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korea-realty

by app.sallim
OverviewDiscussionsAdmin

인구통계 (인구·가구·연령·인구이동)

realty_demographics
Read-onlyIdempotent

지역 인구·가구·고령화·순유입 통계를 조회한다.

지역 인구통계를 조회한다 — "인구 줄고 있어?", "1인 가구 비율은?", "고령화 심해?",
"순유입 되는 동네야?"류 질문용.

응답 meta.data_as_of가 실제 최신 시점이다 — warning이 있으면 그대로 사용자에게 전달하고,
밀린 수치를 "지금 인구"로 단정하지 말 것. 연간 계열(households·age)은 기준연도를 밝혀라.
households는 동명 시군구(중구·서구 등)에 시도를 붙여야 한다('서울특별시 중구') — 원천은 단명으로
적지만 행정코드로 구를 가른다. 시도 없이 '중구'만 주면 후보와 retry를 돌려준다.

Input Schema

NameRequiredDescriptionDefault
metricYespopulation=월별 인구·세대수 / households=연별 가구원수별 가구(1인가구 등) / age=연령대(5세 구간) 분포·고령화 — 시도 단위만 / migration=월별 전입·전출·순이동
monthsNopopulation·migration 시계열 창(개월) — 최대 60(5년)이고 더 긴 창은 이 도구로 못 받는다. 연간 계열엔 미적용 (허용 범위 1~60)
regionYes시도(예: 서울)나 시군구(예: 강남구, 수원시). age는 시도 단위만 제공. age에 한해 '전국'도 가능
include_footnotesNotrue면 계산값 근거 전문(산식·모집단·기간·원천)을 footnotes에 싣는다. 기본은 행마다 한 줄 요지

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / include_footnotes
      Added value: +{
+  "default": false,
+  "description": "true면 계산값 근거 전문(산식·모집단·기간·원천)을 footnotes에 싣는다. 기본은 행마다 한 줄 요지",
+  "title": "Include Footnotes",
+  "type": "boolean"
+}
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "realty_demographicsDictOutput",
-  "type": "object"
-}New value: +null
  3. Changed1 schema field changed
    • changedInput schema / properties / months / description
      Previous value: -"population·migration 시계열 창(개월). 연간 계열엔 미적용"New value: +"population·migration 시계열 창(개월) — 최대 60(5년)이고 더 긴 창은 이 도구로 못 받는다. 연간 계열엔 미적용 (허용 범위 1~60)"
  4. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial behavior beyond them: meta.data_as_of is the true freshness anchor, warnings must be relayed verbatim, stale figures must not be presented as current, annual series need their reference year stated, and ambiguous district names trigger a candidates-plus-retry flow. This is unusually rich operational context.

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 purpose and usage examples are front-loaded and the operational caveats follow logically. There is mild redundancy between the opening line and the second paragraph's restatement of '지역 인구통계를 조회한다', which keeps it from a 5.

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 covers freshness fields (meta.data_as_of), warning handling, annual vs monthly semantics, and the region-naming failure mode, which is enough for an agent to call it correctly. Return-shape detail beyond the timestamps is limited but acceptable for a read-only statistics tool.

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 the baseline is 3, but the description adds real meaning the schema lacks: the province-prefix requirement for same-named districts ('서울특별시 중구') and what happens when it is omitted. It also reinforces the monthly-vs-annual distinction that the months parameter only partially conveys.

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?

States a specific verb and resource domain: regional population, households, aging, and net-inflow statistics, plus concrete example questions that pin the domain. It is clearly distinct from sibling tools like realty_region_price_stats or realty_macro_indicators, but it never names a sibling or explicitly excludes adjacent tools, so it falls short of the top tier.

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 example questions ("인구 줄고 있어?", "1인 가구 비율은?", "순유입 되는 동네야?") give clear usage context and map directly to the metric enum values. There is no explicit when-not guidance or named alternative tool, which keeps it below 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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