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.
npx agentmods add skills/kid-sid/codex-spellbook/sqlalchemynpx skills add kid-sid/codex-spellbook --skill sqlalchemygit clone --depth 1 https://github.com/kid-sid/codex-spellbookWhat 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 | $0.00041 | $0.03240 |
| Opus 5 | $0.00020 | $0.01620 |
| Sonnet 5 | $0.00008 | $0.00648 |
| Haiku 4.5 | $0.00004 | $0.00324 |
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 2d 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 — 397 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQLAlchemy 2.0 — Async Patterns
Modern SQLAlchemy 2.0 with full async support (asyncpg) and Alembic migrations.
When to Activate
- Defining ORM models with
Mapped/mapped_column - Writing async queries (
select,join,filter,order_by) - Managing async sessions (
AsyncSession,async_sessionmaker) - Handling relationships and loading strategies (
selectin,joined,lazy) - Running database transactions or bulk operations
- Writing or debugging Alembic migrations
- Converting between ORM models and domain entities
Model Definition (SQLAlchemy 2.0 style)
from datetime import datetime
from uuid import UUID, uuid4
from sqlalchemy import String, ForeignKey, Text, TIMESTAMP, func
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, relationship
from sqlalchemy.dialects.postgresql import UUID as PGUUID, JSONB
class Base(DeclarativeBase):
pass
class UserORM(Base):
__tablename__ = "users"
id: Mapped[UUID] = mapped_column(PGUUID(as_uuid=True), primary_key=True, default=uuid4)
email: Mapped[str] = mapped_column(String(255), unique=True, nullable=False, index=True)
name: Mapped[str] = mapped_column(String(255), nullable=False)
role: Mapped[str] = mapped_column(String(50), nullable=False, default="user")
metadata_: Mapped[dict] = mapped_column("metadata", JSONB, nullable=False, default=dict)
created_at: Mapped[datetime] = mapped_column(
TIMESTAMP(timezone=True), server_default=func.now(), nullable=False
)
updated_at: Mapped[datetime] = mapped_column(
TIMESTAMP(timezone=True), server_default=func.now(), onupdate=func.now()
)
# Relationship — loads orders when accessed
orders: Mapped[list["OrderORM"]] = relationship("OrderORM", back_populates="user")
class OrderORM(Base):
__tablename__ = "orders"
id: Mapped[UUID] = mapped_column(PGUUID(as_uuid=True), primary_key=True, default=uuid4)
user_id: Mapped[UUID] = mapped_column(
PGUUID(as_uuid=True), ForeignKey("users.id", ondelete="CASCADE"), nullable=False, index=True
)
status: Mapped[str] = mapped_column(String(50), nullable=False, default="pending")
total: Mapped[float] = mapped_column(nullable=False)
created_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True), server_default=func.now())
user: Mapped["UserORM"] = relationship("UserORM", back_populates="orders")
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.
- 2d ago First seen · 397 lines · 41 tokens per session scan A 1e0371cbef9d
sqlalchemy is a skill published in the GitHub repository kid-sid/codex-spellbook (21 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 3,240 once invoked, about $0.0002 per session on Opus 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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