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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).

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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".

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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.

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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。

• 失敗するPythonテストの変数確認
• 予想外の状態変化を追いたいとき
• 例外発生時の状態を調べたいとき

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).

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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。

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.

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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.

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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.

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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.

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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.

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Implement or modify Python SDK behavior under python/composio, including tools, toolkits, sessions, auth configs, connected accounts, client integration, and shared Python models. Use for Python core runtime/API work; pair with python-testing and cross-sdk-parity when TypeScript must match.

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。

Installs the CARLA Python client (the `carla` package) into a chosen interpreter so the other python-api skills work — from a wheel bundled with your release or checkout, from PyPI (`pip install carla==X.Y.Z`), or by putting an older release's .egg on PYTHONPATH. Detects what is already present, picks the source that matches your simulator's version, pins numpy<2, and verifies `import carla` plus the client/server version match. Use when the user asks to "install the CARLA Python API", "pip install carla", "set up the carla python package", or when a skill reports "cannot import carla".

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。

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。

Audit a Python project's installed dependencies for known CVEs by wrapping pip-audit (PyPA's official vulnerability auditor) and emitting findings in the canonical penetration-tester schema. Detects vulnerable direct AND transitive packages, normalizes pip-audit's severity output via OSV severity bands, falls back to pip list --outdated when pip-audit isn't installed, and supports requirements.txt, pyproject.toml (PEP 621), Pipfile.lock, and poetry.lock as input sources. Use when: pre-merge gate on a Python project, post-incident sweep after a PyPI compromise (e.g. ctx, request-toolbelt typosquats, ultralytics 8.3.42 compromise), SOC2 evidence collection, or inheriting an unfamiliar Python codebase. Threshold: any HIGH or CRITICAL CVE in the resolved dependency tree. MODERATE / LOW reported informationally. Trigger with: "audit python deps", "pip vulnerability scan", "check pypi packages for CVEs", "pip-audit run".

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Python visual creation and matplotlib/seaborn patterns for PBIR reports. Automatically invoke when the user mentions "Python visual", "matplotlib in Power BI", "seaborn in Power BI", "pythonVisual", or asks to "create a Python visual", "add a matplotlib chart", "write a Python visual script".

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Python backend for Databricks Apps — FastAPI (default), Flask, Dash, Streamlit, Gradio, Reflex. **Default for a new Databricks App is `databricks-apps` (AppKit — Node/TypeScript/React) — reach for it first.** Use this skill only when the user asks for a Python backend, extends an existing Python app, or the team is Python-only. Covers OAuth auth, app resources, SQL warehouse and Lakebase connectivity, foundation-model / Vector Search / model-serving APIs (via `databricks-python-sdk`), and deployment via CLI or DABs.

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Translate Python programs into equivalent Dafny code, preserving program semantics and ensuring the generated code is well-typed, executable, and verifiable. Use when the user asks to convert Python code to Dafny, port Python programs to Dafny, add formal verification to Python code, or create Dafny versions of Python algorithms with specifications.

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。