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

Annotations already declare read-only, idempotent, non-destructive behavior. The description adds valuable context: data source (postcode.teraren.com), MIT license, no auth required, and the language flexibility of queries. This exceeds the baseline and provides operational expectations beyond the schema.

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 well-structured and front-loaded with the core purpose, followed by use cases, filtering details, and data source. Every sentence contributes meaningful information without redundancy or fluff.

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?

The description covers return format (address in three scripts, coordinates), data source, auth, and language support. It does not explicitly state that at least one search parameter should be provided or clarify interactions between query and filters, but the presence of an output schema mitigates the need to describe return structure in detail.

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 coverage is 100% with detailed parameter descriptions, so the baseline is 3. The description adds value by giving concrete examples (13 for Tokyo, 27 for Osaka), clarifying that queries can mix Japanese and romaji, and pointing to the prefectures tool for codes. This enhances understanding of parameter usage.

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 clearly states the verb (search), resource (Japanese postcodes), and scope (by free-text query, prefecture code, or city name). It also enumerates the returned fields (address in kanji/kana/romaji, coordinates) and mentions use cases, making it unambiguous and distinct from typical postal tools.

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?

The description provides clear context by listing use cases (autocomplete, geocoding, finding all postcodes in an area) and explains filtering options. However, it does not explicitly mention when to use this tool over the sibling postcode-japan.postal.lookup or other postal tools, lacking exclusion guidance.

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