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독립유공자 공훈록 MCP 서버 (Korean Independence Patriots Records)

by MCP-Mirror

get_public_report

Retrieve official merit records of Korean independence patriots by searching with criteria like name, birth date, honor grade, or movement affiliation.

Instructions

독립유공자 공적조서를 조회합니다

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
page_indexNo페이지 번호
count_per_pageNo페이지 당 데이터 건수 (최대 50건)
mng_noNo관리번호
name_koNo성명(한글)
name_chNo성명(한자)
diff_nameNo이명
birthdayNo생년월일 (YYYYMMDD, 년(1945), 년월(194501), 년월일(19450101))
lastdayNo사망년월일 (YYYYMMDD, 년(1945), 년월(194501), 년월일(19450101))
sexNo성별 (0: 여, 1: 남)
register_large_divNo본적대분류
register_mid_divNo본적중분류
judge_yearNo포상년도
hunkukNo훈격
workout_affilNo운동계열
achivementNo공적개요
achivement_koNo공적개요 국한문병기
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the retrieval action without mentioning pagination behavior (implied by page_index/count_per_page), rate limits, authentication requirements, error conditions, or what format the results return. For a 16-parameter query tool with no output schema, this leaves significant behavioral gaps.

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 a single, efficient sentence in Korean that directly states the tool's core function. There's zero wasted language or redundancy. It's appropriately sized for a retrieval tool, though the brevity comes at the cost of completeness in other dimensions.

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

Completeness2/5

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

Given the complexity (16 parameters, no output schema, no annotations), the description is insufficiently complete. It doesn't explain what kind of data structure returns, how pagination works with the page parameters, whether all parameters are optional filters, or how this differs from sibling tools. For a query tool with rich filtering options, more context is needed.

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 all 16 parameters well-documented in the schema itself. The description adds no additional parameter information beyond what's already in the schema descriptions. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't provide any contextual framing about how parameters interact or which combinations are most useful.

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's purpose as '조회합니다' (retrieves/views) for '독립유공자 공적조서' (merit records of independence activists). It specifies the resource type but doesn't distinguish it from sibling tools like 'get_merit_list' which likely serves a similar purpose. The verb+resource combination is specific but lacks sibling differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. There's no mention of when to choose this over 'get_merit_list' or other sibling tools, nor any context about prerequisites, filtering capabilities, or appropriate use cases. The agent must infer usage from the parameter schema alone.

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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