Agent skills for Microsoft Copilot

When to activate: multiprocessing, threading, concurrent.futures, ProcessPoolExecutor, GIL, CPU-bound tasks

When to activate: configuration management, pydantic-settings, env files, feature flags, environment-specific settings

Python data processing pipelines with modular architecture.

When to activate: ETL, data pipeline, Prefect, Airflow, DLT, Polars, batch processing, data quality

When to activate: dataclasses, attrs, msgspec, frozen dataclasses, slots, inheritance, value objects

Write Python and Django code for Saleor — Django ORM patterns, signals, Celery tasks, type hints, migrations, management commands, and…

Set up a Python virtual environment and install Reflex.

When to activate: event-driven architecture, domain events, event sourcing, Kafka, RabbitMQ, NATS

Guidance for structuring a Python/FastAPI backend into layers (routers/services/repositories) and feature-first modules so it stays easy…

When to activate: Strawberry, Graphene, GraphQL, subscriptions, dataloaders, N+1, schema-first design

When to activate: Python logging, structlog, JSON logs, correlation IDs, log levels, observability setup

When to activate: scikit-learn, machine learning pipelines, feature engineering, model evaluation, cross-validation

Complete Python Cloudflare deployment system.

Facilitates the creation of high-performance Python bindings for Rust cores using PyO3 and idiomatic wrapper patterns.

When to activate: Python security review, OWASP, SQL injection, secrets management, authentication, cryptography

Use this when authoring integration tests against a real backend (PostgreSQL, Redis, Kafka, MinIO, NATS, MongoDB), debugging slow or flaky…

Use pytest as the testing framework for its powerful features and clean syntax. pytest automatically discovers tests following these…

AI/ML Python code tutor that provides actionable hints for writing pythonic, high-performance, modern code.

Python visual creation and matplotlib/seaborn patterns for PBIR reports.

Fully sharded data-parallel training for large models.

Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property…