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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), and the description adds real context beyond them: a per-call price of $0.005 USDC via x402 on Base, and the explicit limitation that a missing postal code is never inferred. It does not cover failure modes, error responses, or latency, which keeps it short of a 5.

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 English text is front-loaded and well structured (purpose, use-when, returns, cost), but the entire payload is then mirrored verbatim in Japanese, roughly doubling length without adding information a capable model needs. The Use-when clause also restates the purpose sentence rather than extending it.

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?

With no output schema, the description correctly enumerates the return fields (hierarchy components, confidence, match hierarchy, geocoder and postal evidence) and states the pricing and non-inference guarantee. The main remaining gap is input-side guidance: format expectations for `address` and the effect of `response_language` on the returned English rendering.

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 0% for two parameters. The description says nothing about the `address` parameter's expected script or format (Japanese characters vs romaji) or the length bound, and it never explains the `response_language` enum values ja/en/both, even though output language is the one ambiguity an agent would need clarified.

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 first sentence names a specific verb (normalize), a specific resource (Japanese address), and the output shape (canonical hierarchy with English rendering), which distinguishes it from extraction siblings like jp_receipt_extract. It never explicitly contrasts with the nearest sibling, jp_address_validate, so the boundary is inferred rather than stated.

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?

"Use when: You need Japanese address normalization or standardization, whether or not the input contains a postal code" gives a clear triggering condition and pre-empts the most likely confusion (postal code presence). However, it names no alternative tool and no exclusion that would route an agent to jp_address_validate instead.

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