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jp_get_article

Read-onlyIdempotent

Fetch the text of a specific article from Japanese law. Input law ID and article number to retrieve official text.

Instructions

Fetch the text of one article of a law.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
law_idYese.g. ``"129AC0000000089"`` (the Civil Code).
article_numYesthe e-Gov ``Num`` attribute, e.g. ``"1"`` for Article 1, ``"3_2"`` for a branch article (第三条の二).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNo
law_idYes
captionNo
eli_uriNo
eli_noteNoJapan has not deployed ELI. eli_uri is the durable e-Gov viewer URL (https://laws.e-gov.go.jp/law/{law_id}), keyed on the stable law_id e-Gov assigns to every law - never invented.
source_urlNo
article_numYes
dataset_noteNoe-Gov (laws.e-gov.go.jp) is Japan's official portal for national legislation, run by the Digital Agency. Japan has no ELI scheme; eli_uri carries the durable e-Gov viewer URL keyed on law_id (see eli_note). Discover by law_title (jp_search_laws) or full-text keyword (jp_search_by_keyword), then fetch metadata or a specific article by law_id.
human_readable_citationNo
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds no extra behavioral context beyond stating the read operation.

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?

Single sentence, no redundancy, direct statement of purpose.

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?

Simple tool with full annotations and output schema; description is adequate. Could optionally mention return format, but output schema covers that.

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% with clear parameter descriptions. Description adds no additional meaning beyond what schema provides.

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?

Description uses specific verb 'Fetch' and resource 'text of one article of a law'. Clearly distinguishes from siblings like jp_get_full_text which fetches entire law text, and search tools.

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?

No explicit when/when-not guidance in description. Context from sibling names provides implicit differentiation, but description lacks direct usage instructions.

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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