quote_orderWhat an order would cost: per piece by size, the pieces, any volume discount, shipping, and the total before sales tax (tax is added at checkout where it applies). Nothing is charged. Use the sizes the customer named; a line is one item in one color with a count per size.
| Name | Required | Description | Default |
|---|---|---|---|
| lines | Yes |
Changes observed during successful MCP inspections.
Input schema / properties / lines / items / properties / design_idAdded value: +{
+ "description": "The design_id this line prints, when one has been made. Omit on a price with no design yet.",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds useful behavioral context: nothing is charged, sales tax is excluded and added at checkout, and the quote components are enumerated. It does not cover auth or rate limits, but for a read-only quote this is strong.
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?
Three efficient sentences: front-loaded return components, then the no-charge caveat, then the input rule. Every sentence adds distinct value with no wasted wording.
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?
With no output schema, the description carries the return burden and does so by listing per-piece cost, pieces, volume discount, shipping, and pre-tax total. Annotations cover safety; schema covers nested parameters. A minor omission is that item-key lookup via list_items appears only in the schema, not the description.
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?
The top-level 'lines' parameter lacks a schema description, but the tool description clarifies that a line is one item in one color with a count per size and says to use the sizes the customer named. The schema documents nested fields, and the description adds important line-grouping semantics beyond the structured data.
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?
States specifically what the tool does: calculates what an order would cost, including per-piece pricing, volume discount, shipping, and pre-tax total. 'Nothing is charged' distinguishes it from an actual checkout, but it does not explicitly differentiate from siblings, so 4 rather than 5.
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?
Implies pre-purchase quoting through 'Nothing is charged' and 'tax is added at checkout,' but gives no explicit when/when-not guidance or alternatives. The sibling list_items is only referenced in the schema, not in the tool description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.