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
Install / Use
npx skills add wshobson/agents --skill postgresql-table-designInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Data & AnalyticsSupported Platforms
Our assessment of postgresql-table-design
postgresql-table-design scores 96/100 on our quality scale, 13th of 159 Data & Analytics skills we index (top 9%).
Its SKILL.md is 7.7 KB long, well organised into 11 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.
With 39,920 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 4 days ago, so postgresql-table-design is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
postgresql-table-design compared with similar skills
All 4 of these similar skills score higher than postgresql-table-design; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| postgresql-table-design (this skill)by wshobson | 96 | 39.9k | 4d ago | SKILL.md |
| claude-memby thedotmack | 100 | 94.7k | today | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 2d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 2d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 3d ago | SKILL.md |
Frequently asked questions
- How do I install postgresql-table-design?
- Run
npx skills add wshobson/agents --skill postgresql-table-design. The install tabs above show the steps for each supported agent. - Which AI agents does postgresql-table-design work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is postgresql-table-design safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is postgresql-table-design still maintained?
- The repository was last updated 4 days ago, so postgresql-table-design is actively maintained.
Skill content
View source on GitHubname: postgresql-table-design description: Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
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.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
