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n8n workflow development patterns, testing, validation, and best practices for building composable webhook workflows
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
| status | DEPRECATED |
| deprecated_in | 2026-01-20 |
| name | n8n-development |
| description | n8n workflow development patterns, testing, validation, and best practices for building composable webhook workflows |
| user-invocable | true |
This skill provides comprehensive guidance for developing, testing, and maintaining n8n webhook workflows integrated with Python services. It includes patterns for building composable workflows, template development, test-driven development practices, and complete development workflows.
Apply this skill when:
uv run pytestnathan/workflows/[category]/workflow_registry.yaml)tests/workflows/[category]/${VAR_NAME} syntax# Core development
uv sync # Install dependencies
uv run pytest # Run tests
uv run pytest --cov=nathan --cov-report=term-missing # With coverage
uvx ruff check . # Lint
uvx ruff format . # Format
# n8n development
docker compose -f docker-compose.n8n.yml up -d # Run n8n locally
uv run python -m nathan.scripts.n8n_workflow_registry --help # Registry CLI
uv run python -m nathan.templating --help # Template CLI
Test structure should mirror source in tests/ directory with descriptive naming (test_trigger_workflow_with_valid_parameters). Use pytest fixtures for shared setup and mock external dependencies. Target 80%+ test coverage.
Use Pydantic models for API requests/responses and SQLModel for database models. Implement input validation at boundaries (API endpoints, CLI arguments) with clear, actionable error messages.
Use httpx for all HTTP calls with proper timeout handling. Always use try/except for HTTP calls and async with context managers for HTTP clients. Use asyncio.gather() for parallel operations.
Load these reference files when needed for specific tasks:
references/common_patterns.md for workflow registry, template rendering, and error handling code examplesreferences/review_checklist.md before submitting code for reviewreferences/cli_commands.md for n8n command-line operations (export, import, execute workflows)references/rest_api.md for n8n REST API endpoints and Python client examplesreferences/workflow_json_structure.md for understanding and building n8n workflow JSON filesFollow conventional commits format:
feat: for new featuresfix: for bug fixesdocs: for documentation changestest: for test additions/changesrefactor: for code refactoringMake atomic commits (one logical change per commit), test before committing, and include documentation updates with code changes.
Systematic testing of code variations, edge cases, boundary conditions, and alternative implementations. This skill provides methodologies and tools for exhaustive testing including input permutation, code path analysis, mutation testing, and implementation alternatives. Use when ensuring code robustness through comprehensive test coverage or when exploring edge cases and boundary conditions.
Specialized skill for MLX-based LLM fine-tuning on Apple Silicon. This skill should be used when working with LoRA fine-tuning, model conversion from HuggingFace to MLX format, adapter management, hyperparameter tuning, memory optimization, and benchmarking on M1/M2/M3/M4 chips.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Use when starting complex tasks, multi-step projects, research tasks, or when the user mentions planning, organizing work, tracking progress, or wants structured output.
Use UV for Python dependency management. Use when setting up Python projects, creating Dockerfiles for Python apps, or managing dependencies & `pyproject.toml` files. UV provides deterministic resolution, speed, and reproducibility.