What is database-sharding?

A database design that splits data across multiple database servers instead of keeping everything on one server. The split is based on a chosen shard key, such as a user identifier.

It helps design shard keys, distribute tenants or geographic data, balance database load, and plan queries across shards.

It helps when one database server cannot handle the required data size or read and write volume, but it also requires planning for distributed queries and data placement.

database-sharding — Skill for Claude Code and Codex by aj-geddes

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 aj-geddes/useful-ai-prompts --skill database-sharding

Clone the repo

git clone --depth 1 https://github.com/aj-geddes/useful-ai-prompts

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/aj-geddes/useful-ai-prompts/database-sharding/github.svg)](https://agentmods.dev/skills/aj-geddes/useful-ai-prompts/database-sharding)

Your own site

<a href="https://agentmods.dev/skills/aj-geddes/useful-ai-prompts/database-sharding"><img src="https://agentmods.dev/badge/skills/aj-geddes/useful-ai-prompts/database-sharding/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/aj-geddes/useful-ai-prompts/database-sharding"><img src="https://agentmods.dev/badge/skills/aj-geddes/useful-ai-prompts/database-sharding.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 556 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. Third-party audits

Socket pass 16 Sept 2026
Snyk pass 16 Sept 2026

How audits are shown

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.

Model	Per session	Once invoked
Fable 5.1	$0.00030	$0.00556
Opus 5.5	$0.00012	$0.00222
Sonnet 5.5	$0.00006	$0.00111
Haiku 4.5	$0.00003	$0.00056

Measured 2mo ago against content hash c3afd207227f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

database-sharding 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 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate-schema.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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/database-sharding/SKILL.md · 89 lines

How it starts

The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Overview

Implement horizontal data partitioning across multiple database servers. Covers sharding strategies, consistent hashing, shard key selection, and cross-shard querying patterns.

When to Use

Database size exceeds single server capacity
Read/write throughput needs horizontal scaling
Geographic data distribution requirements
Multi-tenant data isolation
Cost optimization through distributed architecture
Load balancing across database instances

Quick Start

Minimal working example:

-- Define shard ranges
-- Shard 0: user_id 0-999999
-- Shard 1: user_id 1000000-1999999
-- Shard 2: user_id 2000000-2999999

CREATE TABLE users_shard_0 (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  user_id BIGINT NOT NULL,
  email VARCHAR(255) NOT NULL,
  created_at TIMESTAMP DEFAULT NOW(),
  CONSTRAINT shard_0_range CHECK (user_id BETWEEN 0 AND 999999)
);

CREATE TABLE users_shard_1 (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  user_id BIGINT NOT NULL,
  email VARCHAR(255) NOT NULL,
  created_at TIMESTAMP DEFAULT NOW(),
  CONSTRAINT shard_1_range CHECK (user_id BETWEEN 1000000 AND 1999999)
);

-- Function to determine shard
CREATE OR REPLACE FUNCTION get_shard_id(p_user_id BIGINT)
RETURNS INT AS $$
BEGIN
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide	Contents
Range-Based Sharding	Range-Based Sharding
Hash-Based Sharding	Hash-Based Sharding
Directory-Based Sharding	Directory-Based Sharding

Best Practices

✅ DO

Follow established patterns and conventions
Write clean, maintainable code
Add appropriate documentation
Test thoroughly before deploying

Read the full file on GitHub · 89 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

2mo ago First seen · 89 lines · 30 tokens per session scan A c3afd207227f

Subscribe to this mod's changes

database-sharding is a skill published in the GitHub repository aj-geddes/useful-ai-prompts (376 stars, last pushed 8mo ago), licensed MIT. It adds 30 tokens to every session and 556 once invoked, about $0.0001 per session on Opus 5.5. 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.

Databases

database-sharding next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
database-shardingaj-geddes/useful-ai-prompts	Skill	376	8mo ago	MIT	A	30	Claude Code, Codex
create-prprisma/orm	Skill	48k	yesterday	Apache-2.0	A	48	Claude Code, Codex
schema-explorationlangchain-ai/deepagents	Skill	31k	yesterday	MIT	A	57	Claude Code, Codex
atlas-mssqlariga/atlas	Skill	8.8k	yesterday	Apache-2.0	A	163	Claude Code
ha-data-storesshiwenwen/hope-agent	Skill	1.9k	yesterday	MIT	A	115	Claude Code, Codex
nornicdb-cypher-queriesorneryd/NornicDB	Skill	923	yesterday	MIT	A	79	Claude Code, Codex
volcengine-rds-postgresqlbytedance/agentkit-samples	Skill	484	today	Apache-2.0	A	63	Claude Code, Codex

database-sharding