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3D Printer on Demand

Combine quotes into one order

combine_quotes

Use this when someone has two or more quotes from 3D Printer on Demand in this chat and wants to order the parts together. It takes the private quote links, saves one quote that holds all the parts, and returns its private link with one combined total and one shipping charge, next to what the quotes cost ordered one by one. It does not change the earlier quotes, and it does not take a quote made outside this chat or a part still waiting for a person.

Input Schema

NameRequiredDescriptionDefault
quote_urlsYesThe private quote links from earlier quotes in this chat, one per part.

Output Schema

NameRequiredDescriptionDefault
partsNo
messageYes
outcomeYes
currencyNo
next_stepNo
quote_urlNo
saved_usdNo
total_usdNo
link_numberNo
shipping_usdNo
price_held_daysNo
separate_total_usdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare destructiveHint=false and openWorldHint=false, so the bar is lower, and the description still adds real context: a new quote record is written, earlier quotes are left untouched, and the response carries combined totals versus per-quote costs. It stops short of stating idempotency or whether repeated combines stack, which is the only meaningful gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the selection condition, then behavior, then exclusions — a sensible order with no filler. Three sentences is proportionate, though the middle sentence packs two ideas (what is saved and what is returned) that could read more cleanly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter mutation with annotations and an output schema, everything an agent needs is present: trigger, preconditions, side effects, what is left unchanged, and what the returned link represents. Return-value details are bonus rather than a burden here since an output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and minItems/maxItems already constrain the array, so the schema does the heavy lifting. The description still adds meaning the schema cannot: the links must be 'private quote links from earlier quotes in this chat' and one per part, which is exactly the mis-fill an agent would otherwise make.

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?

States a specific verb and resource ('saves one quote that holds all the parts') plus the outcome ('returns its private link with one combined total and one shipping charge'). It also distinguishes itself from quote_from_link by excluding quotes made outside this chat, so an agent can pick it out of the sibling list without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit trigger ('use this when someone has two or more quotes from 3D Printer on Demand in this chat') and explicit exclusions ('does not take a quote made outside this chat or a part still waiting for a person'). Both when-to-use and when-not-to-use are covered with no inference required.

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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