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sqlalchemy

Python SQL toolkit and ORM for defining schemas and issuing SQL/ORM queries with explicit transaction control.

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SKILL.md

Imports

python
import sqlalchemy
from sqlalchemy import (
    create_engine,
    text,
    select,
    insert,
    update,
    delete,
    bindparam,
    ForeignKey,
    Integer,
    String,
    Column,
    MetaData,
    Table,
    event,
)
from sqlalchemy.orm import (
    DeclarativeBase,
    Mapped,
    mapped_column,
    relationship,
    Session,
    sessionmaker,
    joinedload,
)
from sqlalchemy.ext.associationproxy import association_proxy

Core Patterns

Engine + explicit transactions (Core) ✅ Current

python
from __future__ import annotations

from sqlalchemy import create_engine, text

def main() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)

    with engine.begin() as conn:
        conn.execute(text("CREATE TABLE user_account (id INTEGER PRIMARY KEY, name TEXT NOT NULL)"))
        conn.execute(
            text("INSERT INTO user_account (name) VALUES (:name)"),
            [{"name": "alice"}, {"name": "bob"}],
        )

    with engine.connect() as conn:
        rows = conn.execute(text("SELECT id, name FROM user_account ORDER BY id")).all()
        print(rows)

if __name__ == "__main__":
    main()
  • Use engine.begin() for an explicit transaction boundary (commit on success, rollback on error).
  • Use text() with bound parameters (e.g., :name) instead of string interpolation.

SQL Expression Language CRUD with bound parameters ✅ Current

python
from __future__ import annotations

from sqlalchemy import create_engine, Integer, String, bindparam, select, insert, update, delete
from sqlalchemy import MetaData, Table, Column

def main() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    metadata = MetaData()

    user_account = Table(
        "user_account",
        metadata,
        Column("id", Integer, primary_key=True),
        Column("name", String, nullable=False),
    )

    metadata.create_all(engine)

    with engine.begin() as conn:
        conn.execute(insert(user_account), [{"name": "alice"}, {"name": "bob"}])

        # UPDATE with bound parameters (safe + cacheable)
        conn.execute(
            update(user_account)
            .where(user_account.c.name == bindparam("old_name"))
            .values(name=bindparam("new_name")),
            {"old_name": "bob", "new_name": "robert"},
        )

        # SELECT
        names = conn.execute(select(user_account.c.id, user_account.c.name).order_by(user_account.c.id)).all()
        print(names)

        # DELETE
        conn.execute(delete(user_account).where(user_account.c.name == "alice"))

    with engine.connect() as conn:
        remaining = conn.execute(select(user_account.c.name).order_by(user_account.c.name)).scalars().all()
        print(remaining)

if __name__ == "__main__":
    main()
  • Prefer select()/insert()/update()/delete() over handwritten SQL when practical.
  • Use bindparam() for explicit parameter binding in reusable statements.

Declarative ORM models + relationships ✅ Current

python
from __future__ import annotations

from typing import List

from sqlalchemy import create_engine, ForeignKey, String
from sqlalchemy.orm import DeclarativeBase, Mapped, Session, mapped_column, relationship

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"

    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)

    addresses: Mapped[List["Address"]] = relationship(back_populates="user", cascade="all, delete-orphan")

class Address(Base):
    __tablename__ = "address"

    id: Mapped[int] = mapped_column(primary_key=True)
    email: Mapped[str] = mapped_column(String(255), nullable=False)
    user_id: Mapped[int] = mapped_column(ForeignKey("user_account.id"), nullable=False)

    user: Mapped[User] = relationship(back_populates="addresses")

def main() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    Base.metadata.create_all(engine)

    with Session(engine) as session:
        u = User(name="alice", addresses=[Address(email="[email protected]")])
        session.add(u)
        session.commit()

    with Session(engine) as session:
        users = session.execute(
            sqlalchemy.select(User).order_by(User.id)  # type: ignore[attr-defined]
        ).scalars().all()
        print([(user.id, user.name, [a.email for a in user.addresses]) for user in users])

if __name__ == "__main__":
    main()
  • Use DeclarativeBase, Mapped[...], and mapped_column() for SQLAlchemy 2.0-style typed ORM mappings.
  • Model relationships explicitly with relationship() and ForeignKey().

ORM unit-of-work with explicit commit/rollback ✅ Current

python
from __future__ import annotations

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

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)

def main() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    Base.metadata.create_all(engine)

    # Write transaction
    with Session(engine) as session:
        session.add_all([User(name="alice"), User(name="bob")])
        session.commit()

    # Read-only pattern (no commit needed)
    with Session(engine) as session:
        names = session.execute(select(User.name).order_by(User.name)).scalars().all()
        print(names)

if __name__ == "__main__":
    main()
  • ORM changes are not durable until Session.commit() succeeds; structure code around clear unit-of-work boundaries.
  • Use Session(...) as a context manager to ensure resources are released.

Eager loading relationships ✅ Current

python
from __future__ import annotations

from typing import List

from sqlalchemy import create_engine, ForeignKey, String, select
from sqlalchemy.orm import DeclarativeBase, Mapped, Session, mapped_column, relationship, joinedload

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)
    addresses: Mapped[List["Address"]] = relationship(back_populates="user")

class Address(Base):
    __tablename__ = "address"
    id: Mapped[int] = mapped_column(primary_key=True)
    email: Mapped[str] = mapped_column(String(255), nullable=False)
    user_id: Mapped[int] = mapped_column(ForeignKey("user_account.id"), nullable=False)
    user: Mapped[User] = relationship(back_populates="addresses")

def main() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    Base.metadata.create_all(engine)

    with Session(engine) as session:
        session.add(User(name="alice", addresses=[Address(email="[email protected]")]))
        session.commit()

    # Eager load addresses with JOIN to avoid N+1 queries
    with Session(engine) as session:
        stmt = select(User).options(joinedload(User.addresses)).order_by(User.id)
        users = session.execute(stmt).scalars().unique().all()
        print([(u.name, [a.email for a in u.addresses]) for u in users])

if __name__ == "__main__":
    main()
  • Use joinedload() to eagerly load relationships using a JOIN, avoiding N+1 query problems.
  • Call .unique() after .scalars() when using joinedload() to deduplicate results.

Association proxy for simplified many-to-many access ✅ Current

python
from __future__ import annotations

from typing import List

from sqlalchemy import create_engine, ForeignKey, String, select
from sqlalchemy.orm import DeclarativeBase, Mapped, Session, mapped_column, relationship
from sqlalchemy.ext.associationproxy import association_proxy

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)
    
    user_keywords: Mapped[List["UserKeyword"]] = relationship(back_populates="user")
    keywords: Mapped[List[str]] = association_proxy(
        "user_keywords", "keyword", 
        creator=lambda kw: UserKeyword(keyword=kw)
    )

class UserKeyword(Base):
    __tablename__ = "user_keyword"
    user_id: Mapped[int] = mapped_column(ForeignKey("user_account.id"), primary_key=True)
    keyword: Mapped[str] = mapped_column(String(50), primary_key=True)
    user: Mapped[User] = relationship(back_populates="user_keywords")

def main() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    Base.metadata.create_all(engine)

    with Session(engine) as session:
        u = User(name="alice", keywords=["python", "sql"])
        session.add(u)
        session.commit()

    with Session(engine) as session:
        user = session.execute(select(User)).scalars().first()
        print(user.keywords)  # Access keywords directly without going through association table

if __name__ == "__main__":
    main()
  • Use association_proxy() to simplify access to many-to-many relationships by hiding the association table.
  • Provide a creator function to construct association objects from scalar values.

Event listening ✅ Current

python
from __future__ import annotations

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

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)

def after_insert_listener(mapper, connection, target):
    """Called after an INSERT on User"""
    print(f"Inserted user: {target.name}")

# Register event listener
event.listen(User, "after_insert", after_insert_listener)

def main() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    Base.metadata.create_all(engine)

    with Session(engine) as session:
        session.add(User(name="alice"))
        session.commit()  # Triggers the after_insert event

if __name__ == "__main__":
    main()
  • Use event.listen() to register event listeners on ORM classes, engine connections, or sessions.
  • Common events include before_insert, after_insert, before_update, after_update, before_delete, after_delete.

Configuration

  • Database URL: pass to create_engine() (sync) as "dialect+driver://user:pass@host/dbname".
    • SQLite in-memory: "sqlite+pysqlite:///:memory:"
  • Connection pooling: configured via create_engine() kwargs (e.g., pool_size, max_overflow, pool_pre_ping).
  • Echo / SQL logging: create_engine(..., echo=True) to log SQL emitted by SQLAlchemy.
  • Session configuration:
    • Create ad-hoc sessions with Session(engine).
    • Or create a factory with sessionmaker(bind=engine) for application-wide reuse.
    • Configure session behavior: autoflush=True (default), expire_on_commit=True (default).
  • Transactions:
    • Core: prefer with engine.begin() as conn: ...
    • ORM: prefer with Session(engine) as session: ...; session.commit()
  • Parameter binding: always use bound parameters (text("... :name"), bindparam("name")) rather than interpolating literals into SQL strings.
  • Eager loading: use joinedload(), selectinload(), or subqueryload() to control relationship loading strategy.

Pitfalls

Wrong: assuming ORM add() persists without commit()

python
from __future__ import annotations

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

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
Base.metadata.create_all(engine)

session = Session(engine)
session.add(User(name="alice"))
session.close()  # closes without commit; transaction is rolled back

Right: commit within a clear unit of work

python
from __future__ import annotations

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

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
Base.metadata.create_all(engine)

with Session(engine) as session:
    session.add(User(name="alice"))
    session.commit()

Wrong: SQL injection via string interpolation with exec_driver_sql()

python
from __future__ import annotations

from sqlalchemy import create_engine

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)

name = "alice' OR 1=1 --"
with engine.connect() as conn:
    conn.exec_driver_sql(f"SELECT '{name}'")  # interpolated SQL; unsafe pattern

Right: use text() + bound parameters

python
from __future__ import annotations

from sqlalchemy import create_engine, text

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)

name = "alice' OR 1=1 --"
with engine.connect() as conn:
    value = conn.execute(text("SELECT :name"), {"name": name}).scalar_one()
    print(value)

Wrong: forgetting to wrap Core writes in a transaction

python
from __future__ import annotations

from sqlalchemy import create_engine, text

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)

with engine.connect() as conn:
    conn.execute(text("CREATE TABLE t (id INTEGER PRIMARY KEY, name TEXT)"))
    conn.execute(text("INSERT INTO t (name) VALUES ('alice')"))
    # no commit; many DBAPIs will roll back when the connection closes

Right: use engine.begin() for Core writes

python
from __future__ import annotations

from sqlalchemy import create_engine, text

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)

with engine.begin() as conn:
    conn.execute(text("CREATE TABLE t (id INTEGER PRIMARY KEY, name TEXT)"))
    conn.execute(text("INSERT INTO t (name) VALUES (:name)"), {"name": "alice"})

Wrong: selecting ORM entities but not using .scalars()

python
from __future__ import annotations

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

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
Base.metadata.create_all(engine)

with Session(engine) as session:
    session.add_all([User(name="alice"), User(name="bob")])
    session.commit()

with Session(engine) as session:
    rows = session.execute(select(User)).all()
    # rows are Row objects containing User at index 0, not a list[User]
    users = [r for r in rows]
    print(users)

Right: use .scalars() to get mapped instances

python
from __future__ import annotations

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

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
Base.metadata.create_all(engine)

with Session(engine) as session:
    session.add_all([User(name="alice"), User(name="bob")])
    session.commit()

with Session(engine) as session:
    users = session.execute(select(User).order_by(User.id)).scalars().all()
    print([u.name for u in users])

Wrong: not calling .unique() after .scalars() with joinedload()

python
from __future__ import annotations

from typing import List

from sqlalchemy import create_engine, ForeignKey, String, select
from sqlalchemy.orm import DeclarativeBase, Mapped, Session, mapped_column, relationship, joinedload

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)
    addresses: Mapped[List["Address"]] = relationship()

class Address(Base):
    __tablename__ = "address"
    id: Mapped[int] = mapped_column(primary_key=True)
    email: Mapped[str] = mapped_column(String(255), nullable=False)
    user_id: Mapped[int] = mapped_column(ForeignKey("user_account.id"), nullable=False)

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
Base.metadata.create_all(engine)

with Session(engine) as session:
    session.add(User(name="alice", addresses=[
        Address(email="[email protected]"),
        Address(email="[email protected]")
    ]))
    session.commit()

with Session(engine) as session:
    stmt = select(User).options(joinedload(User.addresses))
    users = session.execute(stmt).scalars().all()
    # Returns duplicate User objects (one per joined address row)
    print(len(users))  # 2 instead of 1

Right: call .unique() to deduplicate after joinedload()

python
from __future__ import annotations

from typing import List

from sqlalchemy import create_engine, ForeignKey, String, select
from sqlalchemy.orm import DeclarativeBase, Mapped, Session, mapped_column, relationship, joinedload

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)
    addresses: Mapped[List["Address"]] = relationship()

class Address(Base):
    __tablename__ = "address"
    id: Mapped[int] = mapped_column(primary_key=True)
    email: Mapped[str] = mapped_column(String(255), nullable=False)
    user_id: Mapped[int] = mapped_column(ForeignKey("user_account.id"), nullable=False)

engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
Base.metadata.create_all(engine)

with Session(engine) as session:
    session.add(User(name="alice", addresses=[
        Address(email="[email protected]"),
        Address(email="[email protected]")
    ]))
    session.commit()

with Session(engine) as session:
    stmt = select(User).options(joinedload(User.addresses))
    users = session.execute(stmt).scalars().unique().all()
    print(len(users))  # 1 (deduplicated)
    print(len(users[0].addresses))  # 2

References

Migration from v1.4

  • SQLAlchemy 2.0 formalizes "2.0 style" usage that was available in 1.4:
    • Prefer select() constructs and Session.execute(select(...)) over legacy Query patterns.
    • Prefer explicit transaction scopes: engine.begin() (Core) and Session(...); commit() (ORM).
    • Prefer typed ORM mappings: DeclarativeBase, Mapped[...], mapped_column().

Legacy ORM query style ⚠️ Soft Deprecation

  • Deprecated since: 1.4 (2.0-style recommended)
  • Still works: True (in many configurations), but prefer 2.0 style for new code
  • Modern alternative: Session.execute(select(...)).scalars()
  • Migration guidance: replace session.query(Model).filter(...) with session.execute(select(Model).where(...)).scalars()
python
from __future__ import annotations

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

class Base(DeclarativeBase):
    pass

class User(Base):
    __tablename__ = "user_account"
    id: Mapped[int] = mapped_column(primary_key=True)
    name: Mapped[str] = mapped_column(String(50), nullable=False)

def main() -> None:
    engine = create_engine("sqlite+pysqlite:///:memory:", future=True)
    Base.metadata.create_all(engine)

    with Session(engine) as session:
        session.add_all([User(name="alice"), User(name="bob")])
        session.commit()

    with Session(engine) as session:
        # 2.0 style:
        users = session.execute(select(User).where(User.name == "alice")).scalars().all()
        print([u.name for u in users])

if __name__ == "__main__":
    main()

API Reference

  • sqlalchemy.create_engine(url, **kwargs) - Create an Engine; key kwargs include echo, pool options, and dialect/driver URL.
  • sqlalchemy.Engine.connect() - Acquire a Connection for SQL execution (explicit transaction management required for writes).
  • sqlalchemy.Engine.begin() - Context manager that provides a Connection with an explicit transaction (commit/rollback).
  • sqlalchemy.text(sql_text) - Create a textual SQL statement supporting bound parameters (:name).
  • sqlalchemy.select(*entities) - Build a SELECT statement from tables/columns/ORM entities.
  • sqlalchemy.insert(table) - Build an INSERT statement.
  • sqlalchemy.update(table) - Build an UPDATE statement.
  • sqlalchemy.delete(table) - Build a DELETE statement.
  • sqlalchemy.bindparam(name) - Define an explicit bound parameter for SQL constructs.
  • sqlalchemy.Column(*args, primary_key=False, nullable=True, **kwargs) - Define a table column (legacy Core API, prefer mapped_column() for ORM).
  • sqlalchemy.ForeignKey(column, *, onupdate=None, ondelete=None, **kwargs) - Define a foreign key constraint.
  • sqlalchemy.Integer() - Integer column type.
  • sqlalchemy.String(length=None) - String/VARCHAR column type.
  • sqlalchemy.MetaData() - Container object for schema constructs like Table.
  • sqlalchemy.Table(name, metadata, *columns, **kwargs) - Represent a database table in Core.
  • sqlalchemy.event.listen(target, identifier, fn, **kwargs) - Register an event listener on a target object.
  • sqlalchemy.orm.Session(bind=None, *, autoflush=True, expire_on_commit=True, **kwargs) - ORM session (unit of work / identity map); use commit() to persist.
  • sqlalchemy.orm.Session.add(instance) - Add an object to the session.
  • sqlalchemy.orm.Session.add_all(instances) - Add multiple objects to the session.
  • sqlalchemy.orm.Session.commit() - Commit the current transaction.
  • sqlalchemy.orm.Session.execute(statement, params=None, **kwargs) - Execute a SQL statement and return a Result.
  • sqlalchemy.orm.Session.scalars(statement, params=None, **kwargs) - Execute a statement and return scalar results.
  • sqlalchemy.orm.sessionmaker(bind=engine, **kwargs) - Factory for creating configured Session objects.
  • sqlalchemy.orm.DeclarativeBase - Base class for declarative ORM mappings (2.0 style).
  • sqlalchemy.orm.Mapped[T] - Typing annotation used for ORM-mapped attributes.
  • sqlalchemy.orm.mapped_column(*args, primary_key=False, nullable=None, default=None, **kwargs) - Declare an ORM-mapped column with typing support.
  • sqlalchemy.orm.relationship(argument=None, *, cascade=None, backref=None, lazy='select', **kwargs) - Define ORM relationships between mapped classes.
  • sqlalchemy.orm.joinedload(attr, *, innerjoin=False) - Eager load a relationship using a JOIN.
  • sqlalchemy.ext.associationproxy.association_proxy(target_collection, attr, **kwargs) - Create an association proxy for simplified many-to-many access.
  • sqlalchemy.orm.Query ⚠️ - Legacy query API (soft deprecation; prefer select() for 2.0 style).

Current Library State

SQLAlchemy 2.0 is a mature, production-ready ORM and SQL toolkit following these core principles:

Philosophy

  • Transactions as the norm: Nothing persists until commit() is called explicitly.
  • Bound parameters everywhere: Never render literal values in SQL; use bound parameters to prevent SQL injection and enable query plan caching.
  • Choose the right tool: Use Core for SQL operations that don't need object mapping; use ORM when you need the data mapper pattern.
  • Full SQL exposure: SQLAlchemy exposes relational database functionality fully rather than hiding it.
  • Developer control: You control all design decisions regarding object model structure, schema design, and naming conventions.

Key Capabilities

  • Identity map: Session maintains a single instance per database identity within a session.
  • Unit of work: Changes are tracked and flushed to the database as a coordinated unit.
  • Data mapper pattern: Separates domain model from relational schema with explicit mappings.
  • Declarative configuration: Define ORM models with typed attributes using DeclarativeBase and Mapped[...].
  • Query construction: Build SQL queries using Pythonic constructs that render to optimized SQL.
  • Eager loading control: Choose loading strategies (joined, selectin, subquery, lazy) per-query.
  • Connection pooling: Built-in connection pool management with configurable sizing and behavior.
  • Schema metadata: Reflect existing database schemas or define new ones programmatically.
  • Event system: Hook into ORM and Core operations with event listeners.

Common Pitfalls

  • Transaction management: Assuming changes persist without calling commit() - they don't.
  • SQL injection: Using string interpolation instead of bound parameters - always use bound parameters.
  • Wrong tool selection: Using ORM when Core would suffice - ORM adds overhead for simple operations.
  • Query responsibility: Blaming SQLAlchemy for bad queries - you control query structure including joins, subqueries, and correlation.
  • Impedance mismatch: Expecting databases to behave like object collections (or vice versa) - use SQLAlchemy's mediation patterns.

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majiayu000/claude-skill-registry

agent-ops-spec

Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.

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majiayu000/claude-skill-registry

agent-ops-testing

Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.

163 31
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majiayu000/claude-skill-registry

agent-ops-testing

Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.

163 31
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majiayu000/claude-skill-registry

agent-ops-state

Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.

163 31
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