japanlaw.org — Japanese law

Look up the words a law defines

get_definitions

Read-onlyIdempotent

What a word means in a Japanese law that defines it. The words a law defines for itself (定義語): inside that law, and only as far as each definition reaches, the word means what the statute says, not what it means in everyday speech or in another law. For each, the statute's own words (statuteJa), its reading, its English and whose that is (englishWhose), a plain explanation by japanlaw.org (explanation, in lang), where it is defined (definedAt, url) and how far it reaches (scope, scopeLabel). With address — {"law": "labor-standards-act", "address": "art-36"} — the definitions that apply in that provision, because its text uses the word, and japanlaw.org's explanations of the words of Japanese law it uses (concepts: 施行, 政令, 附則…). Call it before explaining what a provision means. term narrows the answer to one word, in Japanese, its reading or its English. A law with many terms stops at one; continued.cursor, passed back as cursor with the same arguments, goes on. The text in force only.

Input Schema

Name	Required	Description
`law`	Yes	The law: its Japanese title (労働基準法), English title (Labor Standards Act), short name (労基法), slug (labor-standards-act) or e-Gov law ID (322AC0000000049).
`lang`	No	The language of the pages every url opens, and of the card get_provision is drawn as: "en" (default) or "ja". The text returned always holds both languages.
`term`	No	One word to look up: the term (労働者), its reading (ろうどうしゃ) or its English (worker).
`cursor`	No	Go on from here: the cursor an earlier answer's continued gave, with the same law, address and term.
`address`	No	A provision: the definitions that apply in it, and the legal vocabulary it uses. Unset lists every term the law defines. Written as for get_provision: 第三十六条, Article 36(2) or art-36/par-2.

Output Schema

Name	Required	Description	Default
`url`	Yes
`path`	Yes
`lawId`	Yes
`total`	Yes
`concepts`	Yes
`definitions`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 1, 2026

addedInput schema / properties / cursor

Added value: +{
+  "description": "Go on from here: the cursor an earlier answer's continued gave, with the same law, address and term.",
+  "maxLength": 300,
+  "type": "string"
+}

removedInput schema / properties / from

Removed value: -{
-  "description": "Go on from this term: the from an earlier answer's continued gave, with the same law, address and term.",
-  "maxLength": 300,
-  "type": "string"
-}

First observedOct 31, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations by disclosing pagination semantics (a law with many terms stops at one; continued.cursor must be passed back with the same arguments), the currency constraint ('The text in force only'), and the fact that the response mixes statute text, japanlaw.org explanations, and related legal concepts (施行, 政令, 附則). That is substantive behavioral context an agent could not infer from annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded in the first sentence, followed by scope, mode selection, and pagination in a logical order. The long parenthetical enumerating return fields (statuteJa, englishWhose, definedAt, scopeLabel…) partly duplicates the existing output schema and makes the middle sentence a run-on, which is the main efficiency cost.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a five-parameter tool with an output schema, the description covers everything an agent needs: what is returned conceptually, how address changes the result set, how term narrows it, how to continue paging, and that only in-force text is included. No material gap remains.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all five parameters; the description adds value by explaining why address matters ('because its text uses the word'), that term matches Japanese, reading, or English, and that cursor must be reused with identical arguments. The marginal gain is real but modest given how complete the schema is.

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 specific verb and resource: it returns the words a Japanese law defines for itself (定義語), and explicitly bounds their meaning to that law's reach rather than everyday speech or another law. The 'Call it before explaining what a provision means' line and the address/term framing make it clearly distinct from get_provision and get_law.

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 concrete when-to-use direction ('Call it before explaining what a provision means') and explains the two operating modes: unset address lists every defined term, while address returns only the definitions that apply in that provision. It does not explicitly route away from siblings such as search or get_provision beyond the address-format cross-reference, so it stops short of full alternative naming.

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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