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knorq-ai

moneyforward-connector

by knorq-ai

mf_expense_update_transaction

Updates an existing expense transaction in MoneyForward Cloud Expense, changing fields like amount, date, memo, expense category, department, project, and tax type.

Instructions

経費明細を更新します

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
memoNoメモ
valueNo金額
remarkNo摘要
dept_idNo部門ID
office_idYes事業者ID
ex_item_idNo経費科目ID
project_idNoプロジェクトID
dr_excise_idNo税区分ID
recognized_atNo日付(YYYY-MM-DD)
transaction_idYes経費明細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 provided, so the description carries the full burden of behavioral disclosure. It only implies a mutation via 更新 and says nothing about partial vs full update semantics, permission/auth requirements, reversibility, or what happens to fields omitted from the call.

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?

A single, front-loaded sentence with zero filler or repetition. It is efficient, though its brevity borders on under-specification rather than optimal conciseness.

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

Completeness2/5

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

For a 10-parameter mutation tool with no annotations and no output schema, the description is far too thin. It omits which fields are updatable, whether updates are partial or whole-record, and any indication of the result of the operation.

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%, with every one of the 10 parameters (memo, value, remark, dept_id, ex_item_id, project_id, dr_excise_id, recognized_at, etc.) documented in the schema. The description adds no additional parameter meaning, so the baseline 3 applies.

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 (更新) and resource (経費明細), so an agent knows this mutates an expense line item. However it does nothing to distinguish itself from siblings like mf_expense_create_transaction or mf_expense_delete_transaction beyond the verb.

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 when-to-use guidance, no mention of prerequisites (e.g. that office_id and transaction_id must reference an existing record), and no routing to alternatives such as create/delete/get. The agent must infer all usage context from the name alone.

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