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dma9527

irs-taxpayer-mcp

by dma9527

calculate_total_tax

Calculate combined federal and state tax liability using income, deductions, filing status, and state code to determine total tax owed.

Instructions

Calculate combined federal + state tax for a complete picture of total tax liability. Returns federal breakdown, state tax, and combined totals in one call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taxYearYesTax year (2024 or 2025)
filingStatusYesFiling status
grossIncomeYesTotal gross income in USD
stateCodeYesTwo-letter state code (e.g., 'CA', 'TX', 'NY')
w2IncomeNoW-2 wage income
selfEmploymentIncomeNoSelf-employment income
capitalGainsNoLong-term capital gains
capitalGainsLongTermNoWhether capital gains are long-term (default: true)
qualifiedBusinessIncomeNoQBI for Section 199A deduction
aboveTheLineDeductionsNoAbove-the-line deductions
itemizedDeductionsNoTotal itemized deductions
dependentsNoNumber of qualifying child dependents
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the tool returns federal breakdown, state tax, and combined totals, which is useful. However, it lacks critical behavioral details such as whether this is a simulation or actual filing, accuracy limitations, rate limits, or authentication requirements for a tax calculation tool with 12 parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose and followed by return details. It's efficient with zero waste, though slightly more context could improve completeness without sacrificing conciseness.

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?

For a complex tax calculation tool with 12 parameters and no annotations or output schema, the description is minimally adequate. It covers the purpose and return structure but lacks behavioral transparency, usage guidelines, and output details, leaving gaps for an AI agent to understand full context.

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?

Schema description coverage is 100%, so the schema fully documents all 12 parameters. The description adds no parameter-specific information beyond implying the tool uses these inputs for combined tax calculation, which is minimal value. Baseline 3 is appropriate when schema does the heavy lifting.

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 the tool calculates combined federal and state tax liability, which is specific (verb+resource). It distinguishes from sibling tools like calculate_federal_tax and estimate_state_tax by emphasizing the combined calculation, though it doesn't explicitly name them for comparison.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like calculate_federal_tax or estimate_state_tax. It mentions 'complete picture' but doesn't specify scenarios, prerequisites, or exclusions for usage.

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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