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FalaZuki Finance BR

calculate_first_million

Calcula em quanto tempo um aporte mensal chega a R$ 1 milhão (ou outra meta), quanto veio de juros, e o aporte necessário pra fechar em 10, 20 ou 30 anos. Taxa real escolhida pelo usuário. Parâmetros obrigatórios: monthly_contribution. Opcionais: initial_amount, annual_return, target_amount. Use exatamente estes nomes, em inglês.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
annual_returnNoRentabilidade anual em % (8 = padrão conservador de renda fixa líquida)
target_amountNoA meta em R$ (padrão: 1 milhão)
initial_amountNoQuanto já tem investido em R$
monthly_contributionYesAporte mensal em R$

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does disclose the calculation behavior, the real-rate assumption, and the parameter categories, but it does not describe the output structure or edge-case behavior (e.g., zero contribution, zero return, or how the 10/20/30-year results are returned together).

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 compact sentences with no filler. The main purpose is front-loaded, followed by the parameter contract. Every sentence earns its place.

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?

The tool has moderate complexity (4 params, no output schema) and many siblings. The description covers the scenario, calculations, required/optional parameters, and naming convention, which is enough to invoke it correctly. However, it leaves the exact output shape unspecified, which would be helpful given the multi-part calculation.

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%, giving a solid schema baseline of 3. The description adds value by explicitly grouping required vs optional parameters and instructing to use the exact English parameter names, which is useful for an agent that might otherwise localize or reorder the 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 ('Calcula') and a clear resource: how long a monthly contribution takes to reach R$ 1 million, how much came from interest, and the required contribution for 10/20/30 years. This clearly differentiates the tool from investment siblings like calculate_compound_interest or calculate_retirement by its unique goal-based horizon output.

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: use this when the user has a monthly contribution and wants to know time-to-goal, interest share, or needed contribution for fixed horizons. It does not explicitly name alternatives or say when not to use it, so it falls short of a 5.

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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