Currently, a change in the tf_vars property does not trigger a recreation but a modification of the template.

As the tf_vars effectively change the content of the template, it should trigger a new version.

As an example, it would be possible to change the name of a parameter via tf_var.

A more drastic example to show what would be possible is to base the entire coder parameters on a tf_var:

template.tf

resource"coderd_template""example" {name="example"description="example"versions=[    {      directory="./template"      active=true      tf_vars= [{        name="parameters"        value=jsonencode(["cpu","memory"        ])      }]    }  ]}

in the template:

variable"parameters" {type=string}locals {parameters=jsondecode(var.parameters)}data"coder_parameter""parameters" {for_each=toset(local.parameters)name=each.key}

If I change the content of the parameters var via the coderd_template in this scenario, the whole template would change.