Japan Corporate Number and Certifications (gBizINFO)

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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds the content categories returned (prices, licensing, limits, freshness), which is useful context, but an output schema exists and would surface the same structure, so the incremental disclosure is modest.

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?

A single front-loaded sentence with no filler; every clause enumerates distinct payload content, so nothing is wasted.

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 parameters, a read-only annotation, and an output schema present, the description need not explain return values or safety. It is nearly complete for this simple tool; only a hint about when to reach for it is absent.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline 4 applies under the '0 params' rule.

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?

Clear verb ("List") plus resource ("the tools of this server") and an enumeration of the payload contents (prices, data sources, licensing, daily limits, freshness). It is plainly distinguishable from siblings like get_receipt or drone_flight_check, though it does not explicitly name or contrast them.

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?

No explicit when-to-use or when-not-to-use guidance is given; usage is only implied by the discovery framing ("the tools of this server"). An agent can infer this is the entry point for learning available tools and pricing, but nothing states that intent directly.

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

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld), so the bar is lower. The description adds genuinely useful behavior that annotations cannot convey: zero rows means the source is non-exhaustive rather than truly 'none', the row data is 'as published', a source notice is carried, and the result is explicitly 'not an official result'. These provenance/coverage caveats are exactly the kind of context 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?

Three sentences, front-loaded with the core question and followed by the return shape and the decisive caveats. Every sentence carries weight; the only minor cost is the dense parenthetical clauses, but nothing is wasted.

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?

An output schema exists, so return-value documentation is not required. Given the read-only nature (annotations) and full schema coverage, the description closes the remaining gaps by explaining the non-exhaustive coverage semantics and provenance. It is complete enough to call correctly without overclaiming.

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 all three parameters are already documented (limit semantics with total/truncated, ministry filter example, corporate_number check-digit validation). The description adds no parameter-level detail beyond this, so the baseline 3 applies.

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+resource: 'Which notifications and certifications ... does gBizINFO publish for this Japanese corporate number?' It names the source (METI), the entity type (corporate number), and the returned fields (ministry, title, date). This is clearly distinguishable from siblings like gbizinfo_company_basic or gbizinfo_resolve_corporate_number.

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 explains what you get and the key semantic caveat (zero rows = unknown, not none), which implicitly guides interpretation. However, it never states when to prefer this tool over siblings such as gbizinfo_company_basic, nor any prerequisites for selecting it. Usage is implied rather than directed.

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

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld), and the description adds real context on top: closure data appears only when the source states it, status_as_of is derived from gBizINFO's last_acquisition_date, the response carries a gBizINFO source notice, and the result is explicitly not official. It does not contradict any annotation.

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 scope of returned data is front-loaded in the first clause, followed by provenance and disclaimer notes in a compact form. Slightly awkward question-form opening and a few clauses that restate provenance (source notice / not official) cost it the top score, but nothing is padded.

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 single-parameter read tool with a full output schema and covering annotations, the description supplies what structured fields cannot: data provenance (National Tax Agency via gBizINFO), conditional presence of closure data, the meaning of status_as_of, and a not-official caveat. An agent can call and correctly interpret the response without further context.

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 sole corporate_number parameter is fully documented (format, example, check-digit validation) without description help. The description only refers to it obliquely as 'this Japanese corporate number', adding nothing beyond the schema, so the baseline 3 applies.

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 names a specific resource (basic information for a Japanese corporate number) and enumerates exactly which fields come back (name, kana, English name, address, closure date/cause), plus an explicit exclusion (representative names are not returned). It distinguishes itself from gbizinfo_certifications by scoping to basic registry data, but never names gbizinfo_resolve_corporate_number as the way to obtain the number, so sibling differentiation is implicit 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?

Usage is only implied: the reader infers that a valid 13-digit corporate number is required and that this is the lookup for core registry facts. There is no explicit when-to-use statement, no condition for choosing it over catalog/gbizinfo_certifications, and no pointer to gbizinfo_resolve_corporate_number for name-to-number resolution.

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

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

Annotations already cover readOnly, idempotent and openWorld, and the description adds genuine behavioral context beyond them: candidates are labelled exact_name vs fuzzy_candidate, results include total and may be truncated, the gBizINFO source notice is carried, and results are 'not official'. It stops short of stating rate limits or pagination mechanics.

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?

Three tight sentences: purpose first, then result behaviour, then the disclaimer. The leading question is slightly rhetorical but effectively front-loads the purpose, and nothing is wasted.

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 a full output schema, complete parameter descriptions and read-only/idempotent annotations, the description only needs to add matching semantics, no-auto-pick behaviour and the non-official caveat — all of which it does. A brief note on how to proceed after choosing a candidate would make it fully complete.

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 name, limit, prefecture and address_hint are already fully documented in the schema, including the partial-match and no-drop ordering semantics. The description restates the name/prefecture behaviour but adds no parameter meaning beyond the schema, so the baseline 3 applies.

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+resource question ('Which Japanese corporate numbers could this company name refer to?') and then states exactly what it searches (gBizINFO by partial name, optional prefecture) and what it returns (every candidate marked exact_name or fuzzy_candidate). This clearly separates it from siblings like gbizinfo_company_basic, which presumably takes an already-known number.

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 makes the use case explicit: name-based resolution with no automatic selection ('Never picks one for you'), which is the condition that selects this tool over a direct number lookup. It does not, however, name the alternative tool (e.g. gbizinfo_company_basic) to call once a number is chosen, so the routing guidance stops one step short of 5.

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

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

Goes well past readOnlyHint=true by disclosing cost ('Free'), the failure mode and error code (RECEIPT_NOT_FOUND for unknown/unsettled ids), and the retention window (90 days after settlement). These are exactly the runtime traits an agent needs before calling.

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?

Three short sentences, front-loaded with the action and the receipt_id, followed by behavioral facts. No filler, no restatement of the title.

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?

An output schema exists, so return values need no explanation, and the description still covers cost, error behavior, and retention limits. Nothing an agent needs to call this correctly 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% and the schema already specifies the receipt_id format ('rcpt_' + 64 hex characters, maxLength 80). The description only names the identifier without adding format or constraint detail, so the schema does the real work.

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 ('re-fetch'), specific resource ('stored result of a settled paid call'), and the keying mechanism ('by its receipt_id'). The 're-fetch ... for when the response was lost' framing clearly separates it from the unrelated sibling 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?

Gives an explicit triggering scenario: use it when a paid call's response was lost after payment. It also implies the boundary condition (unknown or unsettled ids are not valid targets), but does not name an alternative tool or state a when-not clause for other lookup paths.

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