data-relational-database

data-relational-database is a skill for Claude Code, Codex from j4flmao/agent-skills. It costs 148 tokens per session (6,073 once invoked), scanned A, original, MIT.

A guide to designing relational databases, where data is stored in related tables, with a focus on PostgreSQL and similar systems.

In plain words
What is it for?
Use it to plan schemas, indexes, partitions, replicas, connection pools, migrations, and query optimizations.
Why use it?
It helps prevent slow queries, overloaded connections, poor indexing, and database designs that become difficult to scale or maintain.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Good fit Use it to plan schemas, indexes, partitions, replicas, connection pools, migrations, and query optimizations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/j4flmao/agent-skills/relational-database
Install

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.

Any agent
npx skills add j4flmao/agent-skills --skill relational-database
Clone the repo
git clone --depth 1 https://github.com/j4flmao/agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for data-relational-database

README.md
[![agentmods](https://agentmods.dev/badge/skills/j4flmao/agent-skills/relational-database.svg)](https://agentmods.dev/skills/j4flmao/agent-skills/relational-database)
Your own site
<a href="https://agentmods.dev/skills/j4flmao/agent-skills/relational-database"><img src="https://agentmods.dev/badge/skills/j4flmao/agent-skills/relational-database.svg" alt="Measured on agentmods" height="20"></a>
Per session 148 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,073 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00148 $0.06073
Opus 5 $0.00074 $0.03037
Sonnet 5 $0.00030 $0.01215
Haiku 4.5 $0.00015 $0.00607

Measured 3d ago against content hash 7ca68752bdb6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

data-relational-database 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 3d 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.

skills/data/relational-database/SKILL.md · 511 lines

How it starts

The opening of the file, as written. The whole thing — 511 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Data Relational Database

Purpose

Design relational database schemas with proper indexing, partitioning, replication, connection pooling, and query optimization strategies.

Agent Protocol

Trigger

Exact user phrases: "PostgreSQL", "MySQL", "relational database", "partitioning", "replication", "indexing", "vacuum", "connection pooling", "query optimization", "EXPLAIN", "CTE", "window function", "transaction isolation", "migration", "PgBouncer", "MVCC", "WAL", "B-tree", "GiST", "GIN", "BRIN".

Input Context

Before activating, verify:

  • Database platform (PostgreSQL, MySQL, MariaDB, SQLite)
  • Data volume (rows, growth rate, total size in GB/TB)
  • Query workload (OLTP, OLAP, mixed)
  • Current schema and migration tool (Alembic, Sqitch, Flyway, Liquibase)
  • Existing indexing strategy and planner statistics
  • Replication needs (read replicas, disaster recovery, logical replication)
  • Connection pooling requirements (client count, max connections)

Output Artifact

Database schema with indexes, partition configuration, replication setup, and query optimization plan as SQL and YAML.

Response Format

-- Table DDL with partitioning
-- Index creation statements
-- Replication configuration
-- Migration statements
# Connection pool config
# Replication setup
# Vacuum settings

No preamble. No postamble. No explanations. No filler/hedging/transitions. Compress output — why use many token when few do trick.

Completion Criteria

  • Normalized schema with appropriate constraints (PK, FK, CHECK, UNIQUE)
  • Indexing strategy covering slow queries (EXPLAIN ANALYZE output reviewed)
  • Partitioning scheme configured for large tables
  • Replication setup (streaming for HA, logical for data distribution)
  • Connection pool configured (PgBouncer transaction mode default)
  • Vacuum and autovacuum settings tuned
  • Transaction isolation levels chosen per workload
  • Migration plan with rollback strategy

Max Response Length

300 lines of SQL and configuration.

Read the full file on GitHub · 511 lines

Changes

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.

  1. 3d ago First seen · 511 lines · 148 tokens per session scan A 7ca68752bdb6

Subscribe to this mod's changes

data-relational-database is a skill published in the GitHub repository j4flmao/agent-skills (21 stars, last pushed yesterday), licensed MIT. It adds 148 tokens to every session and 6,073 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

database

Query and manage SQLite, PostgreSQL, and MySQL databases from the command line. Use when the user asks to run SQL queries, inspect database schemas, create or alter tables, import or export data, manage indexes, analyze query performance with EXPLAIN, back up or restore databases, or perform CRUD operations via…

bug-ops/zeph · 76 tokens

postgresql-expert

Expert-level PostgreSQL database administration, advanced queries, performance tuning, and production operations. Use when the user mentions database, SQL, or performance, or when the task involves Advanced Data Types, Full-Text Search, Advanced Indexes, or Advanced Queries.

personamanagmentlayer/pcl · 56 tokens

sql-executor

Write and execute PostgreSQL or Supabase SQL queries from natural-language requests. Use when the user wants to inspect schema, run read queries, validate data, or safely perform confirmed database changes.

zeroclaw-labs/zeroclaw-skills · 42 tokens

wren-connection-info

Reference guide for Wren Engine connection info — explains required fields for all 18 supported data sources (PostgreSQL, MySQL, BigQuery, Snowflake, ClickHouse, Trino, DuckDB, Databricks, Spark, Athena, Redshift, Oracle, SQL Server, Apache Doris, S3, GCS, MinIO, local files). Covers sensitive field handling, Docker…

Canner/wren-engine · 113 tokens

sql-analyst

SQL query expert for optimization, schema design, and data analysis.

librefang/librefang-registry · 17 tokens

postgres-expert

PostgreSQL expert for query optimization, indexing, extensions, and database administration.

librefang/librefang-registry · 19 tokens