calc.engineer

salary to hourly

salary_to_hourly

Converts compensation between annual salary, monthly pay, weekly pay, and hourly wage. Accepts any of the four pay periods as input and derives all others. Uses configurable hours per week (default 40) and weeks per year (default 52). Daily rate assumes an 8-hour workday; monthly is annual divided by 12. Useful for comparing job offers quoted in different pay periods, freelance rate-setting, and budgeting. Chain from sales_tax to see how many hours a purchase costs.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`amount`	Yes	The salary or wage amount to convert.
`from_type`	No	The pay period of the input amount. Defaults to 'annual'.	annual
`hours_per_week`	No	Hours worked per week. Defaults to 40 for a standard full-time schedule.
`weeks_per_year`	No	Working weeks per year. Defaults to 52. Use 50 to account for 2 weeks unpaid vacation.

Output Schema

TableJSON Schema

Name	Required	Description
`daily`	Yes	Daily earnings assuming an 8-hour workday.
`annual`	Yes	Annual salary.
`hourly`	Yes	Hourly wage.
`weekly`	Yes	Weekly earnings.
`monthly`	Yes	Monthly earnings (annual / 12).
`biweekly`	Yes	Biweekly (every two weeks) earnings.

TDQS

A4.7/5.0

Behavior5/5

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

No annotations provided, so the description fully carries the burden. It discloses assumptions (default 40 hours/week, 52 weeks/year), derivations (daily rate from 8-hour day, monthly from annual/12), and flexibility (any pay period as input).

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?

Five concise, well-structured sentences. Each sentence adds information: purpose, input flexibility, defaults, formulas, use cases. No wasted words.

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

Completeness5/5

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

Given the presence of an output schema (not shown, but implied), the description covers all needed behavioral details: input types, defaults, derivations, and practical applications. It is complete for the tool's complexity.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds value by explaining the conversion logic and default behaviors (e.g., 'Uses configurable hours per week...'). It confirms the purpose of from_type and provides context for hours_per_week and weeks_per_year.

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 the tool converts compensation between annual salary, monthly pay, weekly pay, and hourly wage. It specifies the input and output perspectives, and the use cases differentiate it from sibling financial calculators.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear use cases: comparing job offers, freelance rate-setting, budgeting. It also suggests chaining with sales_tax, giving practical context. No explicit when-not-to-use, but the context is sufficient.

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

A3.9/5.0

Disambiguation4/5

Despite 89 tools, each has a clearly distinct purpose with detailed descriptions that often reference related tools. Overlap exists (e.g., multiple LoRa/RF tools), but the descriptions are sufficient to distinguish them. Some confusion possible among similar-sounding tools like attenuator_pi and attenuator_tee, but the descriptions explicitly compare them.

Naming Consistency4/5

Consistent underscore-separated lowercase naming. Most tools follow a verb_noun pattern (e.g., capacitor_charge, wire_gauge) or noun_noun (power_cost). Minor inconsistencies such as 'bmi_calculator' vs 'solar_sizing' but overall predictable.

Tool Count2/5

89 tools is far too many for a single MCP server. This scope is more appropriate for multiple specialized servers. The sheer number will slow agent selection and increase cognitive load, reducing coherence.

Completeness3/5

Covers many domains (RF, solar, PCB, networking, math, etc.) but lacks depth in some areas (e.g., no three-phase power, no airflow calculations). Some domains have comprehensive coverage (LoRa/Meshtastic), but others feel incomplete for the tool count.

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