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find_article

Read-onlyIdempotent

Locate Korean tax statute articles by keyword when the article number is unknown. Use issue keywords as a first step to find relevant provisions.

Instructions

Find statute articles by keyword — first step when you don't know the article number. 키워드로 조문 위치를 찾는다.

언제: 쟁점 키워드는 있는데 조문 번호를 모를 때 first step. 예: '압류금지 생계비계좌' → 국세징수법 제41조. 반환: [{법령, 조, 제목, 적용 시행일, 일치 문장: 키워드가 든 문장 1~2개(각 200자 이내)}], 다음 단계: law_article(law_name, 조, keyword=...)로 해당 항만 조회. 결과 길이 4,000자 이내. 읽기 전용. 법제처 공식 API — LAW_OC 필요, 없으면 오류.

Input Schema

NameRequiredDescriptionDefault
nNo반환 건수(1~20)
langNoOutput language. 'en': English keys and labels, official English texts where available (tax treaties, statutes), other Korean texts returned with a host_ai_translate instruction (your AI translates); Solar machine translation only when UPSTAGE_API_KEY or on-prem Solar is configured. 기본 'ko'ko
as_ofNo기준일 YYYYMMDD. 생략하면 오늘
keywordYes찾을 키워드(공백으로 여러 단어). 예: '압류금지 생계비계좌'
law_nameNo법령명(정식 명칭). 생략하면 주요 세법 전부(국세기본법·징수법·소득세법·법인세법·부가가치세법·상속세및증여세법·조세특례제한법·국제조세조정법 + 각 시행령)에서 조회

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.9.1

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent/open-world safety, and the description goes further with genuinely new operational facts: an authentication requirement (LAW_OC needed, otherwise error) and a hard output cap of 4,000 characters. It also sketches the return record shape, which matters because no output schema exists.

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 purpose, then cleanly labeled sections (언제 / 반환 / 다음 단계) that a scanning agent can parse. The English and Korean halves restate each other, so some text is duplicative rather than additive, which keeps it short of a 5.

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 5-parameter search tool with no output schema, the description supplies everything an agent needs: trigger condition, example query, return field list, result-size ceiling, auth prerequisite, and the next tool to call. Nothing required to invoke it correctly is missing.

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

Parameters5/5

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

Schema description coverage is 100%, so the schema already documents n, lang, as_of, keyword, and law_name (including the default search scope). The description adds only a usage example for keyword and the shape of the law_article follow-up call, so the baseline of 3 is the right level.

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 ('Find statute articles by keyword') plus the scope of the lookup. It explicitly positions itself against the sibling law_article by stage ('first step when you don't know the article number'), so an agent can tell which tool to reach for without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit trigger condition ('쟁점 키워드는 있는데 조문 번호를 모를 때'), a concrete example mapping a keyword to a statute article, and the follow-up step with the exact tool and arguments ('law_article(law_name, 조, keyword=...)'). When-to-use and the alternative are both spelled out.

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