PostgreSQL Table Design

Overview

This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/postgresql from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

PostgreSQL Table Design

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Safety, PostgreSQL “Gotchas”, Data Types, Table Types, Row-Level Security, Constraints.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Designing a schema for PostgreSQL
• Selecting data types and constraints
• Planning indexes, partitions, or RLS policies
• Reviewing tables for scale and maintainability
• You are targeting a non-PostgreSQL database
• You only need query tuning without schema changes

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Capture entities, access patterns, and scale targets (rows, QPS, retention).
2. Choose data types and constraints that enforce invariants.
3. Add indexes for real query paths and validate with EXPLAIN.
4. Plan partitioning or RLS where required by scale or access control.
5. Review migration impact and apply changes safely.
6. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
7. Read the overview and provenance files before loading any copied upstream support files.

Imported Workflow Notes

Imported: Instructions

1. Capture entities, access patterns, and scale targets (rows, QPS, retention).
2. Choose data types and constraints that enforce invariants.
3. Add indexes for real query paths and validate with EXPLAIN.
4. Plan partitioning or RLS where required by scale or access control.
5. Review migration impact and apply changes safely.

Imported: Safety

• Avoid destructive DDL on production without backups and a rollback plan.
• Use migrations and staging validation before applying schema changes.

Examples

Example 1: Ask for the upstream workflow directly

Use @postgresql to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @postgresql against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @postgresql for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @postgresql using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: Examples

Users

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);

Orders

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

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);

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• 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. Premature denormalization creates maintenance burden.
• Add NOT NULL everywhere it’s 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 integer values, DOUBLE PRECISION for floats (or NUMERIC for exact decimal arithmetic).
• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.

Imported Operating Notes

Imported: 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. Premature denormalization creates maintenance burden.
• Add NOT NULL everywhere it’s 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 integer values, DOUBLE PRECISION for floats (or NUMERIC for exact d