
postgresql-table-design
Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
- Installs
- 28K
- Last 24h
- +70
- Trending rank
- #2693
- Security
- Pass
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/wshobson/agents --skill postgresql-table-design- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads postgresql-table-design automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
PostgreSQL Table Design
When to Use
- Designing a new PostgreSQL schema, or reviewing one before it ships.
- Choosing column types, keys, constraints, or indexes for PostgreSQL specifically.
- Deciding whether and how to partition a large table, or how to store semi-structured data.
- Planning a schema change on a live database without downtime.
The rules and decision points for a PostgreSQL schema. The full data-type catalog, workload
patterns (update-heavy, insert-heavy, upsert, schema evolution), extensions, JSONB indexing,
and worked DDL examples are in references/details.md; open it when a section below points there.
Core Rules
- Define a PRIMARY KEY for reference tables (users, orders, etc.). Not always needed for time-series/event/log data. When used, prefer
BIGINT GENERATED ALWAYS AS IDENTITY; useUUIDonly when global uniqueness/opacity is needed. - Normalize first (to 3NF) to eliminate data redundancy and update anomalies; denormalize only for measured, high-ROI reads where join performance is proven problematic.
- Add NOT NULL everywhere it is semantically required; use DEFAULTs for common values.
- Create indexes for access paths you actually query: PK/unique (auto), FK columns (manual!), frequent filters/sorts, and join keys.
- Prefer TIMESTAMPTZ for event time; NUMERIC for money; TEXT for strings; BIGINT for integers; DOUBLE PRECISION for floats (or
NUMERICfor exact decimal arithmetic).
PostgreSQL Gotchas
- Identifiers: unquoted → lowercased. Avoid quoted/mixed-case names; use
snake_case. - Unique + NULLs: UNIQUE allows multiple NULLs. Use
UNIQUE NULLS NOT DISTINCT (...)(PG15+) to restrict to one NULL. - FK indexes: PostgreSQL does not auto-index FK columns. Add them.
- No silent coercions: length/precision overflows error out (no truncation). Inserting 999 into
NUMERIC(2,0)fails, unlike databases that silently truncate or round. - Sequences/identity have gaps (normal; don't "fix"). Rollbacks, crashes, and concurrent transactions leave gaps (1, 2, 5, 6...).
- Heap storage: no clustered PK by default;
CLUSTERis a one-off reorganization, not maintained on later inserts. - MVCC: updates/deletes leave dead tuples; vacuum handles them—design to avoid hot wide-row churn.
Data Types
- IDs:
BIGINT GENERATED ALWAYS AS IDENTITY;UUIDfor distributed or opaque IDs, generated withuuidv7()(PG18+) orgen_random_uuid(). - Numbers:
BIGINTunless storage is critical;DOUBLE PRECISIONoverREAL;NUMERIC(p,s)for money and exact decimals. - Strings:
TEXT, withCHECK (LENGTH(col) <= n)when a limit is needed;BYTEAfor binary. Case-insensitive lookups: expression index onLOWER(col), orCITEXTwhen a constraint must be case-insensitive. - Time:
TIMESTAMPTZ,DATE,INTERVAL.now()is transaction start;clock_timestamp()is wall clock. - Booleans:
BOOLEAN NOT NULLunless tri-state is required. - Enums:
CREATE TYPE ... AS ENUMonly for small, stable sets; evolving business values getTEXT+CHECKor a lookup table. - JSONB over JSON, indexed with GIN, for optional/semi-structured attributes only.
- Arrays, ranges, network, geometric, full-text, domain, composite, and vector types, plus TOAST storage and collation control: see
references/details.md.
Types to avoid
| Avoid | Use instead |
|---|---|
timestamp (without time zone) | timestamptz |
char(n), varchar(n) | text (+ CHECK on length if needed) |
money | numeric |
timetz | timestamptz |
timestamptz(0) or any precision | timestamptz |
serial | generated always as identity |
Constraints
- PK: implicit UNIQUE + NOT NULL; creates a B-tree index.
- FK: specify
ON DELETE/UPDATE(CASCADE,RESTRICT,SET NULL,SET DEFAULT). Index the referencing column. UseDEFERRABLE INITIALLY DEFERREDfor circular dependencies checked at commit. - UNIQUE: creates a B-tree index; allows multiple NULLs unless
NULLS NOT DISTINCT(PG15+). PreferNULLS NOT DISTINCTunless duplicate NULLs are wanted. - CHECK: row-local; NULL passes (three-valued logic). Combine with
NOT NULL:price NUMERIC NOT NULL CHECK (price > 0). - EXCLUDE: prevents overlaps with operators, e.g.
EXCLUDE USING gist (room_id WITH =, booking_period WITH &&)stops double-booking. Needs a GiST-capable type.
Indexing
- B-tree: default for equality/range (
=,<,>,BETWEEN,ORDER BY). - Composite: leftmost-prefix rule (
WHERE a = ? AND b > ?uses(a,b);WHERE b = ?does not). Most selective columns first. - Covering:
CREATE INDEX ON tbl (id) INCLUDE (name, email)for index-only scans. - Partial: hot subsets,
CREATE INDEX ON tbl (user_id) WHERE status = 'active'. - Expression:
CREATE INDEX ON tbl (LOWER(email)); the query must use the same expression. - GIN: JSONB containment/existence, arrays, full-text search. GiST: ranges, geometry, exclusion constraints.
- BRIN: large, naturally ordered data (time-series) at minimal storage cost; effective when disk order correlates with the indexed column.
Partitioning
- Use for large tables (>100M rows) whose queries consistently filter on the partition key, or where maintenance (pruning, bulk replacement) follows a key.
- RANGE for time-series (
PARTITION BY RANGE (created_at); TimescaleDB automates it with retention and compression), LIST for discrete values, HASH for even distribution without a natural key. - Constraint exclusion: the planner prunes partitions through their
CHECKconstraints; declarative partitioning (PG10+) creates them for you. - Prefer declarative partitioning or hypertables. Do NOT use table inheritance.
- Limitations: no global UNIQUE constraints—include the partition key in PK/UNIQUE. FKs from partitioned tables need PG11+, FKs referencing a partitioned table need PG12+; on older versions, use triggers.
Examples
CREATE TABLE users (
user_id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
email TEXT NOT NULL UNIQUE,
name TEXT NOT NULL,
created_at TIMESTAMPTZ NOT NULL DEFAULT now()
);
CREATE UNIQUE INDEX ON users (LOWER(email));
CREATE INDEX ON users (created_at);
CREATE TABLE orders (
order_id BIGINT GENERATED ALWAYS AS IDENTITY PRIMARY KEY,
user_id BIGINT NOT NULL REFERENCES users(user_id),
status TEXT NOT NULL DEFAULT 'PENDING' CHECK (status IN ('PENDING','PAID','CANCELED')),
total NUMERIC(10,2) NOT NULL CHECK (total > 0),
created_at TIMESTAMPTZ NOT NULL DEFAULT now()
);
CREATE INDEX ON orders (user_id);
CREATE INDEX ON orders (created_at);
-- JSONB attributes with a generated, indexable scalar
CREATE TABLE profiles (
user_id BIGINT PRIMARY KEY REFERENCES users(user_id),
attrs JSONB NOT NULL DEFAULT '{}',
theme TEXT GENERATED ALWAYS AS (attrs->>'theme') STORED
);
CREATE INDEX profiles_attrs_gin ON profiles USING GIN (attrs);
Going deeper
references/details.md holds the material this file only names:
- The full data-type catalog: TOAST storage, collations, arrays, ranges, network, geometric, text search, domains, composites, vectors.
- Table types (
TEMPORARY,UNLOGGED) and row-level security. - Constraint and index notes, and partitioning DDL for RANGE, LIST, and HASH.
- Workload patterns: update-heavy, insert-heavy, upsert design, safe schema evolution.
- Generated columns and extensions (
pg_trgm,citext,timescaledb,postgis,pgvector, and more). - JSONB indexing strategies, including
jsonb_path_opsand extracted B-tree columns.
FAQ
What does the postgresql-table-design skill do?
Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
How do I install postgresql-table-design?
Run npx skills add https://github.com/wshobson/agents --skill postgresql-table-design in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/postgresql-table-design/ (personal) or .claude/skills/postgresql-table-design/ (project).
Which AI agents can use postgresql-table-design?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is postgresql-table-design safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed; Runlayer passed; ZeroLeaks passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains postgresql-table-design?
It is published by wshobson in wshobson/agents. It has 27,983 recorded installs.
More from wshobson/agents
typescript-advanced-types
wshobson/agents
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications. Use when implementing complex type logic, creating reusable type utilities, or ensuring compile-time type safety in TypeScript projects.
tailwind-design-system
wshobson/agents
Build scalable design systems with Tailwind CSS v4, design tokens, component libraries, and responsive patterns. Use when creating component libraries, implementing design systems, or standardizing UI patterns.
nodejs-backend-patterns
wshobson/agents
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.
brand-landingpage
wshobson/agents
Brand-first landing page designer — runs a brand-identity interview (colors, typography, shape language), then generates and iterates on a polished landing page via Stitch with deployment-ready HTML. Use when the user asks to create, design, or build a landing page, homepage, or marketing page and has no established visual direction. Skip when they have a design mockup, need a dashboard or app UI, are working at component level, building a multi-page app, or restyling with known design tokens — use frontend-design instead.
python-testing-patterns
wshobson/agents
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
python-performance-optimization
wshobson/agents
Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
Popular data & databases skills
supabase-postgres-best-practices
supabase/agent-skills
Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pgcron, pgmq), vector/semantic search (pgvector), and restoring dumps (pgrestore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.
prisma-client-api
prisma/skills
Prisma Client API reference covering model queries, filters, operators, and client methods. Use when writing database queries, using CRUD operations, filtering data, or configuring Prisma Client. Triggers on "prisma query", "findMany", "create", "update", "delete", "$transaction".
prisma-database-setup
prisma/skills
Deprecated compatibility name for prisma-orm-setup. Use only when a user or existing integration explicitly invokes prisma-database-setup; otherwise select prisma-orm-setup.
prisma-cli
prisma/skills
Prisma ORM 7 CLI reference for existing Prisma 7 applications or explicitly selected Prisma 7 workflows. Covers prisma init, generate, migrate, db, dev, studio, and mcp. For setup, connection repair, or Prisma 8, use prisma-orm-setup; not the Prisma Platform CLI.
prisma-postgres
prisma/skills
Deprecated compatibility name for prisma-postgres-setup. Use only when a user or existing integration explicitly invokes prisma-postgres; otherwise select prisma-postgres-setup.
prisma-driver-adapter-implementation
prisma/skills
Required reference for Prisma ORM 7 SQL driver adapter work. Use when implementing or modifying adapters, adding database drivers, or touching SqlDriverAdapter, Transaction, savepoint, result mapping, or DriverAdapterError behavior. Covers current transaction lifecycle, optional savepoint hooks, original database-error preservation, and verification.