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chiKeka

Alberta Tax Agent

by chiKeka

Salary vs Dividend Optimizer

salary_vs_dividend

Compare total tax cost of extracting corporate income via salary, eligible dividends, or non-eligible dividends, factoring in CPP/EI, RRSP room, and integration imperfections.

Instructions

Compare the total tax cost of extracting corporate income as salary, eligible dividends, or non-eligible dividends. Accounts for CPP/EI, RRSP room, and integration imperfections.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
needs_rrsp_roomNoDoes the shareholder want to maximize RRSP contribution room?
corporate_incomeYesAmount of corporate income to extract ($)
needs_cpp_benefitsNoDoes the shareholder want to build CPP pension benefits?
other_personal_incomeNoOther personal income besides this extraction ($)
Behavior3/5

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

With no annotations, the description carries the full burden. It transparently discloses key calculation factors (CPP/EI, RRSP room, integration imperfections) but does not mention output format, assumptions, limitations, or side effects. This is adequate but not detailed.

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 short sentences, front-loaded with the primary verb 'Compare' and delivers essential information without redundancy. Every phrase adds value.

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?

For a calculator with 4 parameters and no output schema, the description covers the core purpose and factors. It does not specify the exact return format or any prerequisites, but given the moderate complexity and full schema descriptions, it is mostly complete. A small gap remains around output details.

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 baseline of 3. The description adds meaning by linking parameters to functional purpose: 'RRSP room' relates to needs_rrsp_room and 'CPP/EI' to needs_cpp_benefits, and it explains the overall objective of the calculation. This goes beyond 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's function: comparing total tax cost among salary, eligible dividends, and non-eligible dividends. It uses specific verbs and a clear resource, and it distinguishes itself from sibling tools like calculate_payroll or calculate_corporate_tax by explicitly focusing on extraction method comparison.

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 implies usage context clearly: when deciding how to extract corporate income as salary vs dividends. However, it does not explicitly mention when not to use it or provide alternative tool names, so it lacks explicit exclusions/alternatives but still offers a clear context.

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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