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sugukurukabe

japan-real-estate-intel

レバレッジ10年キャッシュフロー試算

simulate_leveraged_cashflow
Read-only

Run a leveraged 10-year real estate pro-forma: input loan terms, rent, expenses, exit assumptions to get NOI, debt service, after-tax cash flows, DSCR, IRR, equity multiple, and sensitivity.

Instructions

Leveraged 10-year real estate pro-forma: accepts loan interest rate, LTV/loan amount, rent, vacancy, operating costs, property tax, depreciation and exit assumptions, then returns annual NOI, debt service, after-tax cash flow, DSCR, IRR, equity multiple and sensitivity. | 銀行借入の利率・LTV・賃料・空室率・経費・固定資産税・減価償却・出口条件から10年の年次収支、税引後CF、DSCR、IRR、感応度を試算する。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYes市区町村(例: '名古屋市中区', '新宿区')
loanYes銀行借入条件
districtNo町丁目・地区名(任意)
annualRentYes初年度の想定年間賃料収入(円)
prefectureNo都道府県名(和名/英名/ISO 3166-2 コード対応)愛知県
annualCapexNo毎年の資本的支出・大規模修繕積立相当(円/年)
askingPriceYes購入価格・売出価格(円)
assumptionsNo10年収支・税務前提
output_modeNoOutput verbosity. compact=TL;DR + key numbers only (default), detailed=full Markdown report | 出力詳細度。compact=主要数値のみ(デフォルト)、detailed=全文レポート付きcompact
vacancyRateNo初年度の想定空室率(0-1)
propertyTypeNo物件種別mansion
purchaseCostNo仲介手数料・登記費用など初期取得費用(円)
landValueRatioNo土地按分比率。建物減価償却のために使用(0-1)
renovationCostNo初期修繕・リノベーション費用(円)
otherIncomeAnnualNo駐車場・看板等のその他年間収入(円)
propertyTaxAnnualNo固定資産税・都市計画税等(円/年)
operatingExpenseAnnualNo管理費・修繕費・保険料など年間運営費(円)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYes
summaryYes
districtYes
redFlagsYes
prefectureYes
yearlyRowsYes
assumptionsYes
attributionYes
sensitivityYes
summaryKpisYes
dashboardUriYes
markdownReportYes
recommendationsYes
Behavior3/5

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

Annotations already declare readOnlyHint=true, so no contradiction. The description adds no further behavioral context (e.g., that it produces a report without side effects). Adequate but minimal.

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?

Two sentences front-loaded with purpose and inputs, but bilingual repetition slightly reduces efficiency. Still concise and structured.

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?

Given the complexity (17 params, nested objects, output schema), the description covers key outputs and sensitivity. Could mention output structure but not necessary due to output schema.

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 coverage is 100%, so the description adds little beyond listing input categories already documented. Does not provide additional meaning or syntax hints.

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 the tool performs a leveraged 10-year real estate pro-forma, listing inputs and outputs. It distinguishes from sibling tools that focus on analysis, risk, demographics, etc.

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 guidance on when to use this tool versus alternatives like 'scenario_what_if' or 'analyze_renovation_yield'. No prerequisites or exclusions mentioned.

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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