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socialkim

korea-onegov-mcp

by socialkim

기관(부처) 코드 목록

onegov_list_ministries
Read-onlyIdempotent

Retrieve a list of Korean central government ministries with their document counts. Filter by ministry name to obtain the ministry code for use in searches.

Instructions

색인된 중앙행정기관 목록과 각 기관의 보유 문서 수를 돌려준다. onegov_search 의 ministry 필터에 넣을 코드를 여기서 얻는다.

Args:

  • name_contains (string, 선택): 기관명에 포함된 글자로 필터(예: "고용", "국토").

  • response_format ('markdown'|'json', 기본 markdown)

Returns: { ministries: [{ ministry_code, name, org_type, parent_code, doc_count }] } 참고: "_AGGREGATE"는 특정 부처가 아니라 K-Startup 등 집계 포털에서 모은 전 기관 공통 자료다(가장 문서가 많다).

Examples:

  • "국토교통부 코드가 뭐야" → name_contains="국토" → MOLIT

  • "어느 부처 자료가 제일 많아" → 전체 조회

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
name_containsNo기관명 부분 문자열 필터
response_formatNo출력 형식. 'markdown'은 사람이 읽기 좋은 요약(기본값), 'json'은 API 원본에 가까운 구조화 데이터.markdown
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds return structure, note about '_AGGREGATE' being aggregated data, and that the tool is for getting codes, providing valuable context beyond annotations.

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?

The description is concise and well-structured: purpose, args, returns, note, examples. Every sentence adds value with no fluff.

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?

Given the tool's simplicity (2 optional params, no output schema), the description fully covers the return structure, special cases like '_AGGREGATE', and provides examples. Annotations cover safety traits.

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 100%, so baseline is 3. The description adds meaning by explaining the name_contains filter with examples and clarifying the response_format options and defaults.

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?

The description clearly states that the tool returns a list of ministries with document counts, specifically for obtaining codes to use in the onegov_search filter. This distinguishes it from siblings like onegov_search or onegov_ministry_latest.

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 explains that the tool provides codes for the ministry filter in onegov_search, with examples. While it lacks explicit when-not-to-use guidance, the context is clear and the examples help.

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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