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knorq-ai

moneyforward-connector

by knorq-ai

mf_expense_list_projects

Fetches a list of projects for a specific office ID to support expense management and project-based reporting in MoneyForward.

Instructions

プロジェクト一覧を取得します

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 provided, so the description carries the full burden, yet it says nothing about auth requirements, scoping by office, pagination, or ordering. For a read-list tool the safety burden is light, but the behavioral disclosure is essentially absent.

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 short sentence with no filler and the resource front-loaded. It is efficient, though sparse to the point of under-specification.

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 simple one-parameter list tool this is minimally adequate, but with no output schema and no annotations the description should at least hint at what is returned (fields, pagination). It leaves the agent without return-shape context.

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 coverage is 100% (the single office_id parameter is described as 事業者ID), so the schema already documents the parameter. The description adds no filtering or format semantics beyond it, which is the expected baseline when the schema does the work.

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?

The description states a clear verb (取得します) and resource (プロジェクト一覧), so an agent knows it retrieves a list of projects. It distinguishes itself implicitly from siblings like mf_expense_list_offices and mf_expense_list_depts by resource name, but adds no further differentiation or scope detail.

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 guidance on when to call this tool versus the many sibling list tools, no prerequisites, and no exclusions. Usage is only inferable from the resource name.

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