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분양가 적정성 분석 — 분양가 vs 주변 실거래 시세

realty_presale_vs_market
Read-onlyIdempotent

청약(분양) 공고의 분양가가 주변 실거래 시세 대비 싼지/비싼지를 주택형별로 계산한다. "이 청약 넣을 만해?", "분양가 적정해?"류 질문의 정량 근거 — 웹검색으로는 못 하는 분양가×실거래 조인 계산이 이 도구의 존재 이유다.

공고 특정: house_manage_no가 없으면 region+keyword로 검색하고, 여러 건이면
후보 목록을 돌려주니 하나를 골라 다시 호출하라(추측해서 고르지 않는다).
기준선: 평형 행의 gap_pct는 gap_basis가 말하는 기준 대비다 — 인근 비교단지가 충분하면
**공고 좌표 반경·준공 연도 조건·같은 평형대 비교군**(nearby_baseline) 대비이고, 아니면
지역(공고 시군구, 없으면 시도) 실거래 평균(구축·외곽 포함, 이상치 미필터) 대비다. 지역 평균 대비 값은
gap_pct_region_avg에 늘 따로 있고, 두 기준선이 크게 갈리면 baseline_divergence가
붙는다 — 그때 지역 평균 대비 수치로 '비싸다'를 말하지 마라. 청약 경쟁률·당첨 가점
커트라인은 realty_subscription_odds에 있다("넣을 만해?"엔 둘을 같이 써라).
지역 수준 교차확인은 realty_area_price_bands(이상치 필터·중앙값)로 하라.
이 도구는 **현재 공고 1건의 적정성**이다 — 같은 지역 공고들의 분양가 시계열
("기다릴수록 얼마씩 올랐나")은 realty_presale_price_trend.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthsNo실거래 비교 창(개월) (허용 범위 3~24)
pyeongNo대조할 전용평(정수)을 직접 고른다 — 예: [26]이면 국민평형 84㎡만. 안 주면 **세대수 많은 순 상위 5개** 평형을 자동으로 고른다. comparison_truncated에 빠졌다고 적힌 평형은 이 인자로 되받아 부르면 된다(공시만 하고 길이 없으면 막다른 골목이다)
regionNo시도 (예: 서울, 경기, 세종)
keywordNo단지명·주소 부분일치 (예: '우미린', '5-2생활권', '다솜동')
house_manage_noNorealty_presale 응답의 공고 관리번호 — 알면 이걸로 특정하는 게 정확

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / pyeong
      Added value: +{
+  "anyOf": [
+    {
+      "items": {
+        "type": "integer"
+      },
+      "type": "array"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "대조할 전용평(정수)을 직접 고른다 — 예: [26]이면 국민평형 84㎡만. 안 주면 **세대수 많은 순 상위 5개** 평형을 자동으로 고른다. comparison_truncated에 빠졌다고 적힌 평형은 이 인자로 되받아 부르면 된다(공시만 하고 길이 없으면 막다른 골목이다)",
+  "title": "Pyeong"
+}
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "realty_presale_vs_marketDictOutput",
-  "type": "object"
-}New value: +null
  3. Changed1 schema field changed
    • changedInput schema / properties / months / description
      Previous value: -"실거래 비교 창(개월)"New value: +"실거래 비교 창(개월) (허용 범위 3~24)"
  4. Added

TDQS

A4.9/5.0
Behavior5/5

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

Beyond readOnly/idempotent annotations, it discloses important behaviors: how announcement lookup falls back to region+keyword when house_manage_no is missing, that multiple candidates are returned and must be disambiguated without guessing, and the exact baseline-selection logic including nearby_baseline vs region-average fallback and baseline_divergence warnings. It also clarifies output fields like gap_pct and gap_pct_region_avg.

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 dense but every sentence carries operational value, and it is well-structured into lookup, baseline, and sibling-routing sections. The core purpose is front-loaded in the first sentence.

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?

With no output schema, the description compensates by naming key fields (gap_pct, gap_basis, nearby_baseline, gap_pct_region_avg, baseline_divergence, comparison_truncated) and explaining ambiguous selection flows. It also covers recommendation behavior and sibling hand-offs, making it complete for a tool of this complexity.

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?

The input schema already provides 100% rich parameter descriptions, so the baseline is 3. The description adds extra value by explaining how house_manage_no relates to region+keyword, the candidate-list rerouting behavior, and the pyeong auto-selection context via comparison_truncated, so it earns a 4.

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+resource: it calculates whether a subscription announcement's presale price is cheap/expensive relative to nearby actual transaction prices, by housing type. It clearly separates itself from siblings such as realty_presale_price_trend, realty_area_price_bands, and realty_subscription_odds.

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?

It explicitly names the user questions it answers ('이 청약 넣을 만해?', '분양가 적정해?') and gives alternatives: realty_subscription_odds for competition/score cutoffs, realty_area_price_bands for region-level cross-checking, and realty_presale_price_trend for time-series patterns. It also warns when not to use region-average numbers.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All korea-realty toolsInspect
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