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Found 2,126 Skills
Python code refactoring skills, covering code smell identification, design pattern application, readability improvement, and practical experience. This skill is applicable when users request "refactor code", "refactor", "code optimization", "improve code quality", "code smell review", "apply design patterns", "enhance readability", or submit code review requests. It supports generating structured refactoring documents after refactoring completion ("output refactoring document", "generate refactoring report"). It includes practical patterns extracted from 20+ real refactoring PRs in the vllm-ascend repository.
Solve Linear Programming (LP), Mixed-Integer Linear Programming (MILP), and Quadratic Programming (QP, beta) with the Python API. Use when the user asks about optimization with linear or quadratic objectives, linear constraints, integer variables, scheduling, resource allocation, facility location, production planning, portfolio optimization, or least squares.
Python backend development expertise for FastAPI, security patterns, database operations, Upstash integrations, and code quality. Use when: (1) Building REST APIs with FastAPI, (2) Implementing JWT/OAuth2 authentication, (3) Setting up SQLAlchemy/async databases, (4) Integrating Redis/Upstash caching, (5) Refactoring AI-generated Python code (deslopification), (6) Designing API patterns, or (7) Optimizing backend performance.
You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate complete project structures with modern tooling (uv, FastAPI, Django), type hint
Use when preparing branches, commits, or PRs for Python changes — scoping work, running validation gates, and ensuring merge readiness. Also use when debugging CI gate failures, resolving lockfile conflicts, or uncertain what checks to run before opening a PR.
Expert guidance for writing Python code using the official Google GenAI SDK (google-genai) for Gemini API and Vertex AI. Use for text generation, multimodal inputs, reasoning, tools, and media generation.
Guides building Docker images and composing containers for Python/FastAPI applications. Triggered when users ask to "create a Dockerfile", "dockerize a Python app", "optimize Docker image", "create docker-compose", "set up multi-stage build", "reduce Docker image size", "create development container", or "configure Docker for FastAPI". Covers Docker, Dockerfile, container, image build, docker-compose, and containerization best practices for production and development workflows.
Generate Python FastAPI code following project design patterns. Use when creating models, schemas, repositories, services, controllers, database migrations, authentication, or tests. Enforces layered architecture, async patterns, OWASP security, and Alembic migration naming conventions (yyyymmdd_HHmm_feature).
Python FastAPI backend development with async patterns, SQLAlchemy, Pydantic, authentication, and production API patterns.
Python expert for stdlib, packaging, type hints, async/await, and performance optimization
testcontainers-python specialist. Covers all container modules (PostgreSQL, MySQL, MongoDB, Redis, Kafka, RabbitMQ, MinIO, Elasticsearch, LocalStack), GenericContainer, wait strategies, Docker Compose, networks, pytest fixtures, and CI/CD integration. USE WHEN: user mentions "testcontainers", "docker in tests", "real database in tests", "test with real postgres/redis/kafka", asks about container fixtures or Docker-based testing. DO NOT USE FOR: Spring Boot testcontainers (Java) - use `spring-boot-integration`; Mocking HTTP - use `fastapi-testing`; Pure pytest patterns - use `pytest`
Tinybird Python SDK for defining datasources, pipes, and queries in Python. Use when working with tinybird-sdk, Python Tinybird projects, or data ingestion and queries in Python.