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seunguk3

local-tax-mcp

by seunguk3

get_operation_ruling

Retrieve Korean local tax operational rulings by article number or keyword. Use reverse-index lookup to get all rulings for a specific provision, providing current authoritative guidance.

Instructions

행정안전부 「지방세관계법 운영 예규」 조회. 국세의 기본통칙에 대응한다. jo(조문번호)로 역인덱스 조회가 가능해 '지방세법 제106조 관련 예규 전부'를 한 번에 뽑는다. NTS의 지방세 기본통칙은 2018년판이라 stale하므로 이쪽을 정본으로 쓴다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
joNo법 조문번호 필터. 예: 제106조
ocNo
limitNo최대 항목 수 (기본 20)
queryNo제목·본문 키워드
lawNameNo장(章) 기준 법령명 필터. 예: 지방세법
Behavior3/5

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

With no annotations provided, the description carries the transparency burden. It reveals a key behavioral trait: reverse index lookup by jo allows pulling all relevant rulings for an article at once. It also frames the tool as more current than NTS. But it doesn't mention response format, pagination behavior, authentication needs, or any side effects. This is adequate but leaves gaps.

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?

The description is four sentences, each serving a distinct purpose: resource identification, functional equivalence, key feature, and usage guidance. It is dense but not wordy. No fluff, though it could arguably be tightened by merging the NTS comparison into a single clause.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a query tool with 5 parameters and no output schema, the description covers the core purpose, a distinctive capability, and usage preference. It is competent but not exhaustive: it doesn't describe return values, error conditions, or the undocumented 'oc' parameter. The schema helps, but the absence of output schema means the description should have filled more gaps.

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 80%, so baseline is 3. The description adds semantic value for 'jo' by explicitly explaining its reverse index capability and giving the '지방세법 제106조' example. However, the 'oc' parameter remains entirely undocumented, and the description doesn't elaborate on 'limit' or 'query' beyond their schema descriptions.

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?

The description clearly states the tool queries the Ministry of the Interior's 'Local Tax-Related Law Operation Rules' and mentions the reverse index lookup by article number, which differentiates it from general search tools. It also adds context by relating it to the National Tax Service's basic ruling. However, it doesn't explicitly contrast with sibling tools like search_moi_interpretation, so it's not a full 5.

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 explicitly advises using this tool over the NTS basic ruling because the NTS version is from 2018 and stale, providing clear contextual guidance. It doesn't mention exclusions or alternative sibling tools, but the 'use this as the authoritative version' instruction is a strong usage signal.

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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