CRE Intelligence

export_dcf_excel

Generate a downloadable Excel (.xlsx) underwriting model with LIVE formulas — editable assumptions, PMT/FV amortization, IRR, equity multiple, a sensitivity grid, live Fed rates, and (if an address is given) Census trade-area demographics. Returns a download link valid for 60 minutes.

Input Schema

TableJSON Schema

Name	Required	Description
`address`	No	Optional property address — adds a demographics sheet
`loan_rate`	No	Loan rate % — default live SOFR + 175bps
`noi_year1`	Yes	Year 1 Net Operating Income ($)
`equity_pct`	No	Equity as % of price (default 35)
`hold_years`	No	Hold period (default 10)
`exit_cap_rate`	No	Exit cap % — default entry cap + 25bps
`property_name`	No	Optional label for the model header
`purchase_price`	Yes	Acquisition price ($)
`noi_growth_rate`	No	Annual NOI growth % (default 3.0)
`amortization_years`	No	Amortization (default 30)

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4/5.0

Behavior4/5

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

With no annotations, the description carries full burden. It discloses key behavioral traits: the Excel contains live formulas, the download link is valid for 60 minutes, and a demographics sheet is conditionally added. However, it does not mention potential errors, size limits, or rate limits, which would improve transparency.

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 a single dense sentence that efficiently conveys the tool's purpose and key features. It is front-loaded with the primary action ('Generate a downloadable Excel ...') and wastes no words.

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 tool's complexity (10 parameters, output schema exists), the description covers the main functionality and output characteristics. It could mention error conditions or limitations, but overall it provides sufficient context for an agent to understand what the tool produces.

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%, and the schema already describes each parameter adequately. The tool description adds overarching context (e.g., demographics sheet for address) but does not significantly enhance individual parameter semantics beyond what the schema provides.

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 generates a downloadable Excel underwriting model with live formulas, listing specific features like PMT/FV amortization, IRR, sensitivity grid, etc. It distinguishes from siblings like build_dcf_model by emphasizing the export and downloadable nature.

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 description implies use when an Excel export is needed but does not explicitly state when to use this tool over alternatives (e.g., build_dcf_model), nor does it provide when-not-to-use guidance. Usage context is implied but not fully clarified.

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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TDQS

A4.3/5.0

Disambiguation5/5

Each tool targets a distinct resource and action: lease documents, rent rolls, DCF models, Excel export, risk flags, deal memos, market data, rates, inflation, demographics at two geographic levels, and land screening at two scales. No two tools have overlapping purposes.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case (e.g., abstract_lease, get_current_rates, screen_parcel_dd), making the tool surface predictable and easy to navigate.

Tool Count5/5

With 13 tools, the server is well-scoped for CRE investment analysis, covering lease abstraction, rent roll analysis, DCF modeling, market data, demographics, and land screening. The count is sufficient without being bloated.

Completeness5/5

The tool set covers the full lifecycle of CRE deal analysis: document parsing (lease, rent roll), financial modeling (DCF, Excel export), risk assessment (flag risks, parcel screens), market context (rates, inflation, demographics, CRE market data), and output (deal memo). No obvious gaps for the intended purpose.

export_dcf_excel

Input Schema

Output Schema

TDQS

Glama MCP Gateway

TDQS

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