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tae0y

Korea Real Estate MCP

by tae0y

get_apartment_trades

Retrieve apartment sale records and summary statistics including median, min, and max prices for a specific region and month.

Instructions

Return apartment sale records and summary statistics for a region and month.

Korean keywords: 아파트

Use summary.median_price_10k as the reference price and
min/max_price_10k to present the price range.

To compute jeonse ratio, call get_apartment_rent for the same region and
month, then divide rent summary.median_deposit_10k by this
summary.median_price_10k.

region_code must be obtained first via the get_region_code tool.

Query strategy:
- For price trend analysis, call this tool for each of the 6 consecutive
  months preceding the current month.
- To check year-over-year changes, also query the same month across
  3 years (e.g. 202412, 202312, 202212).

Args:
    region_code: 5-digit legal district code (returned by get_region_code).
    year_month: Target year-month in YYYYMM format (e.g. "202501").
        Call get_current_year_month if not specified by the user.
    num_of_rows: Maximum number of records to return. Default 100.

Returns:
    total_count: Total record count from the API
    items: Trade list (apt_name, dong, area_sqm, floor,
           price_10k, trade_date, build_year, deal_type)
    summary: median/min/max price_10k, sample_count
    error/message: Present on API error or network failure

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
year_monthYes
num_of_rowsNo
region_codeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries full burden. It describes the return structure and possible error conditions, but does not explicitly state that the operation is read-only or disclose rate limits or authentication needs. However, the read nature is implied through the language of 'return' and 'summary'.

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 well-structured with clear sections, but slightly verbose. It front-loads the core purpose and adds valuable usage tips. Every sentence serves a purpose, but could be tightened slightly without losing information.

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?

Given the tool's moderate complexity, the description fully covers purpose, parameters, usage patterns, and expected output. It even provides query strategies for common analyses. The output schema is described, so the agent knows what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description has a detailed 'Args' section that explains each parameter's purpose, format, and default behavior (e.g., year_month in YYYYMM, hint to use get_current_year_month, num_of_rows default 100). This adds significant meaning beyond the bare 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?

The description clearly states it returns apartment sale records and summary statistics for a region and month, with specific verbs and resource. It distinguishes from sibling tools like get_apartment_rent and get_officetel_trades by focusing on trades.

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?

Provides explicit guidance on using summary.median_price_10k as reference price, how to compute jeonse ratio via get_apartment_rent, query strategies for trend analysis and year-over-year changes, and prerequisite to call get_region_code first.

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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