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korea-realty

by app.sallim

[유료] 시장 신호 (미분양·심리지수)

realty_market_signals
Read-onlyIdempotent

[유료] 미분양 추이와 시장심리지수를 한 번에 조회한다. 매수 타이밍 판단의 거시 신호.

기본 창은 **6개월**이다(방향 판단에 필요한 최소). 더 긴 추이가 필요하면 months를
올리되, 전국 조회에서 창을 넓히면 오래된 달부터 예산에 맞춰 떨어지고 그 사실이
meta.truncated·meta.truncated_note에 값으로 실린다 — region을 지정하면 전 창이 온다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthsNo시계열 개월 수 (기본 6). 전국(region 미지정)에서 창을 넓히면 시도 18곳×월 행이 곱으로 늘어 응답이 도구 결과 한계에 걸린다 — 긴 창이 필요하면 region으로 지역을 좁혀라 (허용 범위 1~36)
regionNo지역명 (예: 서울). 비우면 전국

TDQS

A4.3/5.0
Behavior5/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, and the description adds non-obvious behavior: widening the window in a nationwide query causes older months to be trimmed to fit a budget, with the fact surfaced via meta.truncated and meta.truncated_note. This is meaningful context beyond the 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?

The description is compact and front-loaded, opening with the purpose and paid indicator, then explaining the default window and the critical truncation behavior. Every sentence conveys essential information without filler, and the trailing context is structured clearly.

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?

For a read-only two-parameter tool with no output schema, the description covers the key context: what is returned, default behavior, when to increase the window, and how truncation is reported. It does not fully describe the response shape beyond the meta fields, but this is sufficient for the tool's simplicity.

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 parameters are already documented. The description nevertheless adds semantics: it explains why months interacts with a nationwide query, the multiplication of rows across an 18-region grid, the truncation limit, and how specifying region avoids it. That's a clear value-add beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb and resource: it 'queries' unsold housing trends and market sentiment index at once, positioning itself as a macro signal for buy timing. It is specific enough to be distinguished from most sibling tools, but it does not explicitly differentiate itself from a named alternative, so it stops short of a 5.

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 gives clear usage context: default 6-month window, when to increase months, and the truncation trade-off for nationwide queries. It does not explicitly say when to prefer this tool over alternatives, so it misses the highest bar, but it provides solid situational guidance.

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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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