Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add KunanonJ/ai-skills-hub --skill postgresqlgit clone --depth 1 https://github.com/KunanonJ/ai-skills-hubWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kunanonj/ai-skills-hub/postgresql)<a href="https://agentmods.dev/skills/kunanonj/ai-skills-hub/postgresql"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/postgresql/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kunanonj/ai-skills-hub/postgresql"><img src="https://agentmods.dev/badge/skills/kunanonj/ai-skills-hub/postgresql.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.04204 |
| Opus 5 | $0.00015 | $0.02102 |
| Sonnet 5 | $0.00006 | $0.00841 |
| Haiku 4.5 | $0.00003 | $0.00420 |
Grade A, and why
postgresql scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
92% identical to postgresql-table-design — 274 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PostgreSQL Table Design
Use this skill when
- Designing a schema for PostgreSQL
- Selecting data types and constraints
- Planning indexes, partitions, or RLS policies
- Reviewing tables for scale and maintainability
Do not use this skill when
- You are targeting a non-PostgreSQL database
- You only need query tuning without schema changes
- You require a DB-agnostic modeling guide
Instructions
- Capture entities, access patterns, and scale targets (rows, QPS, retention).
- Choose data types and constraints that enforce invariants.
- Add indexes for real query paths and validate with
EXPLAIN. - Plan partitioning or RLS where required by scale or access control.
- Review migration impact and apply changes safely.
Safety
- Avoid destructive DDL on production without backups and a rollback plan.
- Use migrations and staging validation before applying schema changes.
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. 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
NUMERICfor exact decimal arithmetic).
PostgreSQL “Gotchas”
- Identifiers: unquoted → lowercased. Avoid quoted/mixed-case names. Convention: use
snake_casefor table/column names. - 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). Example: inserting 999 into
NUMERIC(2,0)fails with error, unlike some databases that silently truncate or round. - Sequences/identity have gaps (normal; don't "fix"). Rollbacks, crashes, and concurrent transactions create gaps in ID sequences (1, 2, 5, 6...). This is expected behavior—don't try to make IDs consecutive.
- Heap storage: no clustered PK by default (unlike SQL Server/MySQL InnoDB);
CLUSTERis one-off reorganization, not maintained on subsequent inserts. Row order on disk is insertion order unless explicitly clustered. - MVCC: updates/deletes leave dead tuples; vacuum handles them—design to avoid hot wide-row churn.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 234 lines · 29 tokens per session scan A 4908afc41b07
postgresql is a skill published in the GitHub repository KunanonJ/ai-skills-hub (5 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 4,204 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to postgresql-table-design, differing in 274 lines, and is treated as a copy.
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postgres-patterns
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
postgres-database-migration
Use this skill for planning, testing, and safely executing PostgreSQL schema migrations — especially when working with production data or shared databases. Trigger when user asks to: Test a schema migration before applying it to production Add, remove, or rename columns safely on a live table Change a column's data…
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Use this skill when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data. Use this to improve the performance of any insert-heavy table. Trigger when user asks to: Create or design SQL schemas/tables AND…