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不動産マクロスナップショット

get_real_estate_macro_snapshot
Read-only

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

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about external data dependencies: e-Stat requires ESTAT_APP_ID and FRED uses a CSV. This is beyond the annotations, but it does not disclose what happens if the key is missing or how failures are handled. Adequate but not rich.

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 a single, dense sentence with a bilingual summary, front-loading the core output. It is efficient and to the point, though the pipe-separated structure and bilingual text add slight noise. Overall, it is well-structured and earns its place.

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?

For a read-only tool with no output schema, the description covers the main returned data series and the optional external requirements. Missing are details about output format, fallback behavior if ESTAT_APP_ID is absent, or network dependencies. Given the tool aggregates multiple sources, a bit more context would help, but it is minimally adequate.

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?

The input schema covers all parameters with clear descriptions (100% coverage), including the includeExternalSeries flag with the same ESTAT_APP_ID note. The description repeats some of this but adds no new meaning about parameters. Given high schema coverage, the baseline of 3 is appropriate; the description does not need to compensate.

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 the tool's purpose: providing a one-screen macro view of multiple real estate indicators (land price YoY, transaction counts, population decline, optional external series). It names specific data points, making it distinct from more specialized tools like get_population_outlook. However, it does not explicitly differentiate from all siblings, so it is clear but not maximally distinct.

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

Usage Guidelines3/5

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

The phrase 'One-screen macro view' implies this is for a high-level overview scenario, and the optional external series section hints at when to include the flag. However, there is no explicit 'when to use vs. alternatives' statement, nor exclusions. Usage guidance remains implicit rather than explicit, so it meets the 'implied usage' level.

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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