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China Salary Tax & Net Pay (cumulative withholding 累计预扣)

china_income_tax_salary
Read-only

Your real China take-home month by month — under the cumulative method, where the same salary is taxed more each month as the year goes on. Computes monthly and annual individual income tax (IIT) on a China salary using the actual cumulative withholding method (累计预扣预缴法). Because tax is recomputed on year-to-date income, the same gross salary is withheld more each month as cumulative income climbs the brackets — so your take-home falls through the year. Simple monthly-bracket calculators (and general AI) get every month after the first bracket crossing wrong.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthlyGrossNoMonthly gross salary Assumed constant across the year.
socialInsuranceNoMonthly social insurance & fund (个人部分) Your own 五险一金 deduction per month (专项扣除) — this reduces taxable income. Use the 五险一金 calculator to get it.
specialDeductionsNoMonthly special additional deductions (专项附加扣除) Total of children’s education (2,000/child), childcare under 3 (2,000/child), elderly care (up to 3,000), housing loan interest (1,000) or rent (800–1,500), continuing education (400). These cut tax, not cash.

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only provide readOnlyHint, but the description goes far beyond by detailing the cumulative method's effect: tax increases each month, take-home falls. It also warns about common mistakes, giving rich behavioral context beyond what annotations offer.

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 appropriately sized for the tool's complexity. Every sentence earns its place: it explains the core concept, warns about common errors, and provides context for parameters. Key information is front-loaded.

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?

Given the tool's complexity (cumulative method, three parameters) and no output schema, the description explains the behavior thoroughly. It lacks explicit mention of return values, but the output is likely a table or numbers, which is implicit. Still, it provides sufficient completeness for an agent to understand what the tool does.

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% with descriptions, but the description adds value by clarifying that monthlyGross is assumed constant, and directs users to another calculator for social insurance. These additions enhance understanding beyond the schema.

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 computes China IIT using cumulative withholding method, and distinguishes it from simple monthly-bracket calculators by explaining that the same salary leads to decreasing take-home as the year progresses. The verb 'computes' and resource 'China salary tax and net pay' are specific.

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 when to use: for accurate China cumulative withholding tax, not simple calculators. It states that simple monthly-bracket calculators and general AI get it wrong, guiding users to this tool for correctness. However, it does not explicitly list alternative sibling tools or state when not to use this tool.

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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TDQS

A3.9/5.0
Disambiguation4/5

Each tool targets a distinct niche (e.g., specific country tax rules, loan types, or legal calculations), with detailed descriptions that clarify boundaries. However, the large number of tools (66) could cause some confusion for an agent trying to select the right one for a general query, especially when multiple tools relate to the same country.

Naming Consistency4/5

Tool names follow a mostly predictable pattern: lowercase words separated by underscores, often starting with a country name (e.g., 'uk_stamp_duty_sdlt') or a topic (e.g., 'compound_growth'). There are minor deviations, such as abbreviations ('npv_irr', 'sip') and varying use of verbs, but overall the naming is clear and consistent.

Tool Count3/5

At 66 tools, the server is unusually large and covers an extensive range of financial and legal calculators. While each tool justifies its existence, the count exceeds the typical well-scoped range (3–15), making the server feel bloated. A more modular design might improve coherence.

Completeness4/5

The tool set covers a wide array of domains: personal income taxes, property taxes, loan calculations, investment returns, and specific country regulations. Minor gaps exist (e.g., missing tools for corporate taxes, general retirement planning, or insurance), but the overall coverage is thorough and addresses many niche scenarios that general AI handles poorly.

Resources