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Æfact — Korean fact desk for AI agents

바뀌는 제도

what_changes
Read-onlyIdempotent

언제부터 무엇이 바뀌나. 기간(from~to)·분야·검색어로 시행되는(또는 막 시행된) 한국 법령 변경을 찾습니다. 결과마다 시행일, 법령명, 바뀌는 문구, 개정이유 첫 문장(법제처 원문 그대로)이 있습니다. 자세한 원문은 get_change. EN: What Korean laws/regulations change between dates (effective dates from the Ministry of Government Legislation), with verbatim reasons and changed wording.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNo끝일 YYYY-MM-DD (기본: 30일 뒤)
fromNo시작일 YYYY-MM-DD (기본: 오늘)
limitNo
queryNo예: 전세, 근로자, 건강보험, 육아휴직
topicNo분야(일·노동, 복지·건강, 세금·금융·경제, 주거·교통, 교육·가족, 안전·행정·사법, 환경·에너지, 농어업, 문화·관광, 과학·디지털, 국방·외교·보훈)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so safety is covered. The description adds genuinely useful behavioral context the annotations do not: each result carries the effective date, statute name, changed wording, and the verbatim first sentence of the amendment reason from the Ministry of Government Legislation's original text.

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?

Front-loaded with the core question ('언제부터 무엇이 바뀌나') followed by scope, result contents, and the sibling pointer. The Korean/English duplication adds length but serves non-Korean agents; nearly every sentence 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 no output schema, the description compensates by enumerating the returned fields (effective date, statute name, changed wording, verbatim amendment reason). An agent knows what it will get and where to go for full text; only pagination/limit behavior is left unstated.

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 80%, so most parameters are already documented in the schema. The description restates the filter triad (period from~to, topic, query) but adds no syntax or default detail beyond what the schema provides, and does not mention limit at all — baseline 3 is appropriate.

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+resource: finding Korean legal/regulatory changes effective within a date range, scoped by topic and keyword. It also names the sibling that returns the full text (get_change), so an agent can distinguish it from the other retrieval tools without opening schemas.

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?

The description frames usage well ('기간(from~to)·분야·검색어로 시행되는(또는 막 시행된) 한국 법령 변경을 찾습니다') and routes to get_change for full text. It lacks explicit when-not conditions (e.g. for historical amendments outside effective-date windows), so it stops short of a 5.

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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