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FIRE Calculator: When Can You Retire Early?

fire_calculator

FIRE Calculator: When Can You Retire Early? — Calculate your FIRE number and years to early retirement. Enter current savings, annual expenses, and expected return rate to reach financial independence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
currentAgeYes
annualSavingsYes
annualExpensesYes
currentSavingsYes
expectedReturnPctYes
withdrawalRatePctYes

Schema Changelog

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

  1. First observed

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description must carry the full burden of behavioral disclosure. It only mentions that it calculates a FIRE number and years to retirement, but fails to explain how inputs like withdrawalRatePct and expectedReturnPct are used, what the output format is, or whether assumptions like inflation or taxes are considered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loaded with the purpose, and efficiently conveys the core function. The minor redundancy of repeating the tool's title verbatim detracts slightly but does not significantly hurt clarity.

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?

For a calculator with six required parameters, no annotations, and no output schema, the description is incomplete. It does not define the FIRE number, explain the calculation methodology, specify output format, or list all required inputs, leaving significant gaps for an agent to infer.

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%, so the description should compensate. It only mentions current savings, annual expenses, and expected return rate, omitting currentAge, annualSavings, and withdrawalRatePct. It adds minimal meaning beyond the parameter names and does not explain how the inputs interact to produce the FIRE number.

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 clearly states a specific verb ('Calculate') and resource ('your FIRE number and years to early retirement'), which distinguishes it from other calculators like coast_fire_calculator. However, it does not explicitly name sibling tools or edge cases, so it lacks strong differentiation.

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?

No guidance is given on when to use this tool versus alternatives such as coast_fire_calculator or retirement_monte_carlo_calculator. There are no prerequisites, exclusions, or scenario-based instructions. The phrase 'Enter current savings...' implies usage but does not provide clear context.

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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