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korea-realty

by app.sallim

아파트 단지 검색·평형별 시세

realty_search_complexes
Read-onlyIdempotent

아파트 단지를 이름·지역으로 검색하고 평형별 실거래 시세를 함께 돌려준다. "○○아파트 34평 얼마야"류 단지 질문의 1차 도구다. query·region 중 하나는 필수.

**이 축의 자리(시세 도구 3종 중)**: 단지가 특정되면 **이게 기본**이다. 지역 평균
도구들(realty_region_price_stats·realty_area_price_bands)은 단지 간 편차를 뭉개므로
단지 질문에 쓰지 마라 — 같은 동 같은 평형에서 단지 평균이 24% 벌어진 실측이 있다
(동 평균 3.96억으로 답했다가 대장 단지 호가와 1억 어긋난 사고). 반대로 지역 전체의
수준·추이 질문이면 저 둘로 가라.

prices_by_area가 평형별 시세다 — pyeong_exclusive(전용평)와 pyeong_supply_est(분양평
어림)를 병기하므로, 사용자가 말한 "34평"(보통 분양평)은 pyeong_supply_est로 맞춰 답하라.
단지 수준 avg_price는 전 평형이 섞인 평균이니 평수 질문에 쓰지 말 것.
층별(저층/고층/RR) 시세·프리미엄 질문은 realty_complex_pyeong_price로 —
거기 층 밴드별 집계(price_by_floor_band)가 있다(이 도구엔 층 축이 없다).
응답의 complex_key는 realty_complex_rent_by_pyeong·[유료] 단지 도구들에 그대로 넣는 키다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo0부터 시작하는 페이지 번호
sortNoname=이름순(거래량 많은 순), price=평균가 **높은** 순, year=준공연도 **최신순(내림차순 — 신축이 먼저)**. ⚠️ **오래된 순 정렬은 이 도구에 없다** — '오래된 단지'·'재건축 후보'를 찾는 조회에 sort='year'를 쓰면 정확히 반대 결과가 온다(정비사업 축은 realty_reconstruction·realty_redevelopment)name
limitNo단지 수 — 평형별 시세가 포함돼 응답이 무겁다. 최대 20이고 더 받으려면 limit을 올리지 말고 **page를 넘겨** 이어 받아라(응답의 total이 전체 건수다). 요청분을 다 실으면 응답이 크기 상한을 넘는 경우 **실제 반환 수를 줄이고 meta.size_capped**에 총계·이어받는 호출을 값으로 싣는다 — 조용히 자르지 않는다 (허용 범위 1~20)
queryNo단지명 일부 (예: 래미안, 마포래미안푸르지오)
regionNo시군구명 (예: 마포구, 서울특별시 마포구). **법정동까지 넣어도 된다**(예: '강남구 대치동') — 백엔드는 동으로 거르고 나머지 토큰은 서버가 검증해 note에 적는다. 종전 설명이 시군구만 적어 **이 도구가 못 하는 일로 읽혔고**, 동 단위를 원한 모델이 비아파트 도구로 새던 자리다(2026-08-23 PlayMCP QA)
period_monthsNo가격 집계 기간(개월). 비우면 2024-01 이후 전체 (허용 범위 1~24)

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/idempotent/non-destructive, and the description adds substantial behavioral context beyond that: pyeong_supply_est vs pyeong_exclusive semantics, avg_price being mixed across pyeong types, size_capped partial responses, and how complex_key connects to other tools. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Dense but well-structured: opens with the core function, uses bold labels and bullets, and each sentence carries routing or behavioral value. No filler or repetition of schema content beyond what is useful.

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 search tool inside a large sibling family, the description covers primary use, exclusions, parameter constraints, response-field semantics, pagination/size_capping behavior, and downstream key usage. Nothing an agent needs to select and invoke this tool confidently is missing.

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. The description adds the important constraint that query or region is required and clarifies how region can include legal dong, plus how sort 'year' should not be used for old-complex queries. Most parameter detail, however, already lives in the schema.

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?

States a specific verb and resource: searching apartment complexes by name/region and returning pyeong-level transaction prices. Explicitly positions itself as the 'primary tool' for complex-specific questions and distinguishes it from regional-average siblings.

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?

Gives direct when-to-use guidance: use for complex-specific price questions, not for regional averages; names alternatives (realty_region_price_stats, realty_area_price_bands) and floor-price sibling (realty_complex_pyeong_price). Also warns against using the wrong sort semantics for 'old complex' searches.

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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TDQS

A3.9/5.0
Disambiguation3/5

The set has very explicit cross-tool guidance and each tool is often given a specific 'role', but there are still many overlapping clusters: auction search vs auction list vs auction detail, regional price bands vs price stats vs rankings, and court auction rate vs public auction rate. The descriptions reduce misselection, but with 51 tools including pairs like `fetch` and `realty_get_auction_case`, confusion is still likely for an agent.

Naming Consistency4/5

Most tools follow a clean `realty_` prefix and use consistent snake_case noun-phrases or verb-noun patterns, e.g. `realty_search_auctions`, `realty_get_auction_case`, `realty_presale_cost`. The exceptions are the generic `fetch`, `search`, and `report_issue`, which break the uniform prefixed convention but are only a small minor deviation from an otherwise consistent naming system.

Tool Count1/5

51 tools far exceeds the recommended threshold, even for a deliberately broad real-estate area; it is effectively an extreme number for a single MCP server. The tool count becomes the hardest usability problem, since agents must handle many tightly related micro-tools instead of interacting with a smaller, more manageable surface.

Completeness5/5

The tool set covers an impressively complete range: auction and public-auction workflows, apartment and non-apartment market, presale/cheongyak processes, tax and loan rules, subscription scoring, redevelopment, demographics, supply, POI, and even a reporting and routing tool. Boundaries and unsupported cases are explicitly documented, so there are no major obvious dead ends.

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