Salary Tax Calculator

Problem

Payroll teams often handle city-specific social insurance rates, housing fund contribution bounds, special additional deductions, and progressive individual income tax brackets by hand. When comparing two payroll periods, it is easy to miss unusual raises, pay cuts, or deduction changes. This skill turns that process into an inspectable calculation pipeline: tax_calculator.py computes pay components from city, gross salary, contribution base, and deductions; salary_parser.py reads Excel or CSV payroll files; anomaly_detector.py compares two periods and flags abnormal fluctuations.

How It Works

Inputs can be single-person parameters, such as “Beijing monthly salary 25,000 with the actual contribution base,” or a batch payroll table. The skill uses references/city_rates.json, references/tax_brackets.json, and references/deduction_rules.json to produce JSON details for social insurance, housing fund, income tax, and take-home pay. Policy queries can combine web search or knowledge-base lookup with links to local human-resources and tax bureau sources. report_generator.py produces an HTML report with a pay-structure pie chart, an income-tax bracket chart, and an anomaly dashboard.

Boundaries

Results depend on the selected city, contribution base, deductions, and reference rate data. If local policy changes, the output should be rechecked against the latest official rules. Anomaly detection is primarily based on period-over-period differences and is useful as a pre-audit screening step, not a compliance conclusion. It runs on Python 3.8+ with openpyxl and pandas, and does not require a GPU.