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sugukurukabe

japan-real-estate-intel

ChatGPTビジュアル要約

quick_visual_summary
Read-only

Generate a real estate visual summary with maps, charts, and recommended next actions, formatted for ChatGPT.

Instructions

Render a ChatGPT-optimized real estate visual summary with map, charts, recommended next actions, and compact markdown fallback. Always use this when the user asks to show, visualize, compare, or continue in ChatGPT. | ChatGPT向けに地図・グラフ・次アクション・要約をまとめて表示するレンダーツール。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prefectureNo都道府県名(和名/英名/ISO 3166-2 コード対応)愛知県
areaNoTarget area to focus the visual summary on | 表示対象エリア
intentNoUser goal for choosing the best visual starting point | 表示目的overview
modeNoDashboard mode | ダッシュボード表示モード2d
compactNoOptimize copy and layout for ChatGPT mobile/compact views

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
summaryYes
prefectureYes
areaYes
intentYes
dashboardUriYesMCP Apps ui:// resource URI
dashboardUrlYesBrowser fallback URL or path
layerYes
modeYes
nextActionsYes
markdownReportYesCompact markdown fallback for non-UI clients
attributionYes
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description does not need to repeat these. The description adds value by mentioning the tool's output components (map, charts, next actions) and the compact markdown fallback, providing additional behavioral 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 remarkably concise: two sentences in English and one in Japanese. It front-loads the primary purpose and usage in the first sentence, with every sentence earning its place. No superfluous content.

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 presence of an output schema and annotations, the description sufficiently covers the tool's role (visual summary), components, and fallback behavior. The sibling tools list provides context for alternatives, but the description itself is complete for this tool's purpose.

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 detailed parameter descriptions (e.g., prefecture, intent enum). The tool description does not add new meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 renders a real estate visual summary with map, charts, recommended next actions, and compact markdown fallback. It specifies the verb 'Render' and the resource 'visual summary', distinguishing it from sibling tools that are analytical in nature.

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?

The description explicitly states 'Always use this when the user asks to show, visualize, compare, or continue in ChatGPT.' This provides direct guidance on when to use this tool versus alternatives, which are listed as sibling tools with specific analytical purposes.

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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