ai-agents-workspace-starter: Skill for Claude Code

.agents/skills/database-patterns/SKILL.md

database-patterns is a skill for Claude Code, Codex from systemowiec/ai-agents-workspace-starter. It costs 18 tokens per session (755 once invoked), scanned A, original, MIT.

A set of project rules for connecting application code to a MariaDB database using SQLAlchemy and Alembic. It describes how to separate business logic, database models, repositories, and schema migrations.

In plain words
What is it for?
Use it when creating or changing database models, repositories, migrations, async queries, or database connection code in this project.
Why use it?
It keeps database code organised and prevents application logic from depending directly on the database library. It also documents the expected connection settings and Docker hostname.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is systemowiec/ai-agents-workspace-starter's own configuration. It tells Claude Code and Codex how to work on ai-agents-workspace-starter itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ai-agents-workspace-starter configures →

Reuse

Borrowing it

Nothing to install: this file belongs to systemowiec/ai-agents-workspace-starter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/systemowiec/ai-agents-workspace-starter/main/.agents/skills/database-patterns/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/systemowiec/ai-agents-workspace-starter

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 database-patterns

README.md
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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.

agentmods 80×15 button for database-patterns

Your own site · 80×15
<a href="https://agentmods.dev/skills/systemowiec/ai-agents-workspace-starter/database-patterns"><img src="https://agentmods.dev/badge/skills/systemowiec/ai-agents-workspace-starter/database-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 755 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 $0.00018 $0.00755
Opus 5.5 $0.00007 $0.00302
Sonnet 5.5 $0.00004 $0.00151
Haiku 4.5 $0.00002 $0.00076

Measured 2mo ago against content hash 854d09084a22, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

database-patterns 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.

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.

.agents/skills/database-patterns/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Database Patterns

Database access patterns. Read when working with models, repositories, migrations.


Stack

  • MariaDB 11+ (MySQL-compatible)
  • SQLAlchemy 2.x async (asyncmy driver)
  • Alembic for migrations
  • Container: infra/docker-compose.yml -> service mariadb

Connection

  • Env var: DATABASE_URL=mysql+asyncmy://${DB_USER}:${DB_PASSWORD}@mariadb:3306/${DB_NAME}
  • Inside Docker use hostname mariadb (service name), NOT localhost.

Repository Pattern (Hexagonal)

The database is an adapter. Never import SQLAlchemy in the domain/application layer.

domain/
  ports.py          -> ABC interfaces (UserRepository, OrderRepository)
  entities.py       -> Pure Python classes (dataclass, no ORM)

application/
  services.py       -> Uses ports (DI), unaware of SQLAlchemy

infrastructure/
  adapters/
    db/
      models.py     -> SQLAlchemy ORM models (Base, User, Order)
      repositories.py -> Port implementations (SQLAlchemy queries)
      session.py    -> AsyncSession factory

Port (interface)

  • File: domain/ports.py
  • ABC class with @abstractmethod async methods (e.g. get_by_id, save, list_active)
  • Return domain entities, not ORM models

Adapter (implementation)

  • File: infrastructure/adapters/db/repositories.py
  • Accept AsyncSession in __init__
  • Use session.get() + .to_entity() for retrieval
  • Use session.add() + session.flush() for persistence (NOT session.commit() - let session factory handle commit)

ORM Model

  • File: infrastructure/adapters/db/models.py
  • Inherit from DeclarativeBase
  • Implement to_entity() instance method and from_entity() classmethod for domain entity conversion
  • Use Column with explicit types, indexes, and constraints

Session Factory

  • File: infrastructure/adapters/db/session.py
  • create_async_engine + async_sessionmaker with expire_on_commit=False
  • Wrap in async with session.begin(): to auto-commit/rollback
  • Use as FastAPI dependency via Depends(get_session)

Read the full file on GitHub · 96 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. 2mo ago First seen · 96 lines · 18 tokens per session scan A 854d09084a22

Subscribe to this mod's changes

database-patterns is a skill published in the GitHub repository systemowiec/ai-agents-workspace-starter (2 stars, last pushed 7mo ago), licensed MIT. It adds 18 tokens to every session and 755 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 2026-08-31.

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