Skills postgresql
📦
postgresql
Content revision r1 Safe ⚙️ External commands
Design PostgreSQL Schemas With Best Practices
PostgreSQL schema design can fail when data types, constraints, indexes, and migrations lack workload context. This skill turns entities, access patterns, and scale targets into PostgreSQL-specific design guidance.
Supports: Claude Codex Code(CC)
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "postgresql" from https://skillstore.io/skills/sickn33-postgresql.md and its manifest at https://skillstore.io/api/skills/sickn33-postgresql/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "postgresql". I need user and order tables with status tracking and reporting queries.
Expected outcome:
- A normalized users table with a stable identity key and unique email handling.
- An orders table with status checks, monetary precision, timestamps, and foreign key support.
- Indexes for user lookups, created time reports, and safe parent row updates.
Using "postgresql". Review my plan to store product attributes in JSONB.
Expected outcome:
- Guidance on when JSONB is appropriate and when regular columns are safer.
- Index choices for containment, key existence, scalar range filters, and generated columns.
- Constraint ideas that keep flexible attributes within expected shapes.
Using "postgresql". Plan a large event table with retention and tenant isolation.
Expected outcome:
- A partitioning approach based on time and retention operations.
- Row-level security considerations for tenant access control.
- Index and migration advice that limits write overhead and release risk.
Security Audit
Safev4 • 7/7/2026 Open versioned report
Static analysis flagged Markdown backticks, SQL examples, and PostgreSQL terms as command execution and reconnaissance. Manual review found documentation-only schema guidance with no executable scripts, network access, prompt injection, or exfiltration intent.
1
Files scanned
231
Lines analyzed
0
Review items
0
False positives ignored
Risk Factors
⚙️ External commands (85)
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No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
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APA citation
sickn33. (2026). postgresql security audit report (audit version 4) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-postgresql/audits/4BibTeX citation
@techreport{sickn33-sickn33-postgresql-2026,
author = {sickn33},
title = {postgresql security audit report (audit version 4)},
institution = {Skillstore},
year = {2026},
number = {4},
url = {https://skillstore.io/skills/sickn33-postgresql/audits/4},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "postgresql security audit report (audit version 4)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-07"
url: "https://skillstore.io/skills/sickn33-postgresql/audits/4"
identifiers:
- type: other
value: "skillstore:sickn33-postgresql:audit:4"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
Highest Skillstore Score
Author / source Skillstore Score Evidence Confidence Skillstore usage Updated
sickn33-postgresql
Skillstore Score 78
Evidence Confidence High
Skillstore usage 13
Updated
2026-08-21
2025emma-postgresql
Skillstore Score 73
Evidence Confidence Medium
Skillstore usage 22
Updated
2026-08-21
Skillstore Score
Why this score Evidence Confidence: High 55
Architecture
85
Maintainability
87
Content
69
Community
83
Spec Compliance
What You Can Build
Design a Feature Schema
Plan tables, keys, constraints, and indexes for a new PostgreSQL feature before implementation starts.
Review a Production Migration
Check schema changes for locking, rewrite, indexing, and rollback risks before a release.
Model Scalable Data Storage
Choose JSONB, partitioning, RLS, and extension patterns for growing data products.
Try These Prompts
Create a Basic Schema
Use the PostgreSQL skill to design tables for this feature. Entities are [entities]. Common queries are [queries]. Expected scale is [scale].
Review Data Types and Constraints
Review this PostgreSQL table plan for data type, nullability, key, and constraint choices. Call out changes that improve correctness and maintainability.
Plan Indexes for Workload
Given these PostgreSQL queries and table sizes, recommend indexes and explain each tradeoff. Include composite, partial, expression, GIN, GiST, or BRIN options when useful.
Audit an Advanced Migration
Audit this PostgreSQL migration plan for locking, rewrites, data backfill, RLS, partitioning, and rollback risk. Suggest a safer deployment sequence.
Best Practices
- Provide real access patterns, row counts, write rates, and retention needs before asking for design advice.
- Validate generated schema ideas with migrations, staging data, and PostgreSQL query plans.
- Prefer explicit constraints and indexes that match actual application behavior.
Avoid
- Do not copy example tables without adapting names, constraints, and indexes to your workload.
- Do not use JSONB as a replacement for core relational modeling.
- Do not run destructive DDL in production without backups, tests, and rollback planning.
Frequently Asked Questions
Does this skill execute PostgreSQL commands?
No. It provides design guidance and examples. Users must run any database changes themselves.
Can it tune live database queries?
It can suggest schema and index changes, but it does not inspect live databases or query plans.
Is it useful for other databases?
It is PostgreSQL-specific. Some modeling ideas may transfer, but many recommendations use PostgreSQL features.
Does it cover row-level security?
Yes. It includes guidance for enabling RLS and creating policies for row-level access control.
Can it help with JSONB design?
Yes. It explains JSONB use, GIN indexes, scalar extraction, and constraints for flexible attributes.
Should I apply its migration advice directly?
No. Review every migration with backups, staging tests, and production change controls.