Skip to main content
Glama

calculators

Rent vs Buy Calculator

rent_vs_buy_calculator

Rent vs Buy Calculator — Compare renting vs buying over any timeline. See which builds more wealth, when break-even hits, and how appreciation and rent increases tip the balance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
homePriceYes
monthlyRentYes
horizonYearsYes
sellCostsPctYes
downPaymentPctYes
mortgageRatePctYes
rentIncreasePctYes
mortgageTermYearsYes
buyClosingCostsPctYes
homeAppreciationPctYes
investmentReturnPctYes
maintenancePctAnnualYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions outputs like wealth comparison and break-even, but doesn't disclose any assumptions, limitations, or that the tool is a simulation relying on percentage inputs. It also omits return format and any 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 concise, two sentences long, front-loaded with the tool name, and contains zero filler. Every sentence contributes to understanding the tool's core purpose and some output details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the high complexity (12 required parameters) and the absence of an output schema, this description is inadequate. It doesn't explain the calculation model, underlying assumptions, or how to interpret results beyond vague notions of wealth and break-even. Critical details about return values and edge cases are missing.

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

Parameters2/5

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

Schema description coverage is 0%, and the description adds no direct parameter explanations. It only loosely references 'appreciation' and 'rent increases', which map to homeAppreciationPct and rentIncreasePct, but gives no units, formulas, or context for the 12 required parameters. Parameter names are self-explanatory, but the description fails to compensate for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the verb 'Compare' with resource 'renting vs buying' and lists specific outputs ('which builds more wealth, when break-even hits'), making the tool's purpose clear. However, it doesn't explicitly differentiate from sibling calculators like rent_affordability_calculator, so it falls short of a 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention exclusions or name any alternative tools, and the phrase 'over any timeline' only implies flexibility without specifying decision criteria or preferential use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources