Update existing work order details like name, status, vehicle, or customer in Shopmonkey.
Update fields on an existing work order.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The work order ID to update | |
| name | No | New order title | |
| status | No | New order status | |
| vehicleId | No | New vehicle ID | |
| customerId | No | New customer ID |
Changes observed during successful MCP inspections.
v1.1.1Input schema / properties / nameAdded value: +{
+ "description": "New order title",
+ "type": "string"
+}Input schema / properties / status / enumAdded value: +[
+ "Estimate",
+ "RepairOrder",
+ "Invoice"
+]v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Update fields', which implies mutation, but does not disclose whether updates are partial or full replacement, whether the operation is idempotent, what permissions are required, or what the response contains (no output schema). This is a critical gap for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action and target. It contains no filler or redundant phrasing, making it appropriately concise for a tool whose schema already covers parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is critically thin. It does not mention whether the operation returns the updated order, how partial updates are handled, or any error or validation behavior. The schema covers parameter names but not the operational context an agent needs to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents each parameter and its purpose. The description adds no additional meaning beyond the schema, so it meets the baseline of 3 but does not enhance understanding of parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Update') on a specific resource ('existing work order'), which clearly distinguishes it from create_order and get_order. It does not explicitly name alternatives, but the purpose is unambiguous and directly maps to the tool name and schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus create_order, get_order, or update_appointment. The implied use case is modifying an existing order, but there are no explicit conditions, prerequisites, or exclusions, leaving the agent to infer usage from the schema and siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.