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시군구 수급 균형 — 입주 예정 대 세대 증가

realty_supply_demand_balance
Read-onlyIdempotent

시군구마다 앞으로 들어올 아파트와 늘어나는 세대를 같은 창으로 나눠 수급을 판정한다.

"○○ 공급 과잉이야?", "세종 대전 서울 경기 수급", "어디가 입주 대비 수요가 많아?"류 질문의
자리 — 입주(청약홈 공고, 향후 N개월)를 연 단위로 환산해 최근 12개월 세대 증가로 나눈
**비율**과 판정(과잉 >1.5 · 공급 우위 1~1.5 · 균형 0.5~1 · 부족 <0.5 · 세대 감소 중)을 주고,
같은 행에 교차검증 신호(순이동·매매 거래량 증감·전세/월세 증감과 월세 비중·1순위 경쟁률·
낙찰가율·미분양)를 싣는다. 판정과 신호가 엇갈리면 `conflict`에 적는다.

**결론에 반드시 옮길 것**:
· 입주는 **하한**이다 — 정비사업 조합원분이 공고에 없어 서울처럼 재건축 비중이 큰 곳은
  '부족'이 실제보다 과장된다. `meta.disclosures`를 그대로 전하라.
· `permit_pipeline_households`(사업승인 기준)는 **입주에 더하지 마라**(이중계상).
· `denominator_unstable=true`면 비율이 분모 탓에 흔들린다 — 배수를 단정하지 마라.
· 판정 구간은 **우리 규칙**이지 공식 기준이 아니다. 호가 매물·비아파트는 데이터에 없다.
· 지표마다 기준 시점이 다르다 — `meta.series_as_of`로 밝혀라.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
regionYes시도(예: '경기', '서울', '세종') 또는 시군구(예: '평택시', '서울 강남구'). 시도를 주면 소속 시군구 표 + 시도 합계, 시군구를 주면 그 행 + 시도 합계. 동명 시군구('중구')는 시도를 붙여라 — 안 붙이면 후보를 돌려준다. '광주'는 광역시·경기 광주시가 갈려 '광주광역시' 또는 '광주시'로 줘라
horizon_monthsNo입주를 **다음 달부터 몇 개월** 볼지(기본 24). 비율은 이 창을 연 단위로 환산해 12개월 세대 증가와 나눈다. 30개월을 넘기면 뒤쪽은 아직 공고 전이라 과소로 나온다 (허용 범위 6~60)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare read-only and idempotent, but the description adds rich behavioral context beyond them: how the ratio is annualized, what verdict thresholds mean, the conflict signal reconciliation, meta.disclosures requirements, and explicit data limitations (호가 매물, 비아파트, 기준 시점 차이). No contradiction with annotations.

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 long, but every sentence earns its place given the analytical complexity. It opens with the core purpose, then systematically lists mandated caveats. Slightly verbose, but not padded; the structure is logical and front-loaded with the verdict categories before the detailed warnings.

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 two-parameter read-only analytical tool with no output schema, the description covers what data is returned (ratio, verdict, signals, conflict), how to interpret each verdict, critical caveats that must be passed to the final answer, and meta information (disclosures, series_as_of, denominator_unstable). An agent has everything needed to call it and interpret results correctly.

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%, so the baseline is 3. The parameter descriptions in the schema already explain region disambiguation and horizon over-estimation. The main description adds calculation context (annualized ratio divided by 12-month household increase) but does not substantially enhance parameter-level semantics beyond what the schema already provides.

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 states a specific verb (판정한다), a clear resource (시군구별 입주 예정 대 세대 증가 수급), and the exact output (비율, 판정 구간, 교차검증 신호). It explicitly answers targeted question types and references a conflict field, making it readily distinguishable from sibling tools like realty_supply_pipeline or realty_move_in_supply.

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?

The '결론에 반드시 옮길 것' section provides explicit interpretive rules: treat 입주 as a floor, do not add permit_pipeline_households, avoid definitive statements when denominator_unstable, and clarify series_as_of. It also includes regional input disambiguation (중구, 광주) in the parameter description. This goes well beyond implied usage and gives clear do/don't guidance.

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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