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yabooung

jp-law-mcp

by yabooung
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TypeScript
Hybrid

法令引用の実在確認

verify_citations

Checks legal citations in Japanese text against statute data, confirming cited laws, articles, paragraphs, and items exist and flagging mismatches or repealed laws with reference excerpts.

Instructions

文章に含まれる法令引用（例: 行政手続法第八条第一項、所得税法（昭和四十年法律第三十三号）第五十七条の二）を取り出し、法令・条・項・号が実在するか確かめます。法令名の誤り、存在しない条、括弧内の法令番号と名称の食い違い、廃止された法令を知らせ、照合用に条文の抜粋を付けます。AI が書いた回答や文書の引用を確認するときに使います。法令を挙げて答えるときは、答えを返す前に、挙げた引用をまとめてこのツールに渡してください（存在しない条を含む答えを返さないため）。主張の内容が正しいかは判断しません。

Input Schema

NameRequiredDescriptionDefault
asofNoこの日に施行されていた版で確認（2017-04-01 以降）。省略で現行
textYes確認する文章
detailNo引用した項・号の本文を長く（600 字まで）返す。答えの内容が条文と合っているか突き合わせるとき
default_lawNo法令名のない「第N条」をどの法令として扱うか（法令名か法令ID）

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.3.20261020
    • addedInput schema / properties / detail
      Added value: +{
+  "default": false,
+  "description": "引用した項・号の本文を長く（600 字まで）返す。答えの内容が条文と合っているか突き合わせるとき",
+  "type": "boolean"
+}
  2. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full load and does well: it discloses what the response contains (error classes plus matched article excerpts for cross-checking) and draws a clear boundary that claim correctness is out of scope. It stops short of stating whether verification requires network/auth, rate limits, or how large result sets behave.

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?

Front-loads purpose and examples, then moves to output contents, then to when to call it and the pre-answer workflow rule, ending with the scope limit. Every sentence adds a distinct fact with no repetition.

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?

No output schema and no annotations, so the description must cover behavior, which it largely does via the enumerated error classes and excerpt attachment. The only mild gap is lack of detail on response shape or handling of very large citation sets.

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?

Schema coverage is 100%, so asof, text, detail, and default_law are already fully documented in the schema; the description adds no parameter-level detail beyond what structured data provides. Baseline 3 applies.

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?

States a concrete verb pair (extract citations, verify existence) with concrete examples of citation forms (行政手続法第八条第一項, 所得税法（昭和四十年法律第三十三号）第五十七条の二). It also enumerates the specific failure classes it detects (wrong law name, nonexistent article, law-number/name mismatch, repealed law), which clearly differentiates it from siblings like find_cited_provisions or search_law_text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit usage contexts ('AI が書いた回答や文書の引用を確認するときに使います') and a concrete workflow instruction (pass all cited provisions to this tool before returning an answer). It also states an explicit exclusion ('主張の内容が正しいかは判断しません'), defining what the tool will not do, though it never names a sibling as an alternative.

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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