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

Beyond the readOnlyHint annotation, it discloses that the call is side-effect free (no job, no credits), that the analyzed range may not match the requested range because scenes may not cover it, and that user approval is required. This is exactly the kind of non-obvious behavior an agent needs.

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?

The description is compact and front-loaded: purpose, side-effect guarantee, caveat, and required workflow are each covered in a short sentence or bullet. No redundant text.

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 read-only preflight tool, it covers what is needed to invoke it correctly and what to do with the result, including the approval step and the range-mismatch caveat. Since the return is conceptually just the analyzed range and credit estimate, no output schema is needed for correct use.

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 baseline is 3. The description adds a useful cross-tool note that parameters are identical to analyze_*, but it does not explain individual parameter semantics beyond the schema.

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 uses a specific verb (確認) and resource (解析範囲と消費クレジット), and explicitly contrasts itself with analyze_* by stating no job is created and no credits are consumed. This makes it easy for an agent to distinguish it from the analyze_* siblings.

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 provides a direct mandatory usage rule: 'analyze_* を実行する前に必ずこれを呼び、結果をユーザーに提示して承認を得てください'. It also tells the agent that the same arguments as analyze_* can be passed as-is, removing ambiguity about parameter selection.

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