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

With no annotations, the description carries the full burden and it does disclose genuine behavioral traits: deterministic rule-based processing, no external AI API calls, and the specific dimensions inspected. It stops short of stating side-effect profile (read-only analysis vs. mutation), input length limits, or the shape of the results, leaving meaningful gaps for a tool with zero structured behavioral coverage.

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

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

Three short sentences with no filler, and the core purpose is front-loaded before the scope notes. Efficient, though it could be tightened slightly by folding the AI-API disclaimer into the first sentence.

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

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

For a low-complexity single-parameter tool this is close to adequate, but with no output schema the description never tells the agent what a 'check' returns (flags, list of issues, scores) or in what form, which is the main remaining uncertainty an agent must resolve.

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

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the single parameter's schema description (チェック対象の日本語記事本文) mirrors the description text, so nothing beyond the schema is added. The baseline of 3 applies when the schema fully documents the parameters.

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

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

The description pairs a specific verb (チェックします) with a precise resource (日本語の記事本文) and even names the check categories (断定・誇張表現、重複文、PR表記、URL形式の出典). It also carves out the approach by stating it is rule-based and does not use an external AI API, which distinguishes it from AI-driven alternatives. No siblings exist, so no sibling differentiation is required.

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

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

Usage is implied rather than stated: the words 簡易 and 外部AI APIは使用しません signal an offline, low-cost quick screen, which hints at when an agent might reach for it. But there is no explicit when-to-use/when-not phrasing and no named alternative to route against.

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