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korea-realty

by app.sallim

모집공고 팩트시트 — 전매제한·자격·층별 분양가·옵션가·중도금

realty_notice_facts
Read-onlyIdempotent

입주자모집공고 원문에서 추출·검증한 팩트시트 — 전매제한·재당첨제한·거주의무· 거주요건, 청약 일정, 층별 분양가표(대지비·건축비·회차별 납부액), 특별공급 배정, 발코니 확장·유상옵션 가격, 중도금 회차 일정, 예비입주자 규칙.

전매제한 기간, 재당첨 제한, 거주의무, 특별공급 자격·배정, 층/타입별 분양가,
발코니 확장비·유상옵션 금액, 중도금 회차와 납부일 — 이 값들을 묻는 질문이 이 도구의
자리다(추정하거나 웹에서 찾을 필요 없이 공고 원문 값이 나온다). 모든 값에 공고 쪽
번호(`p`)가 붙으니 답변에 notice_version(공고 판본)과 쪽 번호를 함께 제시하라.

팩트시트 미추출 공고는 원문 앞쪽(단지 주요정보 표) 텍스트를 unverified_source_text로
준다 — 수치 인용 시 "공고 원문 기준·미검증"을 명시하라. 상세 조항 전문(특공 소득기준,
부적격 처리 등)은 realty_notice_text로 원문 쪽을 직접 읽어라. 여기 없는 값은 지어내지 말 것.

⚠️ 큰 공고는 팩트시트 전체가 도구 결과 한계(64KiB)를 넘는다. 그때 **큰 절부터 떼어**
보내고 `meta.truncated`·`meta.omitted_sections`(절 이름·크기·되부르는 인자)에 그 사실을
적는다 — 뗀 절은 `section='분양가'`처럼 이름을 지정해 전문으로 받아라. **팩트시트에
없다고 공고에 없다고 답하지 마라**(못 봄 ≠ 없음).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordNo단지명 일부 (예: '우미린' — 공백 무관 매칭)
sectionNo팩트시트의 한 절만 전문으로 받는다 (예: '분양가', '공급'). 비우면 전체 — 다만 전체가 도구 결과 한계를 넘으면 큰 절부터 떼어 내고 뗀 절 이름을 meta.omitted_sections에 적는다. 그때 이 인자로 되받아라.
house_manage_noNo공고 관리번호 (realty_presale 응답의 house_manage_no)

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, it discloses p-page citations, notice_version, the unverified_source_text fallback, the 64KiB truncation limit, meta.truncated and meta.omitted_sections behavior, and the '못 봄 ≠ 없음' semantic. This is rich, non-obvious behavior that an agent needs before calling.

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 organized into tool scope, alternate/full-text fallback, risk warning, and truncation semantics, with the most important definition first. It is long but mostly each section earns its place; however, the first and second paragraphs repeat a similar list of fact categories, adding slight redundance.

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?

Despite having no output schema, the description covers the necessary usage context: how to cite results (notice_version, p), how to handle unextracted notices, what to do when results exceed the tool limit, and how to recover omitted portions. That is complete for a read-only, idempotent lookup tool.

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 schema already documents keyword, section, and house_manage_no. The description adds workflow guidance around the truncation case but does not materially add parameter-level meaning beyond the schema, which is the baseline 3 case.

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 names a concrete resource (입주자모집공고 원문) and a concrete operation (추출·검증한 팩트시트), then enumerates the exact fact categories. It also distinguishes itself from realty_notice_text by stating that full provisions belong to that tool, so an agent can tell them apart.

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 says these fact-value questions are the tool's place, that the agent need not estimate or web-search, and that unextracted notices return unverified_source_text. It also gives an explicit alternative: read full clauses via realty_notice_text, and warns not to claim a fact is absent just because it is absent from the fact sheet.

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.

Resources