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Agent Skill · 研究检索

n8n-workflow-patterns(n8n 工作流程模式)

n8n-workflow-patterns 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

n8n-workflow-patterns 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 38,973。

总安装 1,483周安装 60GitHub Stars 35,715下载 466核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:n8n-workflow-patterns(n8n 工作流程模式)
来源仓库:https://github.com/sickn33/antigravity-awesome-skills
仓库路径:skills/n8n-workflow-patterns
安装命令:
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill n8n-workflow-patterns
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill n8n-workflow-patterns

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

n8n-workflow-patterns 提供五种核心模式覆盖 90% 以上用例,以 Webhook 处理最常见。适用于规划模式、选择节点、构建验证到部署的全流程指导。使用清单确保结构完整,集成其他技能实现端到端开发。建议先确定用例模式,再查阅详细文档并调用相关工具辅助实现。

需确认宿主环境是否支持外部 API 调用及工作流执行权限。

来源仓库内路径:skills/n8n-workflow-patterns

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill n8n…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

n8n-workflow-patterns 怎么安装?

在终端执行 npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill n8n-workflow-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

n8n-workflow-patterns 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

n8n-workflow-patterns 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

n8n-workflow-patterns 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

n8n-workflow-patterns 用的人多吗?

公开数据是累计安装 1,483 次,近一周安装 60 次,下载 466 次,GitHub 35,715 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

n8n-workflow-patterns 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 35,715 星,维护活跃度相对可查。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
n8n-workflow-patterns

n8n 工作流程模式 · 本页

1,48335,715调用外部服务未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

n8n Workflow Patterns

Proven architectural patterns for building n8n workflows.

When to Use

  • You need to choose an architectural pattern for an n8n workflow before building it.
  • The task involves webhook processing, API integration, scheduled jobs, database sync, or AI-agent workflow design.
  • You want a high-level workflow structure rather than node-by-node troubleshooting.

The 5 Core Patterns

Based on analysis of real workflow usage:

  1. Webhook Processing (Most Common)

- Receive HTTP requests → Process → Output - Pattern: Webhook → Validate → Transform → Respond/Notify

  1. [HTTP API Integration]

- Fetch from REST APIs → Transform → Store/Use - Pattern: Trigger → HTTP Request → Transform → Action → Error Handler

  1. Database Operations

- Read/Write/Sync database data - Pattern: Schedule → Query → Transform → Write → Verify

  1. AI Agent Workflow

- AI agents with tools and memory - Pattern: Trigger → AI Agent (Model + Tools + Memory) → Output

  1. Scheduled Tasks

- Recurring automation workflows - Pattern: Schedule → Fetch → Process → Deliver → Log


Pattern Selection Guide

When to use each pattern:

Webhook Processing - Use when:

  • Receiving data from external systems
  • Building integrations (Slack commands, form submissions, GitHub webhooks)
  • Need instant response to events
  • Example: "Receive Stripe payment webhook → Update database → Send confirmation"

HTTP API Integration - Use when:

  • Fetching data from external APIs
  • Synchronizing with third-party services
  • Building data pipelines
  • Example: "Fetch GitHub issues → Transform → Create Jira tickets"

Database Operations - Use when:

  • Syncing between databases
  • Running database queries on schedule
  • ETL workflows
  • Example: "Read Postgres records → Transform → Write to MySQL"

AI Agent Workflow - Use when:

  • Building conversational AI
  • Need AI with tool access
  • Multi-step reasoning tasks
  • Example: "Chat with AI that can search docs, query database, send emails"

Scheduled Tasks - Use when:

  • Recurring reports or summaries
  • Periodic data fetching
  • Maintenance tasks
  • Example: "Daily: Fetch analytics → Generate report → Email team"

Common Workflow Components

All patterns share these building blocks:

1. Triggers

  • Webhook - HTTP endpoint (instant)
  • Schedule - Cron-based timing (periodic)
  • Manual - Click to execute (testing)
  • Polling - Check for changes (intervals)

2. Data Sources

  • HTTP Request - REST APIs
  • Database nodes - Postgres, MySQL, MongoDB
  • Service nodes - Slack, Google Sheets, etc.
  • Code - Custom JavaScript/Python

3. Transformation

  • Set - Map/transform fields
  • Code - Complex logic
  • IF/Switch - Conditional routing
  • Merge - Combine data streams

4. Outputs

  • HTTP Request - Call APIs
  • Database - Write data
  • Communication - Email, Slack, Discord
  • Storage - Files, cloud storage

5. Error Handling

  • Error Trigger - Catch workflow errors
  • IF - Check for error conditions
  • Stop and Error - Explicit failure
  • Continue On Fail - Per-node setting

Workflow Creation Checklist

When building ANY workflow, follow this checklist:

Planning Phase

  • Identify the pattern (webhook, API, database, AI, scheduled)
  • List required nodes (use search_nodes)
  • Understand data flow (input → transform → output)
  • Plan error handling strategy

Implementation Phase

  • Create workflow with appropriate trigger
  • Add data source nodes
  • Configure authentication/credentials
  • Add transformation nodes (Set, Code, IF)
  • Add output/action nodes
  • Configure error handling

Validation Phase

  • Validate each node configuration (validate_node)
  • Validate complete workflow (validate_workflow)
  • Test with sample data
  • Handle edge cases (empty data, errors)

Deployment Phase

  • Review workflow settings (execution order, timeout, error handling)
  • Activate workflow using activateWorkflow operation
  • Monitor first executions
  • Document workflow purpose and data flow

Data Flow Patterns

Linear Flow

Trigger → Transform → Action → End

Use when: Simple workflows with single path

Branching Flow

Trigger → IF → [True Path]
             └→ [False Path]

Use when: Different actions based on conditions

Parallel Processing

Trigger → [Branch 1] → Merge
       └→ [Branch 2] ↗

Use when: Independent operations that can run simultaneously

Loop Pattern

Trigger → Split in Batches → Process → Loop (until done)

Use when: Processing large datasets in chunks

Error Handler Pattern

Main Flow → [Success Path]
         └→ [Error Trigger → Error Handler]

Use when: Need separate error handling workflow


Common Gotchas

1. Webhook Data Structure

Problem: Can't access webhook payload data

Solution: Data is nested under $json.body

❌ {{$json.email}}
✅ {{$json.body.email}}

See: n8n Expression Syntax skill

2. Multiple Input Items

Problem: Node processes all input items, but I only want one

Solution: Use "Execute Once" mode or process first item only

{{$json[0].field}}  // First item only

3. Authentication Issues

Problem: API calls failing with 401/403

Solution:

  • Configure credentials properly
  • Use the "Credentials" section, not parameters
  • Test credentials before workflow activation

4. Node Execution Order

Problem: Nodes executing in unexpected order

Solution: Check workflow settings → Execution Order

  • v0: Top-to-bottom (legacy)
  • v1: Connection-based (recommended)

5. Expression Errors

Problem: Expressions showing as literal text

Solution: Use {{}} around expressions

  • See n8n Expression Syntax skill for details

Integration with Other Skills

These skills work together with Workflow Patterns:

n8n MCP Tools Expert - Use to:

  • Find nodes for your pattern (search_nodes)
  • Understand node operations (get_node)
  • Create workflows (n8n_create_workflow)
  • Deploy templates (n8n_deploy_template)
  • Use ai_agents_guide for AI pattern guidance

n8n Expression Syntax - Use to:

  • Write expressions in transformation nodes
  • Access webhook data correctly ({{$json.body.field}})
  • Reference previous nodes ({{$node["Node Name"].json.field}})

n8n Node Configuration - Use to:

  • Configure specific operations for pattern nodes
  • Understand node-specific requirements

n8n Validation Expert - Use to:

  • Validate workflow structure
  • Fix validation errors
  • Ensure workflow correctness before deployment

Pattern Statistics

Common workflow patterns:

Most Common Triggers:

  1. Webhook - 35%
  2. Schedule (periodic tasks) - 28%
  3. Manual (testing/admin) - 22%
  4. Service triggers (Slack, email, etc.) - 15%

Most Common Transformations:

  1. Set (field mapping) - 68%
  2. Code (custom logic) - 42%
  3. IF (conditional routing) - 38%
  4. Switch (multi-condition) - 18%

Most Common Outputs:

  1. HTTP Request (APIs) - 45%
  2. Slack - 32%
  3. Database writes - 28%
  4. Email - 24%

Average Workflow Complexity:

  • Simple (3-5 nodes): 42%
  • Medium (6-10 nodes): 38%
  • Complex (11+ nodes): 20%

Quick Start Examples

Example 1: Simple Webhook → Slack

1. Webhook (path: "form-submit", POST)
2. Set (map form fields)
3. Slack (post message to #notifications)

Example 2: Scheduled Report

1. Schedule (daily at 9 AM)
2. HTTP Request (fetch analytics)
3. Code (aggregate data)
4. Email (send formatted report)
5. Error Trigger → Slack (notify on failure)

Example 3: Database Sync

1. Schedule (every 15 minutes)
2. Postgres (query new records)
3. IF (check if records exist)
4. MySQL (insert records)
5. Postgres (update sync timestamp)

Example 4: AI Assistant

1. Webhook (receive chat message)
2. AI Agent
   ├─ OpenAI Chat Model (ai_languageModel)
   ├─ HTTP Request Tool (ai_tool)
   ├─ Database Tool (ai_tool)
   └─ Window Buffer Memory (ai_memory)
3. Webhook Response (send AI reply)

Example 5: API Integration

1. Manual Trigger (for testing)
2. HTTP Request (GET /api/users)
3. Split In Batches (process 100 at a time)
4. Set (transform user data)
5. Postgres (upsert users)
6. Loop (back to step 3 until done)

Detailed Pattern Files

For comprehensive guidance on each pattern:

  • webhook_processing.md - Webhook patterns, data structure, response handling
  • http_api_integration - REST APIs, authentication, pagination, retries
  • database_operations.md - Queries, sync, transactions, batch processing
  • ai_agent_workflow.md - AI agents, tools, memory, langchain nodes
  • scheduled_tasks.md - Cron schedules, reports, maintenance tasks

Real Template Examples

From n8n template library:

Template #2947: Weather to Slack

  • Pattern: Scheduled Task
  • Nodes: Schedule → HTTP Request (weather API) → Set → Slack
  • Complexity: Simple (4 nodes)

Webhook Processing: Most common pattern

  • Most common: Form submissions, payment webhooks, chat integrations

HTTP API: Common pattern

  • Most common: Data fetching, third-party integrations

Database Operations: Common pattern

  • Most common: ETL, data sync, backup workflows

AI Agents: Growing in usage

  • Most common: Chatbots, content generation, data analysis

Use search_templates and get_template from n8n-mcp tools to find examples!


Best Practices

✅ Do

  • Start with the simplest pattern that solves your problem
  • Plan your workflow structure before building
  • Use error handling on all workflows
  • Test with sample data before activation
  • Follow the workflow creation checklist
  • Use descriptive node names
  • Document complex workflows (notes field)
  • Monitor workflow executions after deployment

❌ Don't

  • Build workflows in one shot (iterate! avg 56s between edits)
  • Skip validation before activation
  • Ignore error scenarios
  • Use complex patterns when simple ones suffice
  • Hardcode credentials in parameters
  • Forget to handle empty data cases
  • Mix multiple patterns without clear boundaries
  • Deploy without testing

Summary

Key Points:

  1. 5 core patterns cover 90%+ of workflow use cases
  2. Webhook processing is the most common pattern
  3. Use the workflow creation checklist for every workflow
  4. Plan pattern → Select nodes → Build → Validate → Deploy
  5. Integrate with other skills for complete workflow development

Next Steps:

  1. Identify your use case pattern
  2. Read the detailed pattern file
  3. Use n8n MCP Tools Expert to find nodes
  4. Follow the workflow creation checklist
  5. Use n8n Validation Expert to validate

Related Skills:

  • n8n MCP Tools Expert - Find and configure nodes
  • n8n Expression Syntax - Write expressions correctly
  • n8n Validation Expert - Validate and fix errors
  • n8n Node Configuration - Configure specific operations

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

平台分布

Codex

35.2%
按下载量换算164

Claude

31.02%
按下载量换算145

Cursor

17.03%
按下载量换算79

Gemini CLI

9.68%
按下载量换算45

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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