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sugukurukabe

japan-real-estate-intel

不動産マクロスナップショット

get_real_estate_macro_snapshot
Read-only

View Japan real estate macro snapshot: land price year-over-year, transaction counts, and population decline to 2050. Optionally includes construction starts and policy rate proxy.

Instructions

One-screen macro view: land price YoY (median ㎡/year), transaction counts (last 3y), population decline to 2050; optional e-Stat building construction starts by prefecture (needs ESTAT_APP_ID) and FRED policy-rate proxy CSV. | 地価中央値YoY・取引件数・2050人口減、e-Stat建築着工・FRED短期金利プロキシを一枚に。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
areaNoOptional city filter (e.g. '名古屋市中区') | 市区町村で絞り込み
prefectureNo都道府県名(和名/英名/ISO 3166-2 コード対応)愛知県
includeExternalSeriesNoIf true, fetch construction starts (e-Stat, needs ESTAT_APP_ID) and policy-rate proxy (FRED CSV, no key). | e-Stat着工・FRED金利系列を併記
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the tool is safe. The description usefully adds that optional external series require an ESTAT_APP_ID and mentions FRED CSV requires no key, providing behavior context beyond annotations. However, it omits rate limits or data freshness.

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 concise (two lines, bilingual) and front-loaded with the main outputs (land price, transactions, population). It efficiently conveys the tool's capability without extraneous detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (multiple data sources, optional external series), the description provides essential metrics but does not explain the output format or how to use the external series effectively. Lacks detail on outcomes for a complete understanding.

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%, with each parameter having adequate descriptions (e.g., prefecture accepts Japanese, English, ISO codes). The tool description does not add new semantic information beyond the schema, so baseline score of 3 is appropriate.

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 it provides a 'One-screen macro view' including specific metrics like land price YoY, transaction counts, and population decline. It effectively communicates the tool's purpose, though it does not explicitly differentiate from sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like 'forecast_land_price_trend' or 'compare_prefectures'. It implies usage for a quick overview but does not state prerequisites or exclude scenarios.

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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