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calculate_company_tax

Compute corporate profit and capital tax for Swiss legal entities and rank locations by tax burden to find the most favorable canton.

Instructions

Profit and capital tax for a company (GmbH, AG or similar).

Pass a canton code, 'capitals' or 'switzerland' as location to rank places, which is the usual reason to ask: cantonal profit tax rates for legal entities differ by a factor of roughly two across Switzerland.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNoWhen ranking locations, how many to return per end.
languageNode
locationYesTax location id, postal code, municipality name, canton code, 'capitals' or 'switzerland'.
tax_yearNo
total_assetsNoBalance sheet total, CHF. Some cantons need it for the capital tax.
share_capitalNoNominal share capital, CHF. Defaults to taxable_capital.
taxable_profitYesTaxable profit, CHF.
taxable_capitalYesTaxable capital (equity), CHF.
patent_box_reliefNoCombined patent box, R&D and equity-interest relief, CHF.
profit_before_taxesNoTrue if taxable_profit is stated before tax is deducted.
taxable_profit_federalNoFederal taxable profit if it differs from the cantonal figure.
participation_net_profitNoNet profit from qualifying participations, for participation relief.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations provided, so description must convey behavior. It implies a read-only calculation but does not explicitly state non-destructive nature or other behavioral traits like data modification or rate limits.

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?

Two sentences, front-loaded purpose, no wasted words. Highly concise.

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

Completeness3/5

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

Given 12 parameters and an output schema, the description covers the primary use case (ranking locations) but lacks depth on other scenarios. It is adequate but not comprehensive.

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?

With 83% schema coverage, the schema already documents most parameters. The description adds value by explaining the 'location' parameter usage for ranking, but does not enhance understanding of other complex parameters like 'patent_box_relief'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it calculates profit and capital tax for companies, and mentions ranking locations. It distinguishes from siblings like 'calculate_tax' and 'compare_locations', but could be more explicit about the return format.

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 hints at when to use (ranking places) and why cantonal rates differ, but does not explicitly state when not to use or mention alternatives like 'calculate_tax'.

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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