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tera911

MF Invoice MCP

by tera911

mf_auth_start

Initiate OAuth authentication for the MoneyForward Cloud Invoice API by starting a local server to handle callback responses.

Instructions

OAuth認証を開始します。ローカルサーバーを起動してコールバックを待ちます。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNotrueの場合、認証完了まで待機します(デフォルト: false)
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 mentions starting a local server and waiting for callback, which gives some context about the tool's behavior (e.g., it likely involves network operations and user interaction). However, it lacks details on critical aspects such as authentication requirements, potential side effects (e.g., opening a browser), error handling, or rate limits. For a tool with no annotation coverage, this is insufficient.

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 concise and front-loaded, consisting of two sentences that directly state the tool's purpose and key behavior. Every sentence earns its place by providing essential information without unnecessary details, making it efficient and well-structured.

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?

Given the tool's complexity (involves OAuth and local server operations), lack of annotations, and no output schema, the description is incomplete. It covers the basic purpose and some behavior but misses important contextual details like what the tool returns, error conditions, or how it integrates with sibling tools. While it's adequate for a minimal understanding, there are clear gaps that could hinder effective use by an AI agent.

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?

The input schema has 1 parameter with 100% description coverage, so the schema already documents the 'wait' parameter thoroughly. The description doesn't add any meaning beyond what the schema provides regarding parameters. According to the rules, with high schema coverage (>80%), the baseline is 3 even with no param info in the description, which applies here.

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 clearly states the tool's purpose: 'OAuth認証を開始します' (starts OAuth authentication) and 'ローカルサーバーを起動してコールバックを待ちます' (starts a local server and waits for callback). It specifies the verb ('開始します' - starts) and resource (OAuth authentication), but doesn't explicitly differentiate from sibling tools like mf_auth_callback or mf_auth_status, which is why it's not a 5.

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

Usage Guidelines3/5

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

The description implies usage context by mentioning starting a local server and waiting for callback, which suggests this is for initiating OAuth flows. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like mf_auth_callback or mf_auth_status, nor does it specify prerequisites or exclusions. The usage is implied but not clearly articulated.

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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