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validate_workflow

Read-onlyIdempotent

Validates n8n workflow structure, connections, expressions, and AI tools. Returns errors, warnings, and fixes to ensure readiness before deployment.

Instructions

Full workflow validation: structure, connections, expressions, AI tools. Returns errors/warnings/fixes. Essential before deploy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflowYesThe complete workflow JSON to validate. Must include nodes array and connections object.
optionsNoOptional validation settings

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
validYes
summaryYes
errorsNo
warningsNo
suggestionsNo
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark the tool as read-only and idempotent. The description adds value by specifying the validation scope (including AI tools) and the return format (errors/warnings/fixes), without contradicting annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the key activity, and every word adds value. No unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity, high schema coverage, and presence of an output schema, the description adequately covers the main purpose and return format. It is sufficient for an AI agent to select and use this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema coverage is 100% with detailed parameter descriptions. The description adds no extra parameter semantics beyond what the schema provides, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool validates workflows, listing specific aspects (structure, connections, expressions, AI tools) and output (errors/warnings/fixes). It uses strong verbs and distinguishes from siblings by specifying scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'Essential before deploy', giving clear context for when to use. However, it does not explicitly mention when not to use or provide alternatives among sibling tools, missing some guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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