Agent skill

n8n Validation Expert

by czlonkowski in czlonkowski/n8n-skills

Interprets n8n validation output from validate_node and validate_workflow, separating real errors from false-positive warnings and guiding each fix.

MITAuto-check passedProductivity & Automation

Install n8n Validation Expert

skills CLI
$ npx skills add czlonkowski/n8n-skills --skill n8n-validation-expert -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install czlonkowski/n8n-skills n8n-validation-expert --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/czlonkowski/n8n-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/n8n-validation-expert .claude/skills/n8n-validation-expert && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
n8n-validation-expert
GitHub stars
6.4k
Token cost
~5.7k tokens
SKILL.md length
2,398 words
Files
5
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Interprets n8n validation output from validate_node and validate_workflow, separating real errors from false-positive warnings and guiding each fix.

  • Works in 3 steps: Errors (Must Fix) → Warnings (Should Fix) → Suggestions (Optional)
  • A validate_node or validate_workflow call returns errors or warnings
  • SKILL.md covers Validation Philosophy, Error Severity Levels, The Validation Loop and Validation Profiles, plus 8 more sections
  • Needs N8N_MCP_ACCESS_TOKEN

What it does

The skill treats validation as an iterative loop: configure a node, validate, read the feedback, fix and validate again, usually for a few rounds. It sorts feedback into errors that block activation (missing required fields, invalid values, type mismatches, bad node references, expression syntax errors), warnings that do not block (recommended-practice, deprecated, security and performance notes) and optional suggestions.

It also explains validation profiles, since some warnings only appear under the ai-friendly or strict profiles while deprecation and security warnings show under all of them. Companion files hold an error catalog, a list of known false positives and a review checklist, and the skill covers operator structure issues and auto-fix behavior.

When your agent uses it

  • A validate_node or validate_workflow call returns errors or warnings
  • Deciding whether a validation warning is a false positive
  • Understanding validation profiles and which warnings each one shows
  • Fixing operator structure issues flagged in a node configuration

Example prompts

  • “validate_workflow returned a missing_required error on my Slack node. Walk me through the fix.”
  • “Is this security warning about an unauthenticated webhook a real problem or a false positive?”
  • “Explain the difference between the ai-friendly and strict validation profiles.”

Requirements

  • Access to n8n validation tools such as validate_node and validate_workflow

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Errors (Must Fix)
  2. Warnings (Should Fix)
  3. Suggestions (Optional)

What it can do on your machine

Read from SKILL.md and the folder at commit 19cd793. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json and javascript).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • N8N_MCP_ACCESS_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

n8n Validation Expert loads about 5.7k tokens when it runs. Until then it costs about 130 tokens; SKILL.md has 2,398 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~130
When it runs · the whole SKILL.md, loaded when a task matches
~5.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from czlonkowski/n8n-skills at commit 19cd793, republished under its MIT licence (© czlonkowski). 2,398 words, ~5,707 tokens.

Download SKILL.mdSave it as .claude/skills/n8n-validation-expert/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
n8n-validation-expert
description
Interpret validation errors and guide fixing them. Use when encountering validation errors, validation warnings, false positives, operator structure issues, or need help understanding validation results. Also use when asking about validation profiles, error types, the validation loop process, or auto-fix capabilities. Consult this skill whenever a validate_node or validate_workflow call returns errors or warnings — it knows which warnings are false positives and which errors need real fixes.

n8n Validation Expert

Expert guide for interpreting and fixing n8n validation errors.


Validation Philosophy

Validate early, validate often

Validation is typically iterative:

  • Expect validation feedback loops
  • Usually 2-3 validate → fix cycles
  • Average: 23s thinking about errors, 58s fixing them

Key insight: Validation is an iterative process, not one-shot!


Error Severity Levels

1. Errors (Must Fix)

Blocks workflow execution - Must be resolved before activation

Types:

  • missing_required - Required field not provided
  • invalid_value - Value doesn't match allowed options
  • type_mismatch - Wrong data type (string instead of number)
  • invalid_reference - Referenced node doesn't exist
  • invalid_expression - Expression syntax error

Example:

json
{
  "type": "missing_required",
  "property": "channel",
  "message": "Channel name is required",
  "fix": "Provide a channel name (lowercase, no spaces, 1-80 characters)"
}
2. Warnings (Should Fix)

Doesn't block execution - Workflow can be activated but may have issues

Types:

  • best_practice - Recommended but not required — surfaces under ai-friendly / strict only
  • deprecated - Using old API/feature — surfaces under every profile
  • security - Hardcoded secrets, unauthenticated webhooks — surfaces under every profile
  • performance - Potential performance issue — advisory, ai-friendly / strict

Example (best-practice — appears under ai-friendly / strict):

json
{
  "type": "warning",
  "nodeName": "Slack",
  "message": "Slack API can have rate limits and transient failures"
}
3. Suggestions (Optional)

Nice to have - Improvements that could enhance workflow

Types:

  • optimization - Could be more efficient
  • alternative - Better way to achieve same result

The Validation Loop

Pattern from Telemetry

7,841 occurrences of this pattern:

1. Configure node
   ↓
2. validate_node (23 seconds thinking about errors)
   ↓
3. Read error messages carefully
   ↓
4. Fix errors
   ↓
5. validate_node again (58 seconds fixing)
   ↓
6. Repeat until valid (usually 2-3 iterations)
Example
javascript
// Iteration 1
let config = {
  resource: "channel",
  operation: "create"
};

const result1 = validate_node({
  nodeType: "nodes-base.slack",
  config,
  profile: "runtime"
});
// → Error: Missing "name"

// ⏱️  23 seconds thinking...

// Iteration 2
config.name = "general";

const result2 = validate_node({
  nodeType: "nodes-base.slack",
  config,
  profile: "runtime"
});
// → Error: Missing "text"

// ⏱️  58 seconds fixing...

// Iteration 3
config.text = "Hello!";

const result3 = validate_node({
  nodeType: "nodes-base.slack",
  config,
  profile: "runtime"
});
// → Valid! ✅

This is normal! Don't be discouraged by multiple iterations.


Validation Profiles

The four profiles are cumulative (n8n-mcp ≥ 2.63.0): each surfaces everything the lower one does, plus more. The dividing line is best-practice advisories — minimal and runtime withhold them; ai-friendly and strict add them. Errors are the same across every profile except that minimal skips a few config-level checks (e.g. enum validation of an explicit operation). Security and deprecation warnings surface under every profile.

minimal

Use when: Quick structural checks while wiring a workflow together.

Surfaces: hard errors that would stop execution (missing required fields, empty code, broken connections). Skips enum checks and all advisories.

Fastest and most permissive.

Use when: Ongoing validation as you build; the everyday profile.

Surfaces: errors (required fields, value types, allowed values, dependencies, broken references) plus security and deprecation warnings. No best-practice advisories.

Balanced — catches everything that breaks, stays quiet about style.

ai-friendly

Use when: You want the best-practice advice before deploying.

Surfaces: everything runtime does, plus best-practice advisories — per-node "without error handling" suggestions, "webhook should always send a response", rate-limit notes, outdated-typeVersion suggestions, cachedResultName and long-chain hints.

Note: ai-friendly is stricter than runtime, not looser. (Older docs described it as reducing false positives — that was true only while profile gating was broken; it is fixed now.)

strict

Use when: Hardening a production-critical workflow.

Surfaces: everything ai-friendly does, plus leftover-property checks ("property 'X' won't be used — not visible with current settings").

Maximum lint. With the false positives fixed at the source, its warnings are advice to weigh, not noise to fight.


Common Error Types

Five core error types, in rough order of frequency:

  • missing_required — a required field isn't provided. Use get_node to see required fields, then add it.
  • invalid_value — value doesn't match allowed options (enums are case-sensitive). Check the error's allowed list or get_node.
  • type_mismatch — wrong data type (string "100" vs number 100). Convert to the expected type.
  • invalid_expression — expression syntax error (missing {{}}, typos). See the n8n Expression Syntax skill.
  • invalid_reference — referenced node doesn't exist (renamed, deleted, or misspelled). Fix the name or cleanStaleConnections.

A sixth class, patchNodeField errors (find-not-found, ambiguous match, invalid/unsafe regex), surfaces when a patchNodeField op fails during n8n_update_partial_workflow — it's strict by design and errors rather than silently continuing.

Every type above has worked examples (broken config → fix) plus the patchNodeField error cases and their fixes in ERROR_CATALOG.md.


Auto-Sanitization System

Automatically normalizes common operator structures on ANY workflow update — n8n_create_workflow, n8n_update_partial_workflow, or any save. Trust it; don't hand-fix these.

What it normalizes on save:

  • Binary operators (equals, notEquals, contains, notContains, greaterThan, lessThan, startsWith, endsWith) — removes a stray singleValue property.
  • Unary operators (isEmpty, isNotEmpty, true, false) — adds singleValue: true.
  • IF/Switch metadata — fills in conditions.options for IF v2.2+ and Switch v3.2+.

Validation no longer errors on these shapes (n8n-mcp ≥ 2.63.0). n8n derives unary-ness from the operator name and defaults the conditions.options sub-fields, so validate_node / validate_workflow accept a condition whether or not singleValue and the options metadata are present — the sanitizer just tidies the canonical form on save. (Older servers wrongly errored on the un-normalized shape; if you see that, upgrade.) What still is a real error: a v1-shaped conditions object on a v2 node, an empty filter with no conditions, and legacy v1 operator names (e.g. smaller) inside a v2 structure.

What the sanitizer CANNOT fix (handle manually): broken connections to non-existent nodes (use cleanStaleConnections), branch-count mismatches (add/remove connections or rules), and paradoxical corrupt states (may need manual DB intervention).

Before/after examples and the full cannot-fix detail are in ERROR_CATALOG.md (Auto-Sanitization sections).


False Positives

The validator overhaul (n8n-mcp ≥ 2.63.0) removed the classic false positives — template literals inside expressions, optional chaining, omitted-operation defaults, the Webhook → Respond-to-Webhook pattern, IF/Filter legacy shapes, and more no longer fire.

Known exceptions (n8n-mcp 2.85.0, reported upstream; re-check after upgrading):

  • ERROR "Incorrect error output configuration… appear to be error handlers but are in main[0]" on a fan-out where one target is a Respond to Webhook or Send Email node, or has error / fail / catch / exception in its name. Moving Respond to Webhook onto main[1], as suggested, means the webhook only answers when the upstream node fails. Treat it as a false positive only when the message matches this text exactly and you've inspected connections and confirmed the named node sits on the success path by design. In that case keep the wiring, say in your reply that you're ignoring n8n-mcp#1111 and why, and don't run n8n_autofix_workflow with the default fix types (exclude error-output-config, or it may rewire the success path). Every other valid: false error still gets fixed. (n8n-mcp#1111)
  • Warning "Possible missing $ prefix" on json/items inside a string, e.g. $jmespath($('X').all(), "[?json.country=='PL'].json.name"). The json. prefix is required there, so ignore the warning. (#1115)
  • validate_node on a language: "pythonNative" Code node → "Code cannot be empty" (jsCode). The error is false; validate the workflow instead. (#1112)
  • Python "Return value must be a list of dicts" for a single-dict return in all-items mode. n8n accepts it and emits one item. (#1113)

Blind spots (valid workflow, wrong result at runtime): $jmespath syntax/quoting mistakes inside expressions (#1114); any JS error inside {{ }}, which resolves to null while the execution stays green (see n8n-expression-syntax); native-Python mistakes such as legacy _input/_json, dot access, blocked imports and classes (#1113, see n8n-code-python). Validation plus a successful run still isn't proof: inspect the output values.

What remains are best-practice advisories (surfaced only under ai-friendly / strict) that flag a real trade-off but may be acceptable in your case. Not every advisory needs a fix — many are context-dependent. Common ones and when each is acceptable vs. worth fixing:

  • "...without error handling" — OK for dev/testing and non-critical notifications; fix for production handling important data. (Never a hard error — style doesn't block execution.)
  • "No retry logic" — OK for idempotent ops, APIs with their own retry, manual triggers; fix for flaky external services and production automation.
  • "...rate limits and transient failures" — OK for internal/low-volume/server-side-limited APIs; fix for public, high-volume APIs.
  • "Unbounded query" — OK for small known datasets, aggregations, dev/testing; fix for production queries on large tables.

Security and deprecation warnings, by contrast, surface under every profile and should be treated as real.

Full per-case guidance, the list of what the validator no longer flags, profile strategies, the "should I fix this?" decision framework, and how to document accepted advisories are in FALSE_POSITIVES.md.


Validation Result Structure

Complete Response
javascript
{
  "valid": false,
  "errors": [
    {
      "type": "missing_required",
      "property": "channel",
      "message": "Channel name is required",
      "fix": "Provide a channel name (lowercase, no spaces)"
    }
  ],
  "warnings": [
    {
      "type": "best_practice",
      "property": "errorHandling",
      "message": "Slack API can have rate limits",
      "suggestion": "Add onError: 'continueRegularOutput'"
    }
  ],
  "suggestions": [
    {
      "type": "optimization",
      "message": "Consider using batch operations for multiple messages"
    }
  ],
  "summary": {
    "hasErrors": true,
    "errorCount": 1,
    "warningCount": 1,
    "suggestionCount": 1
  }
}
How to Read It
  1. Check valid first — true means the config is valid; false means there are errors to fix before deployment.
  2. Fix errors first — each carries a property, message, and fix. These must be resolved.
  3. Review warnings — each has a message and suggestion; decide per-case whether to address it (see False Positives above).
  4. Consider suggestions — optional improvements, not required.

Workflow Validation

validate_workflow (Structure)

Validates entire workflow, not just individual nodes

Checks:

  1. Node configurations - Each node valid
  2. Connections - No broken references
  3. Expressions - Syntax and references valid
  4. Flow - Logical workflow structure

Example:

javascript
validate_workflow({
  workflow: {
    nodes: [...],
    connections: {...}
  },
  options: {
    validateNodes: true,
    validateConnections: true,
    validateExpressions: true,
    profile: "runtime"
  }
})
Common Workflow Errors
1. Broken Connections
json
{
  "error": "Connection from 'Transform' to 'NonExistent' - target node not found"
}

Fix: Remove stale connection or create missing node

2. Cycles (warning, not an error)
json
{
  "warning": "Workflow contains a cycle: Node A → Node B → Node A"
}

A cycle is a warning, not a hard error (n8n-mcp ≥ 2.63.0) — runtime-controlled loops (error-retry, data-driven pagination, a router feeding back) execute to completion and are legitimate. Fix only if the loop is unintentional: ensure the cycle has a real exit (a conditional node, an error output, or a bounded counter) so it can't spin forever.

3. Multiple Start Nodes
json
{
  "warning": "Multiple trigger nodes found - only one will execute"
}

Fix: Remove extra triggers or split into separate workflows

4. Disconnected Nodes
json
{
  "warning": "Node 'Transform' is not connected to workflow flow"
}

Fix: Connect node or remove if unused


Recovery Strategies

Strategy 1: Start Fresh

When: Configuration is severely broken

Steps:

  1. Note required fields from get_node
  2. Create minimal valid configuration
  3. Add features incrementally
  4. Validate after each addition
Show full SKILL.md (953 more words)Show less

When: Workflow validates but executes incorrectly

Steps:

  1. Remove half the nodes
  2. Validate and test
  3. If works: problem is in removed nodes
  4. If fails: problem is in remaining nodes
  5. Repeat until problem isolated
Strategy 3: Clean Stale Connections

When: "Node not found" errors

Steps:

javascript
n8n_update_partial_workflow({
  id: "workflow-id",
  operations: [{
    type: "cleanStaleConnections"
  }]
})
Strategy 4: Use Auto-fix

When: Validation errors that can be automatically resolved

Steps:

javascript
// Preview fixes (default - doesn't apply)
n8n_autofix_workflow({
  id: "workflow-id",
  applyFixes: false,
  confidenceThreshold: "medium"  // high, medium, low
})

// Review fixes, then apply
n8n_autofix_workflow({
  id: "workflow-id",
  applyFixes: true
})

Auto-Fix Capabilities

The n8n_autofix_workflow tool can fix these issue types:

  1. expression-format - Missing = prefix in expressions (e.g., {{ $json.field }} → ={{ $json.field }})
  2. typeversion-correction - Downgrades nodes with unsupported typeVersions
  3. error-output-config - Removes conflicting onError settings
  4. node-type-correction - Fixes unknown node types using similarity matching (90%+ confidence)
  5. webhook-missing-path - Generates UUIDs for webhook nodes missing path configuration
  6. typeversion-upgrade - Smart upgrades to latest node versions with auto-migration
  7. version-migration - Guidance for complex breaking changes requiring manual steps

Confidence levels: high (90%+, safe to auto-apply), medium (70-89%, review recommended), low (<70%, manual review required)

javascript
// Preview all fixes
n8n_autofix_workflow({id: "workflow-id"})

// Only apply high-confidence fixes
n8n_autofix_workflow({
  id: "workflow-id",
  applyFixes: true,
  confidenceThreshold: "high"
})

// Target specific fix types
n8n_autofix_workflow({
  id: "workflow-id",
  fixTypes: ["expression-format", "typeversion-upgrade"],
  applyFixes: true
})

Post-update guidance: For version upgrades, check the postUpdateGuidance field in the response for step-by-step migration instructions.


Best Practices

✅ Do
  • Validate after every significant change
  • Read error messages completely
  • Fix errors iteratively (one at a time)
  • Use runtime profile for pre-deployment
  • Check valid field before assuming success
  • Trust auto-sanitization for operator issues
  • Use get_node when unclear about requirements
  • Document false positives you accept
❌ Don't
  • Skip validation before activation
  • Try to fix all errors at once
  • Ignore error messages
  • Use strict profile during development (too noisy)
  • Assume validation passed (always check result)
  • Manually fix auto-sanitization issues
  • Deploy with unresolved errors
  • Ignore all warnings (some are important!)

Running the workflow after it validates

validate_workflow checks structure, parameters and expressions — it never runs anything. A workflow that validates cleanly can still fail on real data, so run it once before calling it done.

With a webhook, form or chat trigger: n8n_test_workflow({workflowId}) — the default method: "auto" detects the trigger and fires it over HTTP (the workflow must be active).

Without such a trigger (Manual Trigger, Schedule, sub-workflow) there is no HTTP entry point. Use the pin-data path, which runs through n8n's own MCP server (N8N_MCP_ACCESS_TOKEN, n8n 2.34+):

  1. n8n_test_workflow({workflowId, method: "prepare"}) — lists the nodes that need pinned data.
  2. Build one sample item per listed node, keyed by node name, each item wrapped in {json: {...}}:
    json
    {"When clicking 'Test workflow'": [{"json": {"orderId": "1234", "email": "a@b.com"}}]}
    A flat object instead of an array of {json} items is the usual mistake here.
  3. n8n_test_workflow({workflowId, method: "pinned", pinData}) — runs it with that data and waits for the result.

For a quick manual run without pinned data, method: "direct" starts a manual execution and returns as soon as it has started; poll n8n_executions({action: "get", id: executionId, mode: "error"}) for the outcome. Nothing is pinned on a direct run, so every node executes and any external call it makes is real — and even pinned only pins trigger, credentialed and HTTP Request nodes. executionMode: "production" changes the execution context, not whether there are side effects; leave it at the default unless the user asked for a production run.

method: "auto" never runs a workflow through n8n's MCP server. On a workflow with no external trigger it reports that fact and names prepare/pinned/direct; the routed methods only run when you ask for them by name.

Consent before the first routed run. n8n refuses these calls for a workflow whose "Available in MCP" setting is off, which comes back as WORKFLOW_NOT_EXPOSED. Re-running with exposeToMcp: true turns that setting on and retries once. It is a visible, persistent setting on the workflow (and enabling it is a workflow update, so a concurrent UI edit can be overwritten) — ask the user before passing it. The consent flow only ever enables the setting; nothing disables it implicitly. Turning it off again is a deliberate act: n8n_update_partial_workflow({id: workflowId, operations: [{type: "updateSettings", settings: {availableInMCP: false}}]}), or the toggle in the n8n UI.

Reading the result: a run that started and then failed comes back as EXECUTION_FAILED with the executionId — inspect it with n8n_executions({action: "get", id, mode: "error"}) and fix from the node that threw, then validate and run again.


Reviewing an existing workflow

Validating as you build (the loop above) is for catching schema and shape errors in your own in-progress work. Reviewing an existing workflow — yours or one you've been handed — is a different job: the workflow already passes validate_workflow clean, and you're hunting for the issues validation doesn't see (silent connection bugs, injection-prone queries, dropped-item Switches, Set/Code antipatterns, missing error paths). For that, pull the workflow with n8n_get_workflow and walk REVIEW_CHECKLIST.md — a severity-tiered audit (MUST FIX / SHOULD FIX / NICE TO HAVE) where every item points to the canonical skill for the fix. Run n8n_audit_instance alongside it to surface hardcoded secrets and unauthenticated webhooks across the whole instance.


Detailed Guides

For comprehensive error catalogs, false positives, and workflow review:


Summary

Key Points:

  1. Validation is iterative (avg 2-3 cycles, 23s + 58s)
  2. Errors must be fixed, warnings are optional
  3. Auto-sanitization normalizes operator structures on save; validation no longer errors on the raw shape
  4. Use runtime profile by default; step up to ai-friendly/strict for best-practice advisories
  5. Classic false positives are fixed (≥ 2.63.0) — remaining warnings are advisories or security/deprecation notices, not validator mistakes
  6. Read error messages - they contain fix guidance

Validation Process:

  1. Validate → Read errors → Fix → Validate again
  2. Repeat until valid (usually 2-3 iterations)
  3. Review warnings and decide if acceptable
  4. Deploy with confidence

Related Skills & Tools:

  • n8n MCP Tools Expert - Use validation tools correctly
  • n8n Expression Syntax - Fix expression errors
  • n8n Node Configuration - Understand required fields
  • n8n_audit_instance - Proactive security validation (hardcoded secrets, unauthenticated webhooks, missing error handling, data retention)

© czlonkowski, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files in skills/n8n-validation-expert of czlonkowski/n8n-skills.

  • SKILL.md
  • ERROR_CATALOG.md
  • FALSE_POSITIVES.md
  • README.md
  • REVIEW_CHECKLIST.md

Open the folder on GitHubat commit 19cd793

Compare with similar skills

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  • n8n Code Node JavaScript

    czlonkowski/n8n-skills

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  • Native Python in n8n Code Nodes

    czlonkowski/n8n-skills

    Explains how to write native Python in n8n Code nodes, including the two input variables, blocked imports and fixes for common errors.

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  • n8n Custom Code Tool Guide

    czlonkowski/n8n-skills

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  • n8n Error Handling

    czlonkowski/n8n-skills

    Wires n8n workflows so failures are visible and recoverable: per-node error outputs, retries, error workflows and correct 4xx and 5xx webhook responses.

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  • n8n Multi-Instance Targeting

    czlonkowski/n8n-skills

    Keeps an n8n MCP session pointed at the right n8n instance, with rules for discovering, switching and verifying the target before credential writes and for recovering from misroutes.

    6.4k GitHub stars~3.2k tokensUpdated 23 days ago
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Works with

Questions about n8n Validation Expert

What does n8n Validation Expert do?

Interprets n8n validation output from validate_node and validate_workflow, separating real errors from false-positive warnings and guiding each fix. The skill treats validation as an iterative loop: configure a node, validate, read the feedback, fix and validate again, usually for a few rounds. It sorts feedback into errors that block activation (missing required fields, invalid values, type mismatches, bad node references, expression syntax errors), warnings that do not block (recommended-practice, deprecated, security and performance notes) and optional suggestions.

When should I use n8n Validation Expert?

n8n Validation Expert fits situations like: A validate_node or validate_workflow call returns errors or warnings; deciding whether a validation warning is a false positive; understanding validation profiles and which warnings each one shows; fixing operator structure issues flagged in a node configuration.

How do I install n8n Validation Expert in Claude Code?

Run `npx skills add czlonkowski/n8n-skills --skill n8n-validation-expert -a claude-code`. Or copy the skill folder (skills/n8n-validation-expert in czlonkowski/n8n-skills) into .claude/skills/n8n-validation-expert in your project. Claude Code loads it when a task matches its description.

How do I install n8n Validation Expert in Codex?

Run `npx skills add czlonkowski/n8n-skills --skill n8n-validation-expert -a codex`. Or copy the skill folder (skills/n8n-validation-expert in czlonkowski/n8n-skills) into .agents/skills/n8n-validation-expert in your project. Codex loads it when a task matches its description.

Can I use n8n Validation Expert in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add czlonkowski/n8n-skills --skill n8n-validation-expert -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/n8n-validation-expert, .gemini/skills/n8n-validation-expert, .github/skills/n8n-validation-expert and .opencode/skills/n8n-validation-expert in your project.

What does n8n Validation Expert need to run?

Going by SKILL.md and its folder, n8n Validation Expert needs credentials named N8N_MCP_ACCESS_TOKEN. Our summary lists: Access to n8n validation tools such as validate_node and validate_workflow.

Does n8n Validation Expert access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is n8n Validation Expert safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does n8n Validation Expert use?

n8n Validation Expert is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does n8n Validation Expert use?

About 5.7k tokens (SKILL.md is roughly 23k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to n8n Validation Expert?

Skills that share tags, products or a category with n8n Validation Expert: N8n Error Handling (sickn33/agentic-awesome-skills, 47k stars), Debugging Executions (n8n-io/n8n, 207k stars), N8n CLI (n8n-io/n8n, 207k stars) and N8n Docs Assistant (n8n-io/n8n, 207k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains n8n Validation Expert?

czlonkowski (a GitHub user) maintains it in czlonkowski/n8n-skills, which has 6,396 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on September 16, 2026.

Source: czlonkowski/n8n-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.