Relendi — Commercial Real Estate Loan Tools

Calculate Metrics

calculate_metrics

Read-only

Compute the standard commercial real estate underwriting metrics from raw figures: NOI, cap rate, DSCR, debt yield, LTV, LTC, operating expense ratio, break-even occupancy and yield on cost. Supply whatever you have — each metric is returned only when its inputs are present, with the formula used. Use this instead of computing CRE ratios yourself.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "calculate_metrics"
  }
}

Input Schema

Name	Required	Description
`rate`	No	DECIMAL (0.0725 = 7.25%), used to derive debt service
`loanAmount`	No
`annualRevenue`	No	Gross/effective annual revenue
`propertyValue`	No
`purchasePrice`	No
`annualExpenses`	No	Annual operating expenses (excl. debt service)
`totalProjectCost`	No	For LTC and yield-on-cost
`amortizationYears`	No
`annualDebtService`	No	Annual, not monthly
`netOperatingIncome`	No	Supply directly, or let it derive from revenue - expenses

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 15, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already mark the tool read-only and non-destructive; the description adds genuinely useful behavior: metrics are computed only when their inputs are present, and each returned metric includes the formula used. This goes beyond what the annotations alone communicate.

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?

Three sentences, front-loaded with the core purpose and metric list. No filler or restatement of the title beyond the essential.

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 multi-metric tool with ten optional inputs and no output schema, the description gives a good overview but does not specify output formatting, precedence rules (e.g., if netOperatingIncome and revenue-expenses are both supplied), or how inputs combine for each metric. It is adequate but not fully complete.

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 schema already covers 60% of parameters with descriptions, and the remaining parameter names are self-explanatory. The description adds no new unit or relationship details beyond the optionality already visible in the schema, though it does reinforce that partial inputs are acceptable.

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 opens with a precise verb and resource ('Compute the standard commercial real estate underwriting metrics from raw figures') and enumerates the exact output set. This makes it easy to distinguish from siblings like calculate_payment or size_loan, even though it never names them.

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

Usage Guidelines4/5

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

It gives clear context: call this when you have raw figures and need standard CRE ratios, and it explicitly invites partial input ('Supply whatever you have'). It lacks named alternatives or when-not-to-use conditions, so it stops just short of the highest tier.

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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