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Rent Affordability Calculator

rent_affordability_calculator

Rent Affordability Calculator — Find out how much rent you can afford using the 30% rule, 50/30/20 budget, and a cashflow stress test. All three caps side by side so you see the trade-offs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dtiPctYes
takeHomePayYes
grossMonthlyIncomeYes
monthlyFixedExpensesYes

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently states the calculation methods (30% rule, 50/30/20, cashflow stress test) and reveals that output shows 'all three caps side by side' so users see trade-offs. This goes beyond a generic 'calculates rent affordability' and describes what the tool actually does and returns.

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, front-loaded with the tool's purpose, and every sentence adds value. It avoids unnecessary detail and is appropriately sized for a calculator tool.

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?

The description explains the core functionality and output format, but with no output schema and no parameter explanations, it is not fully complete. The ambiguity of `dtiPct` and the absence of any input guidance mean the agent must deduce semantics from parameter names, which is adequate but has clear gaps.

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

Parameters1/5

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

The schema has 0% description coverage and the description does not mention any of the four parameters (grossMonthlyIncome, takeHomePay, monthlyFixedExpenses, dtiPct). The description fails to add meaning to the input schema, leaving the agent to infer parameter semantics from names alone. This is a significant gap for a 4-parameter tool.

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's purpose: calculating rent affordability using three specific methods (30% rule, 50/30/20 budget, cashflow stress test). It uses an action verb ('Find out') and a specific resource ('how much rent you can afford'), and the mention of three methods distinguishes it from sibling calculators like rent_vs_buy_calculator and home_affordability_calculator.

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 the use case — determining affordable rent based on income and expenses — but gives no explicit guidance on when to use this tool versus alternatives like rent_vs_buy_calculator or home_affordability_calculator. It lacks any exclusion criteria or comparisons to sibling tools.

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

B3.1/5.0
Disambiguation2/5

Many calculators occupy overlapping conceptual spaces, such as 'ai_roi_calculator' vs 'ai_automation_payback_calculator' and 'llm_self_host_vs_api_calculator' vs 'ai_build_vs_buy_calculator'. The boundaries between debt payoff, savings goal, and drawdown tools are also fuzzy, making it easy for an agent to select the wrong tool despite detailed descriptions.

Naming Consistency5/5

Every tool follows the same <topic>_calculator pattern with lowercase snake_case, making the naming highly predictable and consistent. Even acronyms and numbers fit the pattern, so there is no mixing of conventions.

Tool Count1/5

122 tools is an extreme number for a single MCP server, far exceeding the 50+ threshold for a severe mismatch. The tools span unrelated domains like AI costs, pet food, concrete, pizza dough, and turkey cooking, creating an unfocused kitchen-sink surface that overwhelms an agent's selection process.

Completeness3/5

The set covers many common calculator categories such as finance, construction, health, and AI costs, but several staple calculators are missing (e.g., BMI, tip, discount, simple interest, currency conversion). The AI cost cluster is over-saturated while other everyday calculations are absent, leaving minor but noticeable gaps.

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