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Xearno Tools

Break-Even

break_even
Read-only

Units and revenue needed to cover costs — and how much pricing moves it. Classic cost-volume-profit analysis: contribution margin, break-even units and revenue, margin of safety if you supply current volume, and the leverage a price change has on all of it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
priceNoPrice per unit
fixedCostsNoFixed costs / month Rent, salaries, software — costs that don’t vary with volume.
currentUnitsNoCurrent monthly units Optional — adds margin-of-safety analysis.
variableCostNoVariable cost per unit Materials, shipping, payment fees — costs incurred per unit sold.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the tool is known to be non-destructive. The description adds context on the specific analyses performed (contribution margin, break-even, margin of safety, price leverage) and the optional nature of current volume, which enhances understanding of the tool's behavior beyond the annotations.

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?

The description is two sentences, front-loaded with the core purpose, and contains no unnecessary words. Every sentence adds meaningful information, achieving maximum conciseness.

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?

Despite no output schema, the description enumerates all key outputs (contribution margin, break-even units and revenue, margin of safety, price leverage). Combined with detailed parameter descriptions, the tool's functionality is fully conveyed for a data analysis tool of moderate 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 description coverage is 100%, so parameters are well-documented. The description adds value by explaining how parameters relate to outputs (e.g., 'current volume' enables margin-of-safety analysis) and summarizing the overall analysis, which goes beyond the schema descriptions.

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 computes break-even units and revenue, contribution margin, margin of safety, and price change leverage. It uses specific verbs like 'needed to cover costs' and 'how much pricing moves it', making the purpose unmistakable and distinct from siblings such as 'unit_economics'.

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 implies usage for cost-volume-profit analysis but does not explicitly state when to use this tool versus alternatives like 'unit_economics' or 'pricing_margin'. No when-not-to-use or alternative tools are mentioned, providing only implicit 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

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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