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True Cost of an Employee Calculator

employee_cost_calculator

True Cost of an Employee Calculator — Calculate the true, fully loaded cost of an employee beyond base salary: add employer FICA, benefits, and overhead to see the total and its multiple of pay.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
salaryYes
ficaPctYes
benefitsValueYes
overheadValueYes

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It does disclose the additive calculation ('add employer FICA, benefits, and overhead') and the output ('total and its multiple of pay'), but it omits critical context like whether values are annual, how ficaPct is applied, or the exact return format.

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 a single sentence and front-loaded with the tool's purpose. The only minor issue is redundancy with the title ('True Cost of an Employee Calculator' appears both in the title and at the start of the description), but no information is wasted.

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 4-parameter calculator with no output schema and no annotations, the description gives the essential inputs and outputs but lacks units, annual vs monthly assumptions, and precise parameter semantics. It is adequate for invocation but leaves the agent to infer several operational details.

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?

Schema description coverage is 0%, so the description must compensate. It maps 'employer FICA' to ficaPct, 'benefits' to benefitsValue, 'overhead' to overheadValue, and 'pay' to salary, which helps conceptually. However, it does not clarify that ficaPct is a percentage, nor that benefits/overhead are currency amounts; the schema's names and bounds partially fill this gap.

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 a specific verb ('Calculate') and a specific resource ('the true, fully loaded cost of an employee beyond base salary'). It further distinguishes the tool by naming components (employer FICA, benefits, overhead) and outputs (total and multiple of pay), making it distinct from basic salary calculators.

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 use case is implied: users who need a fully loaded employee cost beyond base salary. However, the description does not explicitly mention alternatives such as contractor_vs_employee_calculator or global_hiring_cost_calculator, nor does it provide when-not-to-use guidance.

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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