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Found 3 Skills
Production Python engineering patterns covering architecture, observability, testing, performance/concurrency, and core practices. Use when designing Python systems, implementing async/sync APIs, setting up monitoring, structuring tests, optimizing performance, or following Python best practices.
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when writing Python code, performing Python code reviews, working with Python tools (uv, ruff, mypy, pytest), or answering questions about Python best practices and patterns. Applies to CLI tools, AI agents (langgraph), and general Python development.
Apply repository-grounded senior engineering judgment to substantial Python work and bounded Python changes with production or cross-boundary risk. Do not use for trivial syntax questions, generic tutoring, or tasks with no Python artifact unless explicitly invoked. Use for writing, review, diagnosis, design, refactoring, or maintenance where correctness, state, effects, concurrency, compatibility, security, reuse, testing, or long-term ownership materially matters.