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n8n-validation-expert

Interpret validation errors and guide fixing them

Install / Use

npx skills add czlonkowski/n8n-skills --skill n8n-validation-expert

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

89/100

Category

Automation

Supported Platforms

Universal

Tags

Our assessment of n8n-validation-expert

n8n-validation-expert scores 89/100 on our quality scale, 743rd of 1,657 Automation skills we index (top 45%).

Its SKILL.md is 22 KB long, well organised into 40 sections with 13 code examples: a thorough specification that gives an agent plenty to work with.

With 6,309 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
8/15
Adoption
16/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 10 days ago, so n8n-validation-expert is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

n8n-validation-expert compared with similar skills

All 4 of these similar skills score higher than n8n-validation-expert; compare them before choosing.

SkillScoreStarsUpdatedFormat
n8n-validation-expert (this skill)by czlonkowski896.3k10d agoSKILL.md
Agent-Reachby Panniantong10085.6k11d agoCLAUDE.md
rufloby ruvnet10073.3ktodayCLAUDE.md
Scraplingby D4Vinci10083.9ktodayMCP Server
algorithmic-artby anthropics100177.9k4d agoSKILL.md

Frequently asked questions

How do I install n8n-validation-expert?
Run npx skills add czlonkowski/n8n-skills --skill n8n-validation-expert. The install tabs above show the steps for each supported agent.
Which AI agents does n8n-validation-expert work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is n8n-validation-expert safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is n8n-validation-expert still maintained?
The repository was last updated 10 days ago, so n8n-validation-expert is actively maintained.

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:

{
  "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):

{
  "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

// 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.

runtime (RECOMMENDED default)

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

{
  "valid": false,
  "errors": [
    {
      "type": "missing_required",
      "property": "channel",
      "message": "Channel name is required",
      "fix": "Provide a channel nam

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars6.3k
CategoryAutomation
Updated10d ago
Forks1.0k

Languages

Shell

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions