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search_japanese_law

Search Japanese laws and regulations by keyword and return English-normalized metadata (law id, type, era, promulgation date, category) plus the matched Japanese text. No API key required. Japanese keywords match best; the underlying source is full-text Japanese.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (1-20).
keywordYesSearch term. Japanese matches the source text directly; English is best-effort.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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.

Conciseness5/5

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.

Completeness4/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines3/5

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.

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