n8n-io/n8n · error · NodeOperationError

Model did not provide parameter '${parameter.name}' which is

Error message

Model did not provide parameter '${parameter.name}' which is required and must be present in the input

What it means

Thrown by configureToolFunction when iterating tool parameters: a parameter marked required is absent (undefined or null) from the model-supplied input object. This is a contract enforcement — the tool schema promised a required field and the model did not deliver it.

Source

Thrown at packages/@n8n/nodes-langchain/nodes/tools/ToolHttpRequest/utils.ts:751

							dataFromModel = { [toolParameters[0].name]: query };
						} else {
							throw new NodeOperationError(
								ctx.getNode(),
								`Input is not a valid JSON: ${error.message}`,
								{ itemIndex },
							);
						}
					}
				} else {
					dataFromModel = query;
				}

				for (const parameter of toolParameters) {
					if (
						parameter.required &&
						(dataFromModel[parameter.name] === undefined || dataFromModel[parameter.name] === null)
					) {
						throw new NodeOperationError(
							ctx.getNode(),
							`Model did not provide parameter '${parameter.name}' which is required and must be present in the input`,
							{ itemIndex },
						);
					}
				}

				for (const parameter of toolParameters) {
					let argument = dataFromModel[parameter.name];

					if (
						argument &&
						parameter.type === 'json' &&
						!['qsRaw', 'headersRaw', 'bodyRaw'].includes(parameter.key ?? '') &&
						typeof argument !== 'object'
					) {
						try {
							argument = jsonParse(String(argument));

View on GitHub (pinned to 5ac6606e81)

Solutions

1. Mark the parameter as optional if the workflow can function without it.
2. Strengthen the parameter description so the model understands it must always supply the value.
3. Provide a sensible default in the tool description so the model fills it.
4. Switch to a structured tool schema so the agent framework validates required fields upfront.

Example fix

// before: parameter { name: 'query', required: true } omitted by model → throws
// after: relax the constraint or guide the model
{ name: 'query', required: false }
// or enrich description: 'query (REQUIRED): the search term, never omit'

for (const p of toolParameters) {
  if (p.required && (dataFromModel[p.name] === undefined || dataFromModel[p.name] === null)) {
    dataFromModel[p.name] = p.defaultValue ?? ''; // supply a default before running
  }
}

function hasAllRequired(params: ToolParameter[], data: IDataObject): boolean {
  return params.filter(p => p.required).every(p => data[p.name] !== undefined && data[p.name] !== null);
}

if (!hasAllRequired(toolParameters, dataFromModel)) { /* re-prompt model */ }

When it happens

Trigger: The LLM omits a required argument; the model sends an empty string or null for a required field; parameter names in the schema don't match what the model emits due to case/spacing.

Common situations: Models trimming arguments they deem unnecessary; parameter names that are ambiguous; required flags set on fields the model cannot infer from context.

Related errors

• Parameter ${parameter.name} is not a valid JSON: ${error.mes
• Input is not a valid JSON: ${error.message}
• The type ${genericType} is not supported
• The response type must be a string. Received: ${typeof respo
• The response type must be an object or an array of objects

AI-assisted analysis of n8n-io/n8n@5ac6606e81 (2026-08-12). Data as JSON: /api/errors/c9619b6ca42dafc7. Report an issue: GitHub.