Pythonコードの作成・レビューで、PEP 8や型ヒント、例外処理、パッケージ構成を整え、読みやすさと保守性、メモリ効率を考えた改善を支援するスキル。
- Pythonの可読性と記述規約のレビュー
- 型ヒントと例外処理を整えたいとき
- パッケージやモジュールの構成整理
2,715 件 ・ 関連度順
概要と使いどころ
Pythonコードの作成・レビューで、PEP 8や型ヒント、例外処理、パッケージ構成を整え、読みやすさと保守性、メモリ効率を考えた改善を支援するスキル。
PythonアプリをWindows向けに配布するため、Nuitkaでのコンパイル、不要ファイルやDLLの分析、Inno Setupでの軽量なインストーラー作成を支援します。
Write Python in n8n Code nodes (native Python, `language` pythonNative, n8n 2.x). Use when the user explicitly wants Python in a Code node, when migrating old Pyodide/"Python (Beta)" code that used _input/_json/_node/_now, or when a Python Code node fails with NameError, "Security violations detected", "Import of standard library module … is disallowed", "__build_class__ not found", "A 'json' property isn't a dictionary", or "Python runner unavailable". Covers the only two variables (_items/_item), dict-only access, imports blocked by default, the sandbox's denied builtins, accepted return shapes, and how errors interact with onError. JavaScript is the default for Code nodes — native Python has no n8n helpers and, by default, no imports. EXCEPTION — for Python in the AI-agent-callable Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode), use the n8n-code-tool skill instead (input is _query, return must be a string).
日本語の概要は準備中です。原文の説明を表示しています。
Provides AWS Lambda integration patterns for Python with cold start optimization. Use when deploying Python functions to AWS Lambda, choosing between AWS Chalice and raw Python approaches, optimizing cold starts, configuring API Gateway or ALB integration, or implementing serverless Python applications. Triggers include "create lambda python", "deploy python lambda", "chalice lambda aws", "python lambda cold start", "aws lambda python performance", "python serverless framework".
日本語の概要は準備中です。原文の説明を表示しています。
Application and library conventions for plain Python projects (no web framework): src/ package layout, CLI tooling (argparse/click/typer), configuration management (pydantic-settings), logging setup, module design, entry points, and packaging conventions. Activated automatically by python-plugin/stack.md as a convention skill for the development phase. Use this skill to: - Organise Python application code in a src/ layout with proper package structure. - Build CLI tools with argparse, click, or typer and register them as console scripts. - Manage configuration from environment variables using pydantic-settings. - Set up structured logging for production-grade applications. - Package a Python project correctly with pyproject.toml. Do NOT use this skill for: - Language idioms (type hints, dataclasses, enums, match/case) — see python-foundation:python-conventions. - Package manager commands (ruff, mypy, pip/poetry/uv) — see python-foundation:python-tooling. - Testing patterns — see python-foundation:pytest-testing. - Web framework patterns (Django/FastAPI/Flask) — see those framework plugin skills.
日本語の概要は準備中です。原文の説明を表示しています。
Pythonの実行を途中で止めて変数や処理の流れを調べ、例外発生時の状態や稼働中のプロセスも確認しながら、不具合の原因を追うスキル。
Pythonのテストをpytestで設計・作成し、共通の準備処理や外部サービスの代役、複数入力の検証、テストで確認したコードの範囲の測定まで扱うスキル。
Pythonの実行を途中で止め、変数や処理の流れを調べて不具合の原因を探ります。pdbとdebugpyを使い分け、失敗したテストや稼働中のプロセスも調査します。
Write Python code in n8n Code nodes. Use when writing Python in n8n, using _input/_json/_node syntax, working with standard library, or need to understand Python limitations in n8n Code nodes. Use this skill when the user specifically requests Python for an n8n Code node. Note — JavaScript is recommended for 95% of use cases — only use Python when the user explicitly prefers it or the task requires Python-specific standard library capabilities (regex, hashlib, statistics). EXCEPTION — for Python in the AI-agent-callable Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode), use the n8n-code-tool skill instead (input is _query, return must be a string).
日本語の概要は準備中です。原文の説明を表示しています。
Use this before writing Python code, creating Python scripts, modifying Python files, or when user asks to "write python", "create a python script", "implement in python". TRIGGER when starting any Python development task.
日本語の概要は準備中です。原文の説明を表示しています。
高速Python依存関係管理、仮想環境、モダンなPythonプロジェクトワークフローのためのuvパッケージマネージャーをマスター。Pythonプロジェクトのセットアップ、依存関係の管理、uvによるPython開発ワークフローの最適化時に使用。
PythonとNetmikoでネットワーク機器の情報収集を自動化し、接続数の制限、出力の解析、エラー処理、確認を伴う設定変更の実装やレビューを支援します。
APIやデータベース、ファイル処理をAIエージェントから使えるMCPサーバーにするスキル。Pythonでの作成、ローカル検証、クライアント登録、HTTP公開を支援します。
Call Python libraries from MATLAB using the py. interface, pyrun, pyrunfile, or pyenv. Use when writing or executing MATLAB code that calls Python functions or passes data between MATLAB and Python. REQUIRED when triaging Python errors from MATLAB (ModuleNotFoundError, ImportError, "Unable to resolve the name 'py.*'"). REQUIRED when setting up Python environments for MATLAB, creating virtual environments, or installing Python packages for use with MATLAB.
日本語の概要は準備中です。原文の説明を表示しています。
Write correct Python code with the official GREEN-API SDK whatsapp-api-client-python (package whatsapp_api_client_python). Use when sending/receiving WhatsApp messages, files, polls, groups, journals, queues, statuses, contacts, partner instances, polling notifications, or configuring a GREEN-API instance in Python. Triggers: GREEN-API, green-api, whatsapp-api-client-python, GreenAPI, GreenApi, sendMessage, receiveNotification.
日本語の概要は準備中です。原文の説明を表示しています。
Use when implementing a Python feature, adding CLI commands, writing pytest suites, reviewing Python code, debugging, or refactoring. The primary Python engineering workflow orchestrator — classifies the task and delegates through this plugin's own specialist agents (architect → implement → test → review), sized to the task. Delegates to python-cli-architect (implementation), python-pytest-architect (tests), code-reviewer (review), python-cli-design-spec (architecture). Triggers on any Python task requiring specialist agent coordination or multi-agent execution.
日本語の概要は準備中です。原文の説明を表示しています。
Modern Python idioms for any Python 3.10+ project: PEP 8 style, PEP 484/526 type hints, dataclasses, pathlib, enums, f-strings, structural pattern matching (match/case), context managers, exception handling, and null discipline. Stack-agnostic — referenced by every Python plugin in the marketplace. Use this skill to: - Write strongly-typed code with type hints on every function signature and class attribute. - Replace isinstance chains and magic constants with match/case and enums. - Use dataclasses or NamedTuple for value objects and data containers. - Handle resources safely with context managers and pathlib for all file paths. - Apply PEP 8 naming and structure conventions consistently. Do NOT use this skill for: - Framework-specific idioms (Django ORM, FastAPI routers, Flask blueprints — those live in framework plugin skills). - Packaging and dependency management — see python-foundation:python-tooling. - Testing patterns — see python-foundation:pytest-testing.
日本語の概要は準備中です。原文の説明を表示しています。
Python project tooling: pyproject.toml as the single source of truth, package managers (pip, Poetry, uv, pipenv), virtual environments, lockfiles, ruff (lint + format), mypy (type checking), and console scripts / entry points. Stack-agnostic — referenced by every Python plugin in the marketplace. Use this skill to: - Read pyproject.toml (or requirements.txt / Pipfile) to learn which package manager and Python version the project uses. - Install, add, and remove dependencies with the project's package manager. - Run ruff for formatting and linting, mypy for type checking. - Define console scripts and entry points for CLI applications. Do NOT use this skill for: - Language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing. - Framework-specific tooling (django management commands, flask CLI) — see framework plugin skills.
日本語の概要は準備中です。原文の説明を表示しています。
Guideline for designing, implementing, and verifying secure Python applications following OWASP Top 10 best practices. Use when the user wants to: (1) review Python code for security vulnerabilities, (2) design a secure Python application architecture, (3) implement security features (authentication, authorization, cryptography, input validation), (4) audit Python dependencies for known vulnerabilities, (5) create security checklists or verification plans, (6) fix security bugs or harden existing Python code, (7) set up security testing and static analysis (bandit, safety, semgrep), or (8) handle any Python security concern including injection prevention, secure deserialization, SSRF protection, secrets management, and secure deployment.
日本語の概要は準備中です。原文の説明を表示しています。
Creates Pulumi infrastructure-as-code projects in Python, defines cloud resources (AWS, Azure, GCP), configures ESC environments for secrets management, sets up OIDC authentication for secure deployments, and builds multi-language component resources. Use when creating Pulumi Python projects, writing infrastructure code, configuring cloud providers, managing secrets with Pulumi ESC, setting up OIDC for Pulumi, automating infrastructure deployments with Python, creating reusable Pulumi components in Python, or configuring Python toolchains (pip, poetry, uv) for Pulumi. Also use when the user mentions pyproject.toml with Pulumi, component_provider_host, or Python virtual environments for infrastructure code.
日本語の概要は準備中です。原文の説明を表示しています。
Write Estuary derivations in Python — async-generator transforms, Pydantic-typed source/output, optional persistent state, and dependency installation via uv. Use for ML/embeddings, async API calls, or any transform where SQL and TypeScript are awkward. Derivations add complexity and cost (and Python derivations require a private/BYOC data plane) — confirm the user wants a Python derivation before reaching for this. Use when user says "python derivation", "write a derivation in python", "embed with a python derivation", "ML derivation", "call an API from a derivation", or anything mentioning model2vec / huggingface / pydantic in a derivation context.
日本語の概要は準備中です。原文の説明を表示しています。
適切なプロジェクト構造、setup.py/pyproject.toml、PyPIへの公開を使用して配布可能なPythonパッケージを作成。Pythonライブラリのパッケージング、CLIツールの作成、Pythonコードの配布時に使用。
Set up an isolated Python environment for SageMaker / AWS work, with the right Python version and current boto3. Use this skill whenever Python code will be executed for a SageMaker deployment, training job, or any AWS automation — including when about to run `pip install`, when about to invoke `boto3`, when creating or activating a virtualenv, or when the user asks to "set up the environment". Never use system Python and never `pip install` into it. Always isolate. This skill prevents the most common failure modes: wrong Python version, dependency conflicts, and stale SDKs.
日本語の概要は準備中です。原文の説明を表示しています。
遺伝子情報や塩基・アミノ酸配列をggetで検索し、配列の類似性や遺伝子群の特徴を調べながら、結果と検索条件を再確認できる記録にまとめるスキル。