Find the perfect capability for your agent.
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch jobs, scheduling tasks, serving APIs with GPU acceleration, or scaling compute-intensive workloads. Triggers on requests for serverless GPU infrastructure, LLM inference, model training/fine-tuning, parallel data processing, cron jobs in the cloud, or deploying Python web endpoints.
You are a highly skilled AI Engineer specializing in the practical application of machine learning models. You are an expert in Python and popular AI/ML frameworks like TensorFlow, PyTorch, and scikit-learn. You excel at data preprocessing, model training, evaluation, and deployment.
Patterns for using Peewee ORM with DatabaseProxy and scoped connections/transactions. Use when setting up DatabaseProxy, managing connection_context/atomic blocks, or writing tests with SQLite.
为新入职员工或代码审查者生成结构化的代码阅读路径指南。自动分析项目架构,识别技术栈和分层结构,按照从上层到底层的顺序生成渐进式阅读计划。适用场景:(1)新员工项目onboarding,(2)代码审查准备,(3)系统重构前分析,(4)技术债务评估。支持Java/Spring、Node.js、Python等常见技术栈。
Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Teaches thinking, not copying.
You are a seasoned backend architect with deep expertise in designing scalable, resilient, and secure server-side systems. You are proficient in multiple programming languages (like Go, Python, Node.js), database technologies (SQL and NoSQL), and cloud-native architectures (microservices, serverless). You prioritize system performance, data integrity, and long-term maintainability.
Queries Nx workspace metadata, project configurations, affected detection, generator schemas, and dependency graphs via unified Python CLI. Use when analyzing monorepo structure, inspecting project.json configurations, determining affected projects for CI optimization, discovering available generators, or visualizing workspace dependencies.
Review code for bugs, security vulnerabilities, performance issues, accessibility gaps, and CLAUDE.md workflow compliance. Supports any tech stack - HTML/CSS/JS, React, TypeScript, Node.js, Python, NestJS, Next.js, and more. Use when completing features, before commits, or reviewing pull requests.
Provides Django web framework expertise including project structure, models, views, admin, Celery tasks, testing, and Python best practices. Use when generating, analyzing, refactoring, or reviewing Django/Python code.
Python project workflow and standards using Astral uv for environments/dependencies, ty for type checking, typer for CLI, ruff for lint/format, pytest and pytest-cov for tests/coverage, and loguru for logging. Use for Python project setup, dependency management, CLI/logging patterns, type checking, testing, linting/formatting, and packaging guidance.
Generate Python boilerplate code for DAPR microservices, workflows, and actors. Creates properly structured services with DAPR SDK integration, health endpoints, logging, and best practices. Use when creating new services, adding DAPR features, or scaffolding projects.
UV/UVX/Ruff toolchain for DiscoHy Thread Operad with Python packaging and linting
UV/UVX/Ruff toolchain for DiscoHy Thread Operad with Python packaging and linting
Universal Python development guidelines and best practices
Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.
Enterprise-grade Python expertise with production patterns for Python 3.13.9, FastAPI 0.115.x, Django 5.2 LTS, Pydantic v2, SQLAlchemy 2.0; activates for API development, ORM usage, async patterns, testing frameworks, and production deployment strategies.
Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems. | Sử dụng khi xây dựng API, server, backend, máy chủ, xử lý dữ liệu, endpoint, microservices.
Python開発ガイド。FastAPI、Django、Flask、型ヒント、非同期処理、データ処理、パフォーマンス最適化など、Pythonアプリケーション開発のベストプラクティス。
Modern Python backend stack: FastAPI, SQLAlchemy 2.0, Pydantic v2, uv, ruff. Use when: building Python APIs, async services, or working with Python backend code. Triggers: "fastapi", "python backend", "sqlalchemy", "pydantic", "uv", "ruff", "python api", "async python".
Modern Python development with Python 3.12+, Django, FastAPI, async patterns,
