
N8n Validation Expert
Decode n8n validate_node and validate_workflow results so your agent fixes real errors and ignores known false positives before you activate automations.
Overview
n8n-validation-expert is an agent skill most often used in Build integrations (also Ship testing) that interprets n8n validation errors and guides fixes after validate_node or validate_workflow calls.
Install
npx skills add https://github.com/czlonkowski/n8n-skills --skill n8n-validation-expertWhat is this skill?
- Maps error severities: must-fix errors vs ignorable warnings and false positives
- Covers missing_required, invalid_value, type_mismatch, invalid_reference, and invalid_expression types
- Documents iterative validation loop—typically 2–3 validate-and-fix cycles
- Guidance on validation profiles and operator structure issues
- Explicit trigger: consult after every validate_node or validate_workflow call with errors or warnings
- Typical 2–3 validate → fix cycles
- Five enumerated must-fix error types in the severity guide
Adoption & trust: 3.8k installs on skills.sh; 5.3k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
Your agent sees a wall of n8n validation JSON and cannot tell which issues block activation versus which are false positives.
Who is it for?
Builders using agent-driven n8n workflow authoring who hit validation errors, warnings, or operator structure issues regularly.
Skip if: Greenfield workflow design with zero validation tooling, or teams not using n8n’s validate APIs at all.
When should I use this skill?
Encountering validation errors, validation warnings, false positives, operator structure issues, or when asking about validation profiles, error types, the validation loop, or auto-fix capabilities after validate_node or
What do I get? / Deliverables
Workflows reach activatable state faster with prioritized fixes across a short validate → fix loop instead of blind retries.
- Prioritized fix list aligned to n8n error severities
- Activation-ready workflow after iterative validation
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Workflow JSON is authored during Build integrations; validation is the gate before those automations run in production. Integrations subphase is where n8n nodes are wired; this skill is the interpreter for the platform’s validation API feedback.
Where it fits
After an agent adds a Slack node, validation reports missing_required on channel—skill routes a precise field fix.
Distinguish invalid_expression in an IF node from a benign warning before merging the workflow PR.
Pre-activation pass ensures no blocking error types remain in the exported workflow JSON.
How it compares
An interpretation layer on top of n8n validators—not a workflow generator or hosting MCP by itself.
Common Questions / FAQ
Who is n8n-validation-expert for?
Solo builders and indie operators using AI agents to create or patch n8n workflows who need reliable reads on validation output.
When should I use n8n-validation-expert?
In Build while wiring integrations whenever validation returns errors or warnings, and in Ship while testing workflows before activation or production cutover.
Is n8n-validation-expert safe to install?
It is procedural guidance only; review the Security Audits panel on this Prism page and treat any suggested auto-fix steps as code you must verify.
SKILL.md
READMESKILL.md - N8n Validation Expert
# 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 - `deprecated` - Using old API/feature - `performance` - Potential performance issue **Example**: ```json { "type": "best_practice", "property": "errorHandling", "message": "Slack API can have rate limits", "suggestion": "Add onError: 'continueRegularOutput' with retryOnFail" } ``` ### 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 Choose the right profile for your stage: ### minimal **Use when**: Quick checks during editing **Validates**: - Only required fields - Basic structure **Pros**: Fastest, most permissive **Cons**: May miss issues ### runtime (RECOMMENDED) **Use when**: Pre-deployment validation **Validates**: - Required fields - Value types - Allowed values - Basic dependencies **Pros**: Balanced, catches real errors **Cons**: Some edge cases missed **This is the recommended profile for most use cases** ### ai-friendly **Use when**: AI-generated configurations **Validates**: - Same as runtime - Reduces false positives - More tolerant of minor issues **Pros**: Less noisy for AI workflows **Cons**: May allow some questionable configs ### strict **Use