N8n Node Configuration Official logo

N8n Node Configuration Official

Organization
n8n-io
n8n-node-configuration-official

Use when configuring any n8n node: HTTP, webhooks, database, comms (Slack/Gmail/Discord), AI, triggers, Merge, anything. Triggers on any node-builder call (`node(...)`, `trigger(...)`, `tool(...)`, `memory(...)`, `languageModel(...)`, `ifElse(...)`, `merge(...)`, etc.), configuring a parameter, `useDataOfInput`, `numberOfInputs`, fan-in convergence, or any node-specific debugging.

Overview

Publishern8n-io
Repositoryskills
Skill namen8n-node-configuration-official
Stars
551
Forks
80
Bundled files
8
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by n8n-io on GitHub. Read the source before you install it.

Installation

Install the N8n Node Configuration Official AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/n8n-io/skills/tree/main/skills/n8n-node-configuration-official
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/n8n-io/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/n8n-node-configuration-official .claude/skills/n8n-node-configuration-official
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable N8n Node Configuration Official in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads N8n Node Configuration Official on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so N8n Node Configuration Official is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

n8n Node Configuration

Each n8n node has its own parameter shape, often with conditional fields (parameter X only matters when parameter Y has value Z). Shapes evolve between versions. Guessing produces cryptic validation errors.

Don't guess, use the get_node_types tool.

Non-negotiable

Call get_node_types with discriminators (resource, operation, mode) before configuring a node. Without discriminators you get the generic shape, missing operation-specific parameters and required fields. Build against the exact shape. Don't guess from memory.

The live get_node_types output is the canonical parameter shape. The references in this skill cover patterns, gotchas, security rules, and decision-making (when to use which operation, why credentials over text fields, engine retry caps, etc.) not parameter names or field structures. If a reference example conflicts with what get_node_types returns, trust the tool. Markdown drifts; the type def is generated from the live source.

Never guess resource-locator or load-options values. When get_node_types shows a param with @searchListMethod or @loadOptionsMethod (Slack channels, Sheets tabs/docs, DB tables/columns, model lists, labels), resolve the real value with explore_node_resources (pass a credentialId from list_credentials) and use a returned value. If you already know the exact ID, use it; if several match and intent is ambiguous, ask the user. An invented ID validates but points at nothing. Exception: toolWorkflow.workflowId has no search method, resolve it via search_workflows and use mode: 'id'.

Strong defaults

  • Configure operation-first. Set resource and operation first, and conditional parameters become visible. Most "field doesn't exist" errors are really "you haven't set the parent operation yet."
  • Don't carry parameters across operations. When changing operation, re-derive from the new shape. Stale parameters from the previous operation trip validation.

The flow for any new node

1. search_nodes(['<capability keyword>'])
   → returns matching node IDs + discriminators
2. Pick the right (resource, operation) for the task.
3. get_node_types([{ name: '...', resource: '...', operation: '...' }])
   → returns exact parameter shape including conditional fields
4. For any RLC / load-options param in that shape, ground the real value:
   explore_node_resources({ nodeType, version, methodName, methodType, credentialType, credentialId, currentNodeParameters? })
   → use a returned `value`. Don't invent IDs.
5. Build the node config from that shape.
6. validate_workflow → fix errors.
7. get_workflow_details → inspect the saved config; confirm parameters landed.
8. test_workflow with pinned data → confirm runtime behavior.

Skipping any step compounds the next. The most common skip is step 3, leading to "Cannot read property X" errors that are really "you didn't pass the discriminators."

validate_node_config as a side-channel

validate_node_config([{ type, typeVersion, parameters, isToolNode? }]) runs the same Zod schema as validate_workflow on isolated node configs. Schema-level only; doesn't replace validate_workflow (still the publish gate). Cleaner signal for:

  • Iterating on a single node mid-build. Faster than re-running validate_workflow per tweak.
  • Small edits to an existing workflow. Wiring unchanged? Check the one node you touched; full validate before publish.
  • Debugging a misconfigured node. Per-parameter errors with no graph noise.

For tool subnodes (wired via ai_tool), set isToolNode: true so the correct displayOptions branch evaluates.

Operation-aware configuration

Most nodes have a top-level shape like:

ts
{
  resource: '<thing being operated on>',   // 'message', 'spreadsheet', 'user', etc.
  operation: '<verb>',                      // 'send', 'append', 'lookup', etc.
  // ...operation-specific parameters
}

The (resource, operation) pair determines what other parameters exist (e.g., Slack (message, send) differs from (user, info)).

Pattern:

  1. Set resource and operation first.
  2. Re-fetch get_node_types with those discriminators if you didn't initially.
  3. Configure the rest from the operation-specific shape.

Property dependencies: the subtle trap

Some parameters depend on others in non-obvious ways:

  • A field is required only when another field has a specific value.
  • A field accepts different types depending on a mode.
  • A field's options come from another field's value.

Examples:

  • HTTP Request authentication: 'genericCredentialType' requires genericAuthType and credentials, but 'predefinedCredentialType' requires a different shape.
  • Postgres operation: 'executeQuery' requires query, while operation: 'select' requires table and columns.
  • Slack messageType: 'block' enables block-builder fields absent from messageType: 'text'.

Always inspect via get_node_types for the specific operation. Don't reuse a config from a different operation and expect it to validate.

Options-from-another-field is a @loadOptionsMethod: resolve the live options with explore_node_resources (methodType: 'loadOptions'), passing prior selections via currentNodeParameters when the method depends on them (e.g. listing a spreadsheet's tabs needs documentId).

Reference files

Per-category gotchas. Read the file for the node type you're configuring:

FileWhen to read
references/HTTP_NODES.mdConfiguring HTTP Request: auth, pagination, query/body parameters, retries
references/WEBHOOK_NODES.mdConfiguring Webhook trigger or Respond to Webhook: body parsing, response shape, async patterns
references/COMMS_NODES.mdSlack, Gmail, Discord, email: credential types, message shapes, attachments
references/DATABASE_NODES.mdPostgres, MySQL, Mongo, Supabase: query vs operation, parameter binding, error handling
references/AI_NODES.mdAI Agent node config knobs: streaming, vision, maxIterations, retries on the model sub-node. Defers design (prompts, tools, memory, structured output) to n8n-ai-nodes-official
references/TRIGGER_NODES.mdWebhook, Schedule, Manual, Execute Workflow Trigger: input schemas, polling vs realtime
references/SWITCH_FALLBACK.mdConfiguring a Switch node: unnamed outputs / missing fallback silently drop unmatched items
references/MERGE_NODE.mdConfiguring a Merge node, or you see useDataOfInput, numberOfInputs, or branches converging

Anti-patterns

Anti-patternWhat goes wrongFix
Building node config from memory of how the node looked last yearParameter shape has drifted, validation fails with cryptic errorsAlways get_node_types per session per node
Skipping discriminators in get_node_typesGet generic shape, miss operation-specific required fieldsAlways pass resource + operation (and mode where present)
Copying a node config from one operation to another and tweakingStale parameters trip validation, and conditional fields don't applyRe-derive from the new operation's shape
Hardcoding tokens / credentials in node text fieldsLeaks on export. See n8n-credentials-and-security-officialAlways credentials
Not testing the node with test_workflow after configuringRuntime errors only surface on real dataAlways test with pinned data before publish

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the N8n Node Configuration Official AI skill do?

Use when configuring any n8n node: HTTP, webhooks, database, comms (Slack/Gmail/Discord), AI, triggers, Merge, anything. Triggers on any node-builder call (`node(...)`, `trigger(...)`, `tool(...)`, `memory(...)`, `languageModel(...)`, `ifElse(...)`, `merge(...)`, etc.), configuring a parameter, `useDataOfInput`, `numberOfInputs`, fan-in convergence, or any node-specific debugging.

Why use N8n Node Configuration Official on TypingMind?

Because you install it once and use it with any model. N8n Node Configuration Official is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install N8n Node Configuration Official in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/n8n-io/skills/tree/main/skills/n8n-node-configuration-official. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use N8n Node Configuration Official?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with N8n Node Configuration Official?

As many as you like. As long as a model supports skills, you can use N8n Node Configuration Official with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the N8n Node Configuration Official AI skill free?

Yes. It is published on GitHub by n8n-io under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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