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by app.apick

부동산 실거래가 조회

land_rt_price
Read-only

Look up real estate transaction price records in Korea by region, property type, and year. 시/도·시/군/구, 부동산 유형, 년도를 지정해 부동산 실거래 이력을 조회합니다. addr1 값이 잘못되면 응답의 options 필드로 선택 가능한 지역 목록을 안내합니다. [호출당 100포인트]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes유형 코드 A~H 중 하나. A:아파트, B:연립/다세대, C:단독/다가구, D:오피스텔, E:분양/입주권, F:상업/업무용, G:토지, H:공장/창고등
yearYes조회 년도 (1950 ~ 현재 년도, 예: 2025)
addr1Yes도/광역시/특별시 정식 명칭 (예: 서울특별시, 경기도, 부산광역시)
addr2Yes시/군/구 (예: 금천구)

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint. The description adds useful behavioral context: if addr1 is invalid, the response includes an options field with a list of selectable regions, and each call costs 100 points. This goes beyond the annotations without contradicting them.

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 relatively compact, with the English and Korean versions covering similar ground. It includes essential extras (error handling, cost) without excessive fluff. Minor duplication between languages prevents a perfect score.

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?

The tool has 4 required parameters and no output schema, but the description adequately explains the lookup purpose, the error-handling mechanism, and the cost. It does not detail normal response structure, but for a simple read-only lookup, this is sufficient.

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 parameters are already well-documented. The description adds a small but useful note about addr1 error behavior, but does not systematically elaborate on each parameter beyond what the schema 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 clearly states a specific verb ('Look up') and resource ('real estate transaction price records in Korea') with the key dimensions (region, property type, year). It is distinct from all sibling tools, none of which deal with real estate prices.

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 description provides clear context for when to use the tool (Korean real estate transaction lookups) and even includes an error-handling hint about addr1 guiding the user to valid regions. It does not explicitly mention alternatives, but there are no close sibling tools to distinguish from.

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

A3.6/5.0
Disambiguation4/5

Most tools have clearly distinct purposes; even within families like identi_card1-5 vs identi_card_image1-5, the text-input vs image-input distinction is clear. However, the sheer number of tools and some near-synonyms (e.g., ocr_identi1 vs identi_card_image1) could cause occasional misselection, but descriptions mitigate this.

Naming Consistency3/5

Naming follows a loose verb-first pattern (check_, crawl_, download_, draw_, etc.) but includes significant deviations: bare nouns (bank_code, location, whois), numbered variants (identi_card1, identi_card_image1), and mixed prefixes (ocr_, identity_, etc.). The inconsistency is noticeable but still readable and predictable within functional clusters.

Tool Count3/5

80 tools is far above the typical 3-15, but the server is a broad API aggregator covering many independent domains (banking, ID verification, media conversion, search, LLM, etc.), so the high count is somewhat justified. Still, the sheer number makes the toolkit feel unwieldy and hard to navigate, placing it at the high end of acceptable.

Completeness4/5

Within its stated purpose as a general-purpose utility API, the toolset covers a wide array of common task families: identity document verification (text and image), OCR field extraction, media conversion, web/search, domain/IP lookup, and LLM chat. Most operations have both get and act variants (e.g., set/get watermark, parcel_tracking/auto), with few obvious dead ends for typical use cases.

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