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Found 2,118 Skills
Search for available phone numbers by location and features, check coverage, and place orders. Use when acquiring new phone numbers. This skill provides Python SDK examples.
Modern Python asyncio, aiohttp, and concurrency patterns.
Review and verify Python code against PEP 8 using flake8, and optionally apply safe formatting fixes with black after explicit user confirmation. Use when users ask to check style compliance, lint Python files, or fix PEP 8 issues in a target folder.
This skill should be used when the user asks to "connect to MySQL with PyMySQL", "use PyMySQL in Python", "query a MySQL database with Python", "set up PyMySQL", or needs guidance on PyMySQL best practices, transactions, parameterized queries, or cursor types.
Automatically add or improve type annotations in legacy Python code. Use to improve code readability, IDE support, and catch type errors early.
Scaffold a minimal local LangChain agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.
Python 3.13+ development specialist covering FastAPI, Django, async patterns, data science, testing with pytest, and modern Python features. Use when developing Python APIs, web applications, data pipelines, or writing tests.
Use when designing error handling, retry policies, timeout behavior, or failure classification in Python. Also use when code swallows exceptions, loses error context across boundaries, has unbounded retries, silent failures, or lacks idempotency guarantees on retried writes.
Python logging with loguru and platformdirs. TRIGGERS - loguru, structured logging, JSONL logs, log rotation, XDG directories.
Generate copy-pastable ASCII banners with a built-in font (no external font deps), including compact fallback and optional ANSI 256 coloring for the logo.
MLflow experiment tracking via Python API. TRIGGERS - MLflow metrics, log backtest, experiment tracking, search runs.
Structured observability with Pydantic Logfire and OpenTelemetry. Use when: (1) Adding traces/logs to Python APIs, (2) Instrumenting FastAPI, HTTPX, SQLAlchemy, or LLMs, (3) Setting up service metadata, (4) Configuring sampling or scrubbing sensitive data, (5) Testing observability code.