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

Annotations already declare readOnly/idempotent/openWorld, so the burden is lower. The description adds real behavioural context beyond that: the register is a closed read-only dataset covering 5.8M entities, matching semantics (substring, prefix/suffix legal forms), and that English names only exist for some entities (NTA) or LEI-bearing ones (GLEIF). It does not disclose pagination or result ordering, which is a minor gap given the annotated safety profile.

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?

Front-loaded with the core purpose and the primary matching modalities, then scope, then the follow-up call. It is dense but every clause earns its place; the only mild excess is the enumeration of legal forms, which is nonetheless useful for a matching tool.

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 search with no output schema and full schema coverage, the description is nearly complete: it covers matching rules, filter behavior, dataset scope, and the hand-off. It doesn't document the returned fields' semantics in detail or sorting/pagination, but those are secondary for selection.

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%, so 3 is the baseline. The description goes further by explaining the actual semantics of the name match (kanji/katakana substring, legal-form prefix/suffix handling, English-name sources) and restates the prefecture filter accepts JP/EN/code, which meaningfully enriches what the terse schema says.

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+resource: 'Search Japan's National Tax Agency corporate-number register by name'. It names the data source jurisdiction and distinguishes scope from the broader company_register_search sibling, and names jp_corporate_number as the sibling it hands off to for detail.

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?

Describes a clear use context (find a match's corporate number and identity to disambiguate, then call jp_corporate_number for full detail) and gives a precise coverage statement. It stops short of an explicit 'do not use this for X' exclusion, so it is clear but not fully framed against alternatives.

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