python-database-ops

python-database-ops is a skill for Claude Code from 0xDarkMatter/claude-mods. It costs 43 tokens per session (1,209 once invoked), scanned A, original, MIT.

A set of Python database patterns using SQLAlchemy, a library for working with databases through Python objects and queries. It covers models, sessions, connection pools, asynchronous access, migrations, repositories, and units of work.

In plain words
What is it for?
Use it to define database models, create engines and sessions, query records, configure asynchronous SQLAlchemy, and work with Alembic migrations.
Why use it?
It helps structure database access and manage connections, queries, transactions, and schema changes consistently.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Part of the claude-mods plugin — 112 skills, 3 commands, 3 agents, 4 hooks shipped together

Good fit Use it to define database models, create engines and sessions, query records, configure asynchronous SQLAlchemy, and work with Alembic migrations.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/0xdarkmatter/claude-mods/python-database-ops
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 0xDarkMatter/claude-mods --skill python-database-ops
Clone the repo
git clone --depth 1 https://github.com/0xDarkMatter/claude-mods

Made for: Claude Code.

Or install claude-mods, the plugin that ships this one along with the rest of its 112 skills, 3 commands, 3 agents, 4 hooks.

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 python-database-ops

README.md
[![agentmods](https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/python-database-ops/github.svg)](https://agentmods.dev/skills/0xdarkmatter/claude-mods/python-database-ops)
Your own site
<a href="https://agentmods.dev/skills/0xdarkmatter/claude-mods/python-database-ops"><img src="https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/python-database-ops/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.

agentmods 80×15 button for python-database-ops

Your own site · 80×15
<a href="https://agentmods.dev/skills/0xdarkmatter/claude-mods/python-database-ops"><img src="https://agentmods.dev/badge/skills/0xdarkmatter/claude-mods/python-database-ops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 43 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,209 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
  • NVIDIA SkillSpector pass 7 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00043 $0.01209
Opus 5.5 $0.00017 $0.00484
Sonnet 5.5 $0.00009 $0.00242
Haiku 4.5 $0.00004 $0.00121

Measured 1mo ago against content hash 72ee9dc2f41b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

python-database-ops 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 1mo 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/python-database-ops/SKILL.md · 188 lines

How it starts

The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Python Database Patterns

SQLAlchemy 2.0 and database best practices.

SQLAlchemy 2.0 Basics

from sqlalchemy import create_engine, select
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, Session

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(100))
    email: Mapped[str] = mapped_column(String(255), unique=True)
    is_active: Mapped[bool] = mapped_column(default=True)

# Create engine and tables
engine = create_engine("postgresql://user:pass@localhost/db")
Base.metadata.create_all(engine)

# Query with 2.0 style
with Session(engine) as session:
    stmt = select(User).where(User.is_active == True)
    users = session.execute(stmt).scalars().all()

Async SQLAlchemy

from sqlalchemy.ext.asyncio import (
    AsyncSession,
    async_sessionmaker,
    create_async_engine,
)
from sqlalchemy import select

# Async engine
engine = create_async_engine(
    "postgresql+asyncpg://user:pass@localhost/db",
    echo=False,
    pool_size=5,
    max_overflow=10,
)

# Session factory
async_session = async_sessionmaker(engine, expire_on_commit=False)

# Usage
async with async_session() as session:
    result = await session.execute(select(User).where(User.id == 1))
    user = result.scalar_one_or_none()

Model Relationships

from sqlalchemy import ForeignKey
from sqlalchemy.orm import relationship, Mapped, mapped_column

class User(Base):
    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str]

    # One-to-many
    posts: Mapped[list["Post"]] = relationship(back_populates="author")

class Post(Base):
    __tablename__ = "posts"

    id: Mapped[int] = mapped_column(primary_key=True)
    title: Mapped[str]
    author_id: Mapped[int] = mapped_column(ForeignKey("users.id"))

    # Many-to-one
    author: Mapped["User"] = relationship(back_populates="posts")

Read the full file on GitHub · 188 lines

Files

What ships with it

6 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.

  1. 1mo ago First seen · 188 lines · 43 tokens per session scan A 72ee9dc2f41b

Subscribe to this mod's changes

python-database-ops is a skill published in the GitHub repository 0xDarkMatter/claude-mods (71 stars, last pushed 8d ago), licensed MIT. It adds 43 tokens to every session and 1,209 once invoked, about $0.0002 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.

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