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.
git clone --depth 1 https://github.com/nedcodes-ok/cursorrules-collectionWrote 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.
[](https://agentmods.dev/rules/nedcodes-ok/cursorrules-collection/sqlalchemy)<a href="https://agentmods.dev/rules/nedcodes-ok/cursorrules-collection/sqlalchemy"><img src="https://agentmods.dev/badge/rules/nedcodes-ok/cursorrules-collection/sqlalchemy/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.
<a href="https://agentmods.dev/rules/nedcodes-ok/cursorrules-collection/sqlalchemy"><img src="https://agentmods.dev/badge/rules/nedcodes-ok/cursorrules-collection/sqlalchemy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00507 | $0.00507 |
| Opus 5.5 | $0.00203 | $0.00203 |
| Sonnet 5.5 | $0.00101 | $0.00101 |
| Haiku 4.5 | $0.00051 | $0.00051 |
Grade A, and why
sqlalchemy 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.
How it starts
The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQLAlchemy Cursor Rules
You are an expert in SQLAlchemy 2.0+. Follow these rules:
Models (Declarative)
- Use DeclarativeBase with Mapped[] type annotations for all columns
- mapped_column() over Column() — id: Mapped[int] = mapped_column(primary_key=True)
- Use tablename explicitly on every model — never rely on auto-generation
- Keep models in a dedicated models/ package, one file per domain entity
Relationships
- Use relationship() with back_populates on both sides — never backref
- Set lazy="selectin" or lazy="joined" explicitly — never rely on default lazy loading
- Use Mapped[list["Child"]] for one-to-many, Mapped["Parent"] for many-to-one
- Define cascade="all, delete-orphan" on parent side of one-to-many relationships
Sessions & Transactions
- Use sessionmaker or async_sessionmaker bound to engine — never create sessions manually
- Wrap operations in with Session() as session: blocks for auto-cleanup
- Call session.flush() to get IDs mid-transaction, session.commit() at operation boundaries
- Never share sessions across threads or async tasks
- Use session.execute(select(Model).where(...)) — never session.query() (legacy)
Queries (2.0 Style)
- Use select(), insert(), update(), delete() from sqlalchemy — never string SQL
- Chain .where(), .order_by(), .limit(), .offset() on select statements
- Use .scalars().all() for lists, .scalars().one() for exactly one, .scalars().first() for optional
- Use joinedload(), selectinload() for eager loading in specific queries
Async
- Use create_async_engine() and async_sessionmaker for async code
- Use async with session.begin(): for auto-commit/rollback
- Awaitable versions: await session.execute(), await session.commit()
- Access lazy-loaded relationships only after await session.run_sync() or eager load
Migrations (Alembic)
- Generate migrations with alembic revision --autogenerate -m "description"
- Always review autogenerated migrations — they miss indexes, constraints, data migrations
- Use op.execute() for data transforms, not ORM models in migration files
- Test migrations both upgrade and downgrade before merging
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.
- 1mo ago First seen · 47 lines · 507 tokens per session scan A 63df2c77bfe8
sqlalchemy is a cursor rule published in the GitHub repository nedcodes-ok/cursorrules-collection (38 stars, last pushed 7mo ago), licensed MIT. It adds 507 tokens to every session, about $0.0020 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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