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gsaccardi

Dichiarino

by gsaccardi

calcola_irpef

Calculate gross Italian IRPEF tax for a given total income and tax year (2023-2025), returning total tax and per-bracket details.

Instructions

Calcola l'IRPEF lorda per un dato reddito complessivo e anno fiscale.

    Utilizza gli scaglioni ufficiali (2024-2025: 23%/35%/43% - riforma IRPEF L. 207/2024).
    Restituisce l'imposta totale e il dettaglio per scaglione.

    Args:
        reddito_complessivo: Reddito complessivo in euro (>= 0).
        anno: Anno di imposta. Supportati: 2023, 2024, 2025. Default: 2025.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
annoNo
reddito_complessivoYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the transparency burden. It discloses the use of official brackets, the reference to the 2024-2025 IRPEF reform, and that the output is total tax with per-bracket detail. It does not fully detail 2023 bracket behavior, but it is a pure calculation tool with no side effects, so this is acceptable.

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 compact, front-loaded with the main purpose, and uses a clear Args list for parameters. Every sentence contributes meaningful information without redundancy.

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 tool's simplicity (two params, no nested objects), an output schema exists, and the description covers inputs, supported years, calculation basis, and output form. The description is complete enough for reliable invocation.

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

Parameters5/5

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

The input schema provides only titles, while the description adds crucial semantics: unit (euro), minimum value (>=0), supported tax years (2023-2025), and default year. This greatly helps an agent supply correct arguments.

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 uses a specific verb-plus-resource ('Calcola l'IRPEF lorda') and clearly distinguishes this tool from siblings like detrazione or addizionale calculators. It unambiguously states what it computes and for which tax years.

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 gives clear context for when to use the tool: for a given comprehensive income and tax year. It does not explicitly name alternative tools or state when not to use it, but the scope is well defined by the resource and supported years.

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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