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validate_node

Read-onlyIdempotent

Validate n8n node configurations to identify errors, warnings, and suggestions. Use full mode for comprehensive validation or minimal mode for quick required-field checks.

Instructions

Validate n8n node configuration. Use mode='full' for comprehensive validation with errors/warnings/suggestions, mode='minimal' for quick required fields check. Example: nodeType="nodes-base.slack", config={resource:"channel",operation:"create"}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoValidation mode. full=comprehensive validation with errors/warnings/suggestions, minimal=quick required fields check only. Default is "full"full
configYesConfiguration as object. For simple nodes use {}. For complex nodes include fields like {resource:"channel",operation:"create"}
profileNoProfile for mode=full: "minimal", "runtime", "ai-friendly", or "strict". Default is "ai-friendly"ai-friendly
nodeTypeYesNode type as string. Example: "nodes-base.slack"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
validYes
errorsNo
summaryNo
nodeTypeYes
warningsNo
displayNameYes
suggestionsNo
workflowNodeTypeNo
missingRequiredFieldsNoOnly present in mode=minimal
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so safety is clear. The description adds behavioral context by explaining the modes and profiles, and includes an example. No contradictions. It could mention that it doesn't modify state, but annotations already cover that.

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?

Two sentences and an example. First sentence states purpose, second gives usage guidance. No redundancy. The example is placed at the end for reference. Every part earns its place.

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 existence of an output schema (not shown) and the detailed parameter descriptions, the description is largely complete. It explains modes and profiles. It could mention the output structure (errors/warnings/suggestions) but that is covered by the output schema. Overall sufficient for the complexity.

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?

Schema description coverage is 100%, so baseline is 3. The description adds an example and hints about simple vs complex nodes, but the schema already provides detailed descriptions for each parameter. The added value is moderate.

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 n8n node configuration, specifies two modes (full/minimal), and provides a concrete example. This distinguishes it from sibling validation tools like validate_workflow by focusing on node-level validation.

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 gives explicit guidance on when to use each mode ('full' for comprehensive, 'minimal' for quick check). It does not explicitly exclude alternatives or state when not to use it, but the context implies it's for node config vs workflow validation. A clear use case is provided.

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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