Skip to main content
Glama

jp_get_full_text

Read-onlyIdempotent

Fetch the complete text of a Japanese law using its law ID. Large laws are truncated to avoid long responses.

Instructions

Fetch the full text of a law by law_id. Large laws are truncated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
law_idYese.g. ``"129AC0000000089"`` (the Civil Code).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
law_idYes
contentNo
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.
byte_sizeNo
truncatedNo
source_urlNo
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
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. Description adds the important behavioral detail that large laws are truncated, which is beyond annotation coverage.

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?

Two sentences, front-loaded with purpose, no superfluous text. Every word earns its place.

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 an output schema present, description need not explain return values. It covers the main nuance (truncation) and leaves parameter details to schema. Adequate for a simple tool.

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 description coverage is 100% with an example value for law_id. Description adds no further parameter meaning beyond the schema.

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?

Clearly states it fetches the full text of a law by law_id, with a key behavioral note on truncation. Distinguishes from siblings like jp_get_article (single article) 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?

Implied usage for fetching full text, but lacks explicit when-not-to-use or comparisons with sibling tools. The truncation note is helpful but not a full guideline.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/matematicsolutions/jp-eli-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server