freelance_hourly_rate_calculatorFreelance Hourly Rate Calculator — Calculate your freelance hourly rate accounting for taxes, business expenses, and a profit margin. Find out exactly what to charge to hit your income goal.
| Name | Required | Description | Default |
|---|---|---|---|
| taxRatePct | Yes | ||
| profitMarginPct | Yes | ||
| workWeeksPerYear | Yes | ||
| desiredAnnualIncome | Yes | ||
| billableHoursPerWeek | Yes | ||
| annualBusinessExpenses | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden. It explains the tool accounts for taxes, expenses, and profit margin, but does not detail the formula, assumptions, or output format. It leaves ambiguity about how taxes are applied (e.g., gross-up vs. net) or what 'exactly' means.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action. The second sentence reinforces the outcome without adding fluff. Every phrase contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a straightforward calculator with six numeric inputs and no output schema. The description conveys the input categories and goal, which is mostly sufficient. It falls short of full completeness by not describing the output formula or key assumptions, but given the simple domain, it is close to adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 mentions taxes, business expenses, profit margin, and income goal, which maps to the main parameters. However, it does not explain the role of billableHoursPerWeek and workWeeksPerYear explicitly, nor how profit margin is applied.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates a freelance hourly rate, specifically accounting for taxes, business expenses, and profit margin. This distinguishes it from sibling calculators like salary_to_hourly_calculator, which converts salary to hourly without those additional factors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for freelancers who want to set a rate to reach an income goal, naming key inputs (taxes, expenses, profit margin). It does not explicitly mention alternatives or exclusions, but the context is clear enough for typical use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.