Skip to main content
Glama
japan-law-util-mcp-server

japan-law-util-mcp-server

by gotoai

read_law_text

Read-only

Read Japanese law text as plain text, either the whole law or a specified element such as an article or chapter. Retrieve results in chunks and continue from the returned offset.

Instructions

Read a law's text as plain text: the whole law, or the one part elm names, such as MainProvision-Article_17, MainProvision-Chapter_4-Section_2, SupplProvision[1]-Article_1 or AppdxTable[1]. The text comes back in pieces of max_chars; continue from next_offset. The law's 目次 is not included — get_law_outline returns it — and the supplementary provisions of amending laws are left out unless include_amendment_supplements is true.

Input Schema

NameRequiredDescriptionDefault
elmNoElement path from get_law_outline.
asofNoYYYY-MM-DD; the text in force then.
offsetNoCharacter offset to read from.
max_charsNo
law_id_or_numYesLaw id, law number or revision id.
include_amendment_supplementsNoInclude the amending laws' supplementary provisions.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Adds real behavior beyond the readOnlyHint/openWorldHint annotations: output is paginated into max_chars chunks resumed via next_offset, the 目次 is deliberately omitted, and amendment supplementary provisions are excluded by default. It does not cover failure behavior (invalid elm, unknown law id) or how asof interacts with missing revisions.

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?

Three dense sentences, front-loaded with the capability and followed by exclusions, with no filler. The parenthetical list of elm examples is long but earns its place; the Japanese term 目次 is the only mild readability cost.

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?

With annotations and an output schema supplied, the description covers the parts an agent most needs: element addressing, pagination continuation, and default exclusions. Remaining gaps are minor (error cases, asof edge behavior) and partly absorbed by schema descriptions.

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 already 83%, so the baseline is 3; the description goes further by giving concrete elm path shapes (MainProvision-Article_17, MainProvision-Chapter_4-Section_2, SupplProvision[1]-Article_1, AppdxTable[1]) and by explaining how max_chars and offset compose into a continuation loop. asof is left entirely to the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Read a law's text as plain text') and clarifies the two modes: the whole law or a single element. It explicitly separates itself from get_law_outline for the 目次, but says nothing to distinguish it from search_law_text, so sibling differentiation is only partial.

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 clear routing guidance: use get_law_outline to obtain the 目次, and set include_amendment_supplements=true when amending-law supplementary provisions are wanted. It does not state when to prefer this over search_law_text or load_guideline, so the when-not side is incomplete.

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