japan_corporate_registry

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It transparently states that the tool runs fully offline, returns a defined set of fields (corporate number, registered name/address, status, gBizINFO records), names its data sources (法人番号公表サイト and gBizINFO), and explicitly warns that out-of-set lookups return nearest matches rather than failing. This level of candor about limitations and output composition exceeds what is typical for a lookup tool.

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 substantial but each sentence earns its place: it front-loads the core function, then covers coverage/limitations, usage routing, and input reliability. It is not padded, though it could be tightened slightly (e.g., the data sources sentence is somewhat long). Overall it is well-structured and information-dense without being wasteful.

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 two-parameter lookup tool with no output schema, the description is remarkably complete. It covers what the tool returns, its data provenance, its coverage boundary, the reliability of different input types, and how it relates to sibling tools. An agent has everything needed to decide whether to invoke it and how to construct a correct call; nothing essential is missing.

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 both parameters are already documented. The description adds meaningful value beyond the schema by clarifying that a 13-digit corporate number resolves most reliably and by explaining the purpose of info_type ('Which facet to focus on') with concrete facet examples. This reinforces the schema's semantics without redundancy, earning a score above the baseline.

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 opens with a specific verb ('Look up') and a precise resource ('official identity of a Japanese company'), enumerating the exact data points (13-digit corporate number, address, legal status, gBizINFO certifications, subsidies, commendations). It clearly distinguishes itself from sibling tools by explicitly naming edinet_financials_usgaap for financials and japan_company_search for fuzzy discovery, leaving no ambiguity about its scope.

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 gives explicit usage guidance: 'Use this for KYB and entity-verification questions and for 'who or where is this company' lookups' and directly points to alternatives ('use edinet_financials_usgaap for financial figures, or japan_company_search for fuzzy discovery'). It also discloses the coverage limitation (192 blue-chip companies) and advises the most reliable input format (13-digit number or exact Japanese name), which is exactly the kind of operational guidance an agent needs.

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