%term'	Leading wildcard defeats B-tree ordering	Full-text search (schemas.md) or a trigram index (pg_trgm)
Composite (a, b) for WHERE b = ?	B-tree is sorted by a first; b alone is unordered	Separate index on b, or reorder if a is always filtered
WHERE a = ? OR b = ?	One index cannot serve two independent predicates; usually a full scan	UNION ALL of two indexed queries, deduplicated if needed
LIMIT 10 without ORDER BY	Row order is undefined — "top 10" changes between runs and after a vacuum	Always ORDER BY with a unique tiebreaker column
ORDER BY random() LIMIT n	Full scan plus sort of the entire table	TABLESAMPLE or a random-key probe (patterns.md)
SELECT * in application code	Blocks index-only scans, fetches columns you drop, breaks on schema change	Name the columns
DDL without lock_timeout	ALTER TABLE queues behind one long query and every new query queues behind it — brief lock, full outage	SET lock_timeout (default 2s, → Configuration) then retry (operations.md)
Wrapping TRUNCATE/DDL in a transaction on MySQL	MySQL commits implicitly on DDL: the rollback you planned does not exist	Take a backup or use a copy table; transactional DDL is PostgreSQL/SQLite/SQL Server only

Where Experts Disagree

• Surrogate vs natural keys. Surrogate (BIGINT/UUID) is the default: natural keys change, and a changing PK cascades into every child row. Natural keys legitimately win on pure junction tables and on immutable code tables (ISO currency, country) where the extra id buys nothing (modeling.md).
• Foreign keys at scale. Some high-write shops drop FK constraints because they add per-write lock and index cost and complicate online schema-change tooling. Default: keep them — orphan cleanup costs more than the writes saved. Drop only with a measured write bottleneck and integrity enforced elsewhere.
• Logic in the database. Triggers and stored procedures give atomicity nothing in the app can match and centralize rules across many clients; they are also invisible to code review, hard to test, and version-controlled poorly. Default: constraints and simple audit triggers in the database, business workflows in the application (schemas.md).
• Soft delete everywhere. Undo and audit are real requirements, but a deleted_at on every table poisons every query and every unique constraint. Default: hard delete plus an audit log; soft-delete only the tables users actually restore (schemas.md).

Related Skills

More Clawic skills, get them at https://clawic.com/skills/sql (install if the user confirms):

• pg — PostgreSQL server internals: vacuum, work_mem, wraparound
• mysql — MySQL and InnoDB specifics
• sqlite — SQLite concurrency, pragmas, and type affinity
• prisma — Node.js ORM modeling
• dbt — warehouse transformations and tests

Feedback

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