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jbechtel-97

dealflowpro-mcp-server

reverse_calc

Back-solve from target return metrics to calculate the maximum offer price for a multifamily property.

Instructions

Calculate the maximum offer price for a multifamily deal based on target return metrics. Back-solves from your desired cap rate, cash-on-cash, DSCR, and/or IRR to find what you should pay. Use this when someone asks 'what should I offer?' or 'what's the max price?'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthly_incomeYesTotal monthly rental income in dollars
monthly_expensesNoTotal monthly operating expenses in dollars
unitsNoNumber of apartment units
targetsYesTarget return metrics — provide at least one
assumptionsNoOverride default underwriting assumptions
Behavior3/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions back-solving from target metrics and default assumptions can be overridden, but does not detail algorithm limitations, accuracy considerations, or side effects.

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 two sentences: the first states the core function, the second provides use cases. It is extremely concise with no wasted 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 has 5 parameters including nested objects and no output schema, the description adequately covers purpose and usage. It could mention the output format (e.g., a dollar amount), but the lack is not critical.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already explains parameters. The description adds value by stating at least one target is required and assumptions can be overridden, which aides understanding beyond schema.

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 calculates the maximum offer price for a multifamily deal based on target return metrics. It uses specific verbs ('Calculate', 'back-solves') and distinguishes from siblings by focusing on pricing from return targets.

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?

The description explicitly states when to use this tool: when asked 'what should I offer?' or 'what's the max price?'. It implies the tool is for pricing rather than other analyses, but does not explicitly list alternatives or when not to use.

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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