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mianhtsys/landingMod3

Use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features

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landingMod3 is a Claude Code agent skill that use this skill when designing or reviewing a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features.

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文档

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; use UUID only 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 NUMERIC for 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; CLUSTER is 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; UUID for distributed or opaque IDs, generated with uuidv7() (PG18+) or gen_random_uuid().
  • Numbers: BIGINT unless storage is critical; DOUBLE PRECISION over REAL; NUMERIC(p,s) for money and exact decimals.
  • Strings: TEXT, with CHECK (LENGTH(col) <= n) when a limit is needed; BYTEA for binary. Case-insensitive lookups: expression index on LOWER(col), or CITEXT when a constraint must be case-insensitive.
  • Time: TIMESTAMPTZ, DATE, INTERVAL. now() is transaction start; clock_timestamp() is wall clock.
  • Booleans: BOOLEAN NOT NULL unless tri-state is required.
  • Enums: CREATE TYPE ... AS ENUM only for small, stable sets; evolving business values get TEXT + CHECK or 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

AvoidUse instead
timestamp (without time zone)timestamptz
char(n), varchar(n)text (+ CHECK on length if needed)
moneynumeric
timetztimestamptz
timestamptz(0) or any precisiontimestamptz
serialgenerated 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. Use DEFERRABLE INITIALLY DEFERRED for circular dependencies checked at commit.
  • UNIQUE: creates a B-tree index; allows multiple NULLs unless NULLS NOT DISTINCT (PG15+). Prefer NULLS NOT DISTINCT unless 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 CHECK constraints; 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_ops and extracted B-tree columns.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

mianhtsys/landingMod3

Implement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.

mianhtsys/landingMod3

Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.

mianhtsys/landingMod3

Diseña y compara alternativas arquitectónicas trazables a RF/RNF sin implementar código.

mianhtsys/landingMod3

Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers.

mianhtsys/landingMod3

Revisión adversarial de la arquitectura contra RF/RNF, detectando contradicciones, cobertura faltante y complejidad innecesaria.

mianhtsys/landingMod3

Master authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing APIs, or debugging security issues.

mianhtsys/landingMod3

>- Generate grounded-and-verified, engine-agnostic database documentation that reaches 100% parity with the real schema. Introspects the LIVE database as ground truth and cross-validates it against ORM models, migrations, generated types, seeds, and application queries, then proves completeness by diffing the docs back against the database. Produces ER diagrams (mermaid), per-table data dictionaries, and a machine-readable schema.json. Works with PostgreSQL, MySQL, SQL Server, and SQLite across any ORM (Prisma, TypeORM, Drizzle, Sequelize, Knex, Django, Rails) or raw SQL. Use when asked to document a database, produce an ERD or data dictionary, write db/schema docs, audit schema drift, or refresh existing DB docs.

mianhtsys/landingMod3

Compara estrategias de persistencia y motores de datos según consistencia, concurrencia, volumen, recuperación y operación.

mianhtsys/landingMod3

Design robust, scalable database schemas for SQL and NoSQL databases. Provides normalization guidelines, indexing strategies, migration patterns, constraint design, and performance optimization. Ensures data integrity, query performance, and maintainable data models.

mianhtsys/landingMod3

Consolida análisis especializados en una recomendación arquitectónica, matriz de decisión, ADR y plan de validación.

mianhtsys/landingMod3

Master error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications. Use when implementing error handling, designing APIs, or improving application reliability.

mianhtsys/landingMod3

Build and maintain web frontends — component architecture, state management, API integration, responsive layout, client-side performance, and frontend testing patterns. Framework agnostic, focused on web frontend implementation. Do not use for backend service implementation, data engineering, or platform infrastructure work.

mianhtsys/landingMod3

Evalúa despliegue, contenedores, escalado, alta disponibilidad, observabilidad, backup, recuperación y CI/CD de forma proporcional.

mianhtsys/landingMod3

Execute read-only SQL queries against multiple Microsoft SQL Server databases. Use when: (1) querying MSSQL/SQL Server databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.

mianhtsys/landingMod3

Generate and maintain OpenAPI 3.1 specifications from code, design-first specs, and validation patterns. Use when creating API documentation, generating SDKs, or ensuring API contract compliance.

mianhtsys/landingMod3

PHP 8.0+ development — XAMPP, RESTful APIs, PDO/MySQL/MariaDB, and authentication. Use when building PHP backends, creating API endpoints, configuring XAMPP, or integrating PHP with databases.

mianhtsys/landingMod3

Analiza requisitos funcionales y no funcionales, reglas, restricciones, capacidad y ambigüedades antes de seleccionar tecnologías.

mianhtsys/landingMod3

Implement modern responsive layouts using container queries, fluid typography, CSS Grid, and mobile-first breakpoint strategies. Use when building adaptive interfaces, implementing fluid layouts, or creating component-level responsive behavior.

mianhtsys/landingMod3

>- Use when designing or implementing software securely: define security requirements, threat-model a feature, choose secure defaults, design authentication and authorization, handle untrusted data and secrets, evaluate dependencies, design multi-tenant trust boundaries, or review security-sensitive changes. Use for prevention during requirements, design, implementation, and review; not for post-build security assessments or scanning an existing codebase.

mianhtsys/landingMod3

SQL Server development and performance engineering: T-SQL best practices, indexing strategy (clustered, nonclustered, columnstore, filtered, covering/included), execution plans, query optimization, statistics and the cardinality estimator, parameter sniffing mitigation, partitioning, In-Memory OLTP, temporal tables, data compression, and schema design. WHEN: \"T-SQL\", \"write a query\", \"index\", \"covering index\", \"columnstore\", \"execution plan\", \"query plan\", \"query tuning\", \"optimize query\", \"SARGable\", \"cardinality estimator\", \"statistics\", \"parameter sniffing\", \"OPTION RECOMPILE\", \"partitioning\", \"In-Memory OLTP\", \"temporal table\", \"stored procedure\", \"schema design\", \"data type\", \"normalization\".

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