В каталоге 183 730 навыков в 14 категориях.
Modern Python standards (uv, Ruff, strict typing, Pydantic v2, Polars, async I/O). Use when writing or reviewing Python,...
Expert guidance for writing clean, maintainable Python 3.12+ code.
Validates that all imports follow fail-fast principle by detecting try/except ImportError patterns, conditional imports,...
Use this when wrapping a Python SDK client around an external dependency that can go down, adding a backstop to a retry...
Clean architecture patterns for Python services — service layer, repository pattern, domain models, dependency injection...
Perform comprehensive dead code and clean-up analysis in Python projects using static analysis, coverage, dependency che...
Remove dead code, fix PEP 8 violations, add type hints, consolidate duplicates, and modernize Python codebases. Use when...
Universal Python CLI development patterns and best practices
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CLI application patterns for Python. Triggers on: cli, command line, typer, click, argparse, terminal, rich, console, te...
Use when building or structuring Python CLI commands with Typer, including commands, options, and multi-command apps.
Use this when an SDK calls a server that publishes a rate limit, recovering from a 429-amplification incident, reviewing...
Use this when designing a new Python SDK client class, reviewing a __del__ method or non-idempotent close(), seeing aclo...
Use this when a Python SDK opens an HTTPS / TLS connection, reviewing code that touches ssl.SSLContext or sets check_hos...
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Make sure to ALWAYS use this skill when working with python code! Help designing, structuring, and maintaining Python pr...
Python coding conventions, tooling, and style guide. Auto-loads when writing or reviewing Python code.
Apply Google-style docstrings and inline comments to Python .py files. Use when documenting new functions/classes/module...
Python code style and type hinting patterns. Use when writing or reviewing Python code to ensure consistent, modern type...
Python code quality tooling with ruff and pyright. Use when setting up linting, formatting, type checking, configuring r...
Python code quality patterns including style, formatting, naming conventions, docstrings, type annotations, generics, pr...
Python code quality standards. Use when working with types, linting, type checking, exceptions, logging, or configuring...
Review Python code ensuring strict type safety with Python 3.12+ conventions. Use when reviewing Python code, writing ne...
审查 Python 代码，提供改进建议，确保代码质量和最佳实践
Python code style, linting, formatting, naming conventions, and documentation standards. Use when writing new code, revi...
Modern Python 3.12+ development with uv, ruff, pydantic, FastAPI, async patterns, and production-ready practices.
Implement and refactor production Python, FastAPI, Pydantic, async, and migrations.
Python coding standards following PEP 8, type hints, testing best practices, and modern Python patterns. Use for Python...
Use when designing or reviewing concurrent Python code — selecting between asyncio, threads, or multiprocessing; structu...
Python configuration management via environment variables and typed settings. Use when externalizing config, setting up...
Use this when a Python SDK uses aiohttp / httpx / asyncpg / redis / aiokafka, recovering from a pool-exhaustion incident...
Modern Python idioms for any Python 3.10+ project: PEP 8 style, PEP 484/526 type hints, dataclasses, pathlib, enums, f-s...
Team-specific Python conventions — credential management with dotenv, API client rules, LLM response parsing, TDD workfl...
Python code conventions covering type hints, Ruff formatting/linting, mypy/pyright, pytest, async I/O, uv packaging, and...
Work on Python experiments in packages/python_viterbo. Use for layout conventions, stage entrypoints, lint/test commands...
Comprehensive Python development expertise covering modern best practices, type hints, FastAPI web development, async/aw...
Python 3.12+ development with type hints, async patterns, virtual environments, testing, and modern tooling
Implement Python code with dataclasses, type hints, protocols, error handling, and async programming. Use when designing...
Use this when designing a client that authenticates to an external service, reviewing an api_key: str field on a Config,...
编写用于数据清洗、分析和可视化的 Python 脚本 (Pandas/Matplotlib)
Use when Python data modeling with dataclasses, attrs, and Pydantic. Use when creating data structures and models.
Comprehensive Python data engineering patterns for AWS Data Lake, including PySpark, Pandas, Apache Airflow, AWS Glue, E...
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigoro...
Use when designing data ownership, validation boundaries, consistency models, or configuration strategy in Python. Also...
Professional data visualization using Python (matplotlib, seaborn, plotly). Create publication-quality static charts, st...
Use when you need to inspect detailed execution flow of a Python program, stepping through functions and inspecting vari...
Debug Python code using tracebacks, pdb, and structured logging.
Debug Python errors, exceptions, and unexpected behavior. Analyzes tracebacks, reproduces issues, identifies root causes...
Python debugging methodology and problem-solving framework. Use when investigating exceptions, async issues, logging pro...
Master debugger for Python code with expertise in common errors, performance issues, and debugging tools
Debug Python: pdb REPL + debugpy remote (DAP).
Debug Python with pdb, breakpoint(), post-mortem inspection, and debugpy remote attach.
Use this when adding a new entry to pyproject.toml dependencies, bumping a major version of an existing dep, reviewing T...
Use when designing module boundaries, planning refactors, or reviewing architecture in Python codebases. Also use when f...
Python design patterns including KISS, Separation of Concerns, Single Responsibility, and composition over inheritance....
This skill should be used when the user asks about "design patterns", "SOLID principles", "factory pattern", "strategy p...
Python development. Use when writing Python code, CLI tools, scripts, or services. Emphasizes stdlib, type hints, pytest...
Python 开发规范，包含 PEP 8 风格、类型注解、异常处理、测试规范等
World-class
Opinionated Python development setup with uv, ty, ruff, pytest, lefthook, and just. Use when creating a new Python proje...
Python conventions, patterns, and workflows. Use when writing code, reviewing PRs, or setting up new Python projects.
Python development guidelines for modern Python projects. Use when creating Python modules, classes, functions, scripts,...
當要開發或修改 Python 程式碼時使用。
Python development best practices for modern Python projects. Activated when working with Python files, pyproject.toml,...
Spawn a Python development team for feature implementation in src/mde/. Use for features spanning multiple modules, requ...
Эксперт Python разработки. Используй для Python best practices, async, typing и ecosystem.
Build, review, debug, and maintain production Python applications, services, libraries, CLIs, and automation. Use for Py...
Python development patterns for gh-pr-linear-issue-linker. Use when writing Python code, implementing features, fixing b...
Modern Python development with Python 3.12+, Django, FastAPI, async patterns,
Professional Python development skill covering modern Python 3.10+, FastAPI, Django, Flask, async programming, data proc...
You are a Python project architecture expert specializing in scaffolding production-ready Python applications. Generate...
This skill should be used when the user asks about "Python code style", "type hints", "structlog logging", "how to log",...
Django architecture, ORM select_related/prefetch_related optimization, middleware, and signals discipline.
Django development with REST framework, ORM optimization, async views, and production deployment
Python documentation conventions — a Google-style docstring on every public module, class, and function, enforced by ruf...
Use this when authoring an Examples block in a public Python SDK docstring, reviewing a docstring that lacks runnable ex...
Programmatically read, modify, and create Word documents (.docx) with python-docx library
Create and manipulate Microsoft Word documents programmatically. Build reports, contracts, and documentation with full c...
将既有或新编写的 Python 脚本重构为双模式模块，用于稳定、可维护的数据处理流。
Use when writing Python code for DSGE models, HANK models, numerical economic computation, causal inference, or quantita...
Modern Python development patterns - uv, ruff, mypy, pyproject.toml, packaging, and Python 3.11+ features. Auto-triggers...
Review how Python repositories use important ecosystem libraries and integration boundaries, automatically discovering c...
Handle noisy git diffs from src/*.egg-info generated by editable installs (uv) and decide whether to commit or ignore.
Python FastAPI LLM 추론 엔드포인트를 프로젝트 패턴에 맞게 생성하는 스킬. "/python-endpoint"를 입력하거나, "파이썬 엔드포인트 추가", "LLM 추론 API 만들어줘", "FastAPI...
Writes, reviews, and refactors Python code following modern best practices. Specialises in Python 3.12+, uv for project...
Read outputlanguage from .ai/context/workflow-config.md. Write ALL deliverables and code comments in that language. If t...
Comprehensive Python engineering guidelines for writing production-quality Python code. This skill should be used when w...
Write production Python — typing, packaging, pytest discipline, stdlib-first, honest error handling.
USE WHEN you need to create, activate, or manage Python virtual environments (venv/virtualenv); install dependencies in...
Guidelines and requirements for the Python environment setup, running tests (pytest), path normalization, and MCP/stdio...
Gestión de entornos Python — venv, pip, poetry, conda. Entornos reproducibles y dependencias sin conflictos. Trigger: Cu...
Python environment setup with uv, shared utilities, and script structure guidelines.
Use when you have cloned a scientific repository containing Python code (scripts, Jupyter notebooks, or module imports)...
Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when...
Use when designing error handling, retry policies, timeout behavior, or failure classification in Python. Also use when...
Use this when designing the errors module of a new Python SDK, reviewing code that raises bare Exception / RuntimeError...