Xearno Tools

Price in Work Hours

price_in_hours

Read-only

What a price really costs you: hours of your own work, at your take-home pay. Converts any price — a purchase or a subscription — into the hours and workdays of your own labor it consumes, using take-home pay rather than gross (you buy things with net money). For recurring costs it adds the yearly bill, the share of your working year, and what the same money becomes if invested instead. Time is the one budget everyone understands.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`pay`	No	Pay (gross) Hourly rate or annual salary, before tax — the next field nets it down.
`price`	No	Price
`cadence`	No	How often	once
`payMode`	No	You earn	hourly
`takeHomePct`	No	Take-home share (%) The share of gross you actually keep after tax and contributions. Typical full-time range: 65–85%.

TDQS

A3.9/5.0

Behavior4/5

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

Annotations indicate read-only, which matches. Description adds behavioral details: conversion method (take-home pay), handling of recurring costs (yearly bill, working year share, investment alternative). These go beyond annotations.

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?

Description is a single paragraph that is well-structured and front-loaded with the core idea. Every sentence adds value without being overly verbose.

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

Completeness4/5

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

Despite no output schema, description explains what is returned (hours, workdays, and for recurring costs: yearly bill, working year share, investment alternative). All required input parameters are documented in schema, making the tool complete for its purpose.

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 100%, so description does not need to add parameter details. It provides overall context but no parameter-specific explanations. Baseline 3 is appropriate.

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?

Description clearly states what the tool does: converts price into hours and workdays of labor using take-home pay. It is distinct from sibling tools, which are other financial calculators, and provides a unique value proposition.

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?

Description implies usage context (any price, especially subscriptions) but does not explicitly state when to use vs. alternatives or when not to use. No exclusions or alternatives mentioned.

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

Each tool targets a distinct niche (e.g., specific country tax rules, loan types, or legal calculations), with detailed descriptions that clarify boundaries. However, the large number of tools (66) could cause some confusion for an agent trying to select the right one for a general query, especially when multiple tools relate to the same country.

Naming Consistency4/5

Tool names follow a mostly predictable pattern: lowercase words separated by underscores, often starting with a country name (e.g., 'uk_stamp_duty_sdlt') or a topic (e.g., 'compound_growth'). There are minor deviations, such as abbreviations ('npv_irr', 'sip') and varying use of verbs, but overall the naming is clear and consistent.

Tool Count3/5

At 66 tools, the server is unusually large and covers an extensive range of financial and legal calculators. While each tool justifies its existence, the count exceeds the typical well-scoped range (3–15), making the server feel bloated. A more modular design might improve coherence.

Completeness4/5

The tool set covers a wide array of domains: personal income taxes, property taxes, loan calculations, investment returns, and specific country regulations. Minor gaps exist (e.g., missing tools for corporate taxes, general retirement planning, or insurance), but the overall coverage is thorough and addresses many niche scenarios that general AI handles poorly.

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