hivemind: Skill for Claude Code

.claude/skills/sqlalchemy-orm/SKILL.md

sqlalchemy-orm is a skill for Claude Code from cohen-liel/hivemind. It costs 32 tokens per session (895 once invoked), scanned A, original, Apache-2.0.

A set of SQLAlchemy 2.0 patterns for using Python with databases asynchronously. It covers database connections, data models, relationships, queries, and schema changes called migrations.

In plain words
What is it for?
Use it when defining SQLAlchemy models, connecting to a database, loading related records, writing queries, or creating migrations in an async Python project.
Why use it?
It helps avoid repeating setup and common mistakes when building database-backed Python applications that do not want to pause while waiting for database work.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is cohen-liel/hivemind's own configuration. It tells Claude Code how to work on hivemind 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 hivemind configures →

Reuse

Borrowing it

Nothing to install: this file belongs to cohen-liel/hivemind. 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/cohen-liel/hivemind/main/.claude/skills/sqlalchemy-orm/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/cohen-liel/hivemind

Made for: Claude Code.

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README.md
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Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 895 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 $0.00032 $0.00895
Opus 5.5 $0.00013 $0.00358
Sonnet 5.5 $0.00006 $0.00179
Haiku 4.5 $0.00003 $0.00089

Measured 1mo ago against content hash a7fef59ec648, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

sqlalchemy-orm 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.

.claude/skills/sqlalchemy-orm/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SQLAlchemy 2.0 Async ORM Patterns

Database Setup

# database.py
from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker, AsyncSession
from sqlalchemy.orm import DeclarativeBase

engine = create_async_engine(
    settings.DATABASE_URL,  # postgresql+asyncpg://user:pass@host/db
    pool_size=10,
    max_overflow=20,
    pool_pre_ping=True,  # Verify connection before use
    echo=settings.DEBUG,
)

AsyncSessionLocal = async_sessionmaker(engine, expire_on_commit=False)

class Base(DeclarativeBase):
    pass

Model Pattern

from sqlalchemy import String, ForeignKey, func, text
from sqlalchemy.orm import Mapped, mapped_column, relationship

class TimestampMixin:
    created_at: Mapped[datetime] = mapped_column(
        server_default=func.now(), nullable=False
    )
    updated_at: Mapped[datetime] = mapped_column(
        server_default=func.now(), onupdate=func.now(), nullable=False
    )

class User(Base, TimestampMixin):
    __tablename__ = "users"

    id: Mapped[int] = mapped_column(primary_key=True)
    email: Mapped[str] = mapped_column(String(255), unique=True, nullable=False, index=True)
    name: Mapped[str] = mapped_column(String(100), nullable=False)
    hashed_password: Mapped[str] = mapped_column(nullable=False)
    is_active: Mapped[bool] = mapped_column(default=True, server_default=text("true"))

    # Relationship
    posts: Mapped[list["Post"]] = relationship("Post", back_populates="author", lazy="select")

class Post(Base, TimestampMixin):
    __tablename__ = "posts"

    id: Mapped[int] = mapped_column(primary_key=True)
    user_id: Mapped[int] = mapped_column(ForeignKey("users.id"), nullable=False, index=True)
    title: Mapped[str] = mapped_column(String(255), nullable=False)
    body: Mapped[str] = mapped_column(nullable=False)

    author: Mapped["User"] = relationship("User", back_populates="posts")

CRUD Patterns

# SELECT with filter
async def get_user(db: AsyncSession, user_id: int) -> User | None:
    return await db.get(User, user_id)

async def get_user_by_email(db: AsyncSession, email: str) -> User | None:
    result = await db.execute(select(User).where(User.email == email))
    return result.scalar_one_or_none()

# SELECT with join (avoid N+1)
async def get_posts_with_authors(db: AsyncSession) -> list[Post]:
    result = await db.execute(
        select(Post).options(selectinload(Post.author)).order_by(Post.created_at.desc())
    )
    return list(result.scalars())

# INSERT
async def create_user(db: AsyncSession, data: UserCreate) -> User:
    user = User(**data.model_dump())
    db.add(user)
    await db.flush()  # Get ID without committing
    await db.refresh(user)
    return user

# UPDATE
async def update_user(db: AsyncSession, user_id: int, data: dict) -> User:
    await db.execute(update(User).where(User.id == user_id).values(**data))
    return await get_user(db, user_id)

# Bulk insert
async def bulk_create_posts(db: AsyncSession, posts: list[dict]):
    await db.execute(insert(Post), posts)

Read the full file on GitHub · 107 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. 1mo ago First seen · 107 lines · 32 tokens per session scan A a7fef59ec648

Subscribe to this mod's changes

sqlalchemy-orm is a skill published in the GitHub repository cohen-liel/hivemind (112 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 32 tokens to every session and 895 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 2026-08-30.

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