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Caribooks (QuickBooks Online)

Answer a loop's question

answer_question

Send the user's answer to one of the loops' questions (list_questions): the answers they picked, by item and answer number, and what they said in their own words. Only ever the user's own answer: never answer for them. The loop reads the answer and proposes what it understood; nothing changes in QuickBooks until the user approves those changes in Caribooks Approvals.

Input Schema

NameRequiredDescriptionDefault
picksNoThe answers the user picked, one per item, by the numbers list_questions shows.
answerNoThe user's answer in their own words.
question_idYesThe question's id, as list_questions shows it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations, the description discloses the important behavioral chain: the loop reads the answer and proposes an interpretation, and nothing changes in QuickBooks until the user approves changes in Caribooks Approvals. That side-effect boundary is exactly the kind of context an agent needs for a non-read-only tool.

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

Conciseness5/5

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

The description is front-loaded with the purpose, then adds the critical user-answer constraint, then closes with the approval-based side-effect boundary. Every sentence serves a distinct purpose and there is no wasted filler.

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

Completeness4/5

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

It covers the purpose, the source of questions, the user-only constraint, and the downstream approval behavior, which is enough to invoke the tool correctly. The main minor gap is that there is no output schema and the description does not explicitly state what the tool returns after the answer is sent.

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

Parameters3/5

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 question_id, picks, item, and answer. The description reinforces that picks are by item and answer number and that answer is in the user's own words, but it adds no syntax or constraints beyond the schema.

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?

The description states a specific verb and resource: sending the user's answer to one of the loop's questions. It explicitly points to list_questions as the source of questions, so an agent can distinguish it from the sibling that lists questions.

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

Usage Guidelines4/5

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

The description makes clear this is used after list_questions and that the agent must only relay the user's own answer, never answer on the user's behalf. It lacks an explicit statement of when not to use the tool or a named alternative beyond list_questions, so it is strong but not fully exhaustive.

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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