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

Annotations already cover the safety profile (readOnlyHint=false, destructiveHint=false, non-idempotent), so the description is not contradicted. It adds real context beyond them: the returned artifact set, a verification link with an explicit 30-day expiry, and the explicit disclaimer that the worksheet is neither saved nor rendered to PDF.

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 compact sentences, front-loaded with what is produced, then the default behavior, then the negative scope. No filler, though the middle sentence could be folded into the schema's format documentation.

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 7-parameter tool with no output schema, the description supplies the return payload, the link lifetime, and the non-persistence guarantee, which the schema cannot convey. Only the routing against sibling tools is absent, so it is near-complete rather than fully complete.

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%, so the parameters are already well documented. The description only restates one default (format omitted → test_mixed), adding marginal value over the schema; baseline 3 applies.

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?

States a specific verb and resource (既存の問題を組み合わせて…プリント案を作り) and enumerates the return (問題一覧 + 確認用リンク). It implicitly separates itself from the sibling mutation tools by framing itself as the generator, but does not name an alternative explicitly.

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?

It gives one when-behavior (形式を省くと書きと読みのテストになります) and one when-not (プリントの保存と PDF の作成はしません), which is genuinely useful. However it never explains when to pick this over check_available_kanji, find_replacement_questions, or replace_question, leaving routing to inference.

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