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401(k) Employer Match Calculator

401k_match_calculator

401(k) Employer Match Calculator — Calculate your 401(k) employer match: enter salary and contribution rate to see the free money you earn, your total yearly savings, and long-run growth.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearsYes
salaryYes
firstTierPctYes
growthRatePctYes
secondTierPctYes
contributionPctYes
firstTierMatchPctYes
secondTierMatchPctYes

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions what the user will see (free money, yearly savings, growth) but does not explain how the tiered matching works, what assumptions are made about growth, or whether the operation is read-only. Key behavioral traits like the use of first/second tier match percentages are omitted, limiting transparency.

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, front-loaded sentence that quickly conveys the tool's purpose. There is some redundancy between the title and the opening phrase ('401(k) Employer Match Calculator — Calculate your 401(k) employer match'), but it's not overly verbose. It could be tighter by removing the repeated phrase.

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?

With 8 required parameters, no output schema, and no annotations, the description is insufficient for a tool of this complexity. It fails to explain the tiered match structure, the meaning of growth rate and years, or how the calculation works. The description is not complete enough for an agent to select and correctly use the tool without additional context.

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?

The schema has 0% description coverage, and the tool description only references salary and contribution rate, leaving the six tier and growth parameters unexplained. A user cannot understand what 'firstTierPct' or 'secondTierMatchPct' means from the description, so it adds minimal value for most of the 8 required parameters.

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 identifies the tool as a 401(k) employer match calculator with a specific verb ('Calculate') and resource ('your 401(k) employer match'). It distinguishes itself from sibling financial calculators by focusing on the match calculation, and the outputs listed (free money, total yearly savings, long-run growth) further clarify its purpose.

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 provides clear usage context by instructing the user to 'enter salary and contribution rate', implying this tool is used when those inputs are available. However, it does not explicitly state when not to use it or mention alternatives for different savings calculations, so usage guidance is implied rather than explicit.

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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