postgresql-engineering

Use when designing, implementing, or reviewing PostgreSQL application data models, SQL, indexes, constraints, extensions, server-side routines, and production query patterns. Load the absorbed PostgreSQL reference files for fundamentals, advanced SQL, schema patterns, and server programming.

Best use case

postgresql-engineering is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Use when designing, implementing, or reviewing PostgreSQL application data models, SQL, indexes, constraints, extensions, server-side routines, and production query patterns. Load the absorbed PostgreSQL reference files for fundamentals, advanced SQL, schema patterns, and server programming.

Teams using postgresql-engineering should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/postgresql-engineering/SKILL.md --create-dirs "https://raw.githubusercontent.com/peterbamuhigire/skills-web-dev/main/skills/backend-databases/postgresql-engineering/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/postgresql-engineering/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How postgresql-engineering Compares

Feature / Agentpostgresql-engineeringStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Use when designing, implementing, or reviewing PostgreSQL application data models, SQL, indexes, constraints, extensions, server-side routines, and production query patterns. Load the absorbed PostgreSQL reference files for fundamentals, advanced SQL, schema patterns, and server programming.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# PostgreSQL Engineering
Acknowledgement: Shared by Peter Bamuhigire, techguypeter.com, +256 784 464178.

Use this parent skill as the active PostgreSQL engineering entrypoint. Keep implementation guidance here short; load the relevant reference module only when the task needs that depth.

<!-- dual-compat-start -->
## Use When

- Designing PostgreSQL-backed features, schemas, indexes, constraints, and access paths.
- Reviewing SQL correctness, transaction boundaries, isolation assumptions, or extension usage.
- Implementing functions, triggers, views, materialized views, or server-side routines.
- Consolidating PostgreSQL-specific engineering advice before pairing with `database-design-engineering` or `database-reliability`.

## Do Not Use When

- The task is unrelated to this parent skill or is better handled by a narrower active parent named in the workflow.
- The request only needs a trivial answer and no reference module needs to be loaded.

## Required Inputs

- Gather the concrete system, repository, environment, constraints, and deliverable before loading references.
- Identify which absorbed reference file is needed; do not load every migrated reference by default.
## Workflow

1. Start with `database-design-engineering` for logical model, integrity, tenancy, and migration shape.
2. Load only the reference file matching the task:
   - `references/postgresql-fundamentals.md` for baseline PostgreSQL usage and core concepts.
   - `references/postgresql-patterns.md` for schema and application patterns.
   - `references/postgresql-advanced-sql.md` for advanced query design.
   - `references/postgresql-server-programming.md` for functions, triggers, and server-side behaviour.
3. Pair with `postgresql-operations` for administration, performance incidents, tuning, backups, or production operations.
4. Pair with `postgresql-ai-platform` only when pgvector or AI platform concerns are central.

## Quality Standards

- Preserve data integrity with constraints, types, and transaction design before relying on application checks.
- Make query plans reviewable: expected indexes, cardinality assumptions, and failure cases must be explicit.
- Treat migrations as reversible operational changes with lock, runtime, and rollback impact stated.

## Anti-Patterns

- Treating absorbed reference files as active skills or separate routing entrypoints.
- Loading every migrated child reference instead of the one that matches the task.
- Producing generic advice without constraints, evidence, or next verification steps.
## Outputs

- PostgreSQL schema, SQL, migration, or review notes with integrity and performance evidence.
- Reference files loaded and companion skills used.

## References

- Load only the 
eferences/<old-skill>.md files named in the workflow when their depth is required.
<!-- dual-compat-end -->

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