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knorq-ai

moneyforward-connector

by knorq-ai

mf_expense_list_depts

Lists departments for a specified MoneyForward office ID, enabling AI assistants to categorize expenses, invoices, and accounting records by department.

Instructions

部門一覧を取得します

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
office_idYes事業者ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the entire burden of behavioral disclosure, and it says nothing about authentication requirements, the read-only nature of the call, or that results are scoped to a single office. For a bare listing tool the gap is small, but nothing beyond the title-level statement is provided.

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

Conciseness3/5

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

A single short sentence with no wasted words, which is appropriately front-loaded. It is, however, under-specified rather than genuinely concise, so it cannot score higher.

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

Completeness3/5

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

For a one-parameter read tool with no output schema and no annotations, the description is minimally viable: the agent can infer the return type from the name. It does not explain the office-scoped nature of the results or how it relates to the accounting-namespace equivalent, which is the main thing an agent would need here.

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% (office_id is documented as 事業者ID), so the schema already carries the parameter meaning and the baseline of 3 applies. The description adds no additional context such as what happens if the office_id is invalid or whether it filters the returned departments.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("部門一覧を取得します" – retrieve the department list), so an agent knows exactly what the tool returns. However, it does nothing to distinguish itself from the very similar sibling mf_accounting_list_departments, so sibling differentiation is absent.

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

Usage Guidelines2/5

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

There is no indication of when this tool should be used versus alternatives such as mf_accounting_list_departments or mf_expense_list_offices, and no mention of preconditions (e.g., prior authentication via mf_expense_auth_start). The description only asserts what it does, leaving routing to the agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.