japan-data-mcp

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

With no annotations, the description carries the full burden. It discloses that no API key is required, that it returns authentic text with metadata and attribution, and that output is truncated to max_chars. However, it does not mention error handling, rate limits, or what happens if the ID is invalid, which is a notable gap for a fetch 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?

Two sentences, no filler. The primary purpose is front-loaded, and the typical flow is stated succinctly at the end. Every sentence contributes to understanding.

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 simple fetch tool with 3 parameters and no output schema, the description covers the purpose, the usage flow, the authentication requirement, and the output nature. It does not detail error cases, but it is sufficient for an agent to call the tool correctly.

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?

Although schema coverage is 100%, the description adds meaningful context by clarifying that law_id can be a revision_id from search results and by explaining the truncation behavior. It also frames the article parameter as optional extraction, adding value beyond the schema.

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 ('Fetch') and resource ('original Japanese text of a law'), and explicitly distinguishes itself from the search siblings by referencing 'search_japanese_law' as the source of the IDs. The typical flow clarifies its role in the pipeline.

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 clearly states the dependency on search_japanese_law and gives a typical flow (search_japanese_law -> get_law_text), which guides when to use it. It does not explicitly list alternatives or exclusions, but the sibling tools are search-focused and the context makes the usage obvious.

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?

With no annotations, the description carries the burden of behavioral disclosure. It mentions the required API ID and the output format (English-keyed records). However, it does not specify whether partial name searches return multiple results, pagination behavior, or error conditions. It covers core behavior but leaves some operational details unstated.

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 two sentences, front-loaded with the main action and search criteria, then the requirement. No filler; every clause adds information. It is concise and well-structured.

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 lookup tool with two parameters and no output schema, the description covers the essential context: what it does, what it returns, and a key prerequisite. It lacks details on result limits or multiple matches, but for a simple lookup this is acceptable. The requirement note is particularly helpful.

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% for both parameters, so the schema already describes each field. The description adds value by clarifying that the two parameters are alternatives ('or'), which is not explicit in the schema. It also reinforces the 13-digit format and Japanese language requirement, providing practical guidance.

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 states a specific verb ('Look up') and a precise resource ('Japanese corporation'), and names the two search keys (partial name or 13-digit corporate number). It also distinguishes the tool from siblings by specifying the domain (corporations vs. law/statistics).

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 clearly states the prerequisite (a free National Tax Agency application ID) and implies usage for corporate lookups. It does not need to exclude siblings because they cover different domains. No explicit when-not-to-use is given, but the context is clear enough.

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?

With no annotations provided, the description must carry the behavioral burden. It discloses that no API key is required and that the source is full-text Japanese, and it specifies the return contents. However, it does not state whether the operation is read-only (though implied by 'search'), or mention rate limits, pagination, or error behavior. It adds useful context beyond the schema but is not fully transparent about side effects or constraints.

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 two sentences with zero filler. The primary purpose and return details are front-loaded, followed by the access note and language hint. Every sentence contributes value, and it is appropriately concise for a tool of this complexity.

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 simple search tool with two parameters and no output schema, the description covers the essential operational details: what it returns, the language constraint, and access requirements. It omits details like result ordering or error handling, but those are not critical for a basic keyword search. The listed metadata fields and the note on Japanese text give sufficient context for an agent to invoke it correctly.

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 input schema already provides descriptions for both parameters with 100% coverage. The description reinforces that Japanese keywords match best, but this is nearly a verbatim repeat of the keyword schema description ('Japanese matches the source text directly; English is best-effort'). It adds no new meaning beyond what the schema already conveys, so the baseline of 3 is appropriate.

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 states a specific action ('Search Japanese laws and regulations by keyword') and specifies the output ('English-normalized metadata ... plus the matched Japanese text'). This clearly identifies the tool's resource and distinguishes it from siblings like search_corporation or search_statistics, which target different domains. The phrasing is unambiguous and action-oriented.

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 offers a usage hint about keyword language ('Japanese keywords match best') but does not explicitly state when to choose this tool over its siblings or mention any exclusions. There is no reference to get_law_text or other alternatives, leaving the selection decision to inference. It provides some contextual guidance but not a clear when-to-use vs. when-not-to.

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?

With no annotations provided, the description carries the full behavioral burden. It discloses the required authentication prerequisite (e-Stat application ID) and the metadata fields returned, which is useful context. It does not mention network failures, rate limits, or how the ID is supplied, but for a straightforward read-only search tool this is adequate.

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 a single sentence that front-loads the action and scope, then adds return details and the authentication requirement. Every phrase earns its place with no wasted words.

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 simple two-parameter tool with no output schema, the description covers the core call intent, returned fields, and a needed credential. It could add more about error behavior or how the application ID is passed, but the essential information is present.

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 input schema already documents both parameters with 100% coverage, so the description adds limited parameter-level meaning. 'By keyword' reiterates the keyword parameter but does not enrich it beyond the schema.

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 action ('Search'), a concrete resource ('Japanese official statistics tables (e-Stat)'), and the result shape ('English-keyed table metadata'). It is clearly distinct from the sibling tools, which target laws and corporations.

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 makes the intended domain unambiguous by naming e-Stat as the source and states the key prerequisite of an application ID. It does not explicitly contrast with siblings, but the resource differences are obvious enough that an agent can choose correctly.

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