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Glama

日本の給与・社会保険・労働法

by io.github.kishida-devil

個人住民税の見込み額

estimate_resident_tax

Estimate of next fiscal year's resident tax (住民税: 道府県民税 + 市町村民税 + 森林環境税) from the previous year's income and the municipality: employment income from the NTA table for that year, resident-tax deductions (basic 430,000, spouse 330,000, dependants 330,000/450,000/380,000, life insurance capped at 70,000), the 10% income levy split 4%/6% (2%/8% in designated cities), the adjustment credit, the non-taxable thresholds (35万円 × persons + 10万円 + 21万円, with the 級地 rate), ふるさと納税 basic and special credits (special capped at 20% of the income levy), the housing-loan carry-over, per-capita amounts including every prefecture's surtax (37 of 47 have one; Kanagawa also adds 0.025% to the income levy) and the city rules of 横浜市 (+900), 神戸市 (+400) and 名古屋市 (5% cut). Matches the published 令和8年度 worked examples of Yokohama and Nagoya to the yen.

It is an ESTIMATE: the municipality decides the amount and the employer deducts what the 特別徴収税額通知書 says. Say so. income_year is the year the income was earned (2025 for the fiscal-2026 tax). Pass grade_level (級地 1-3) when known; it changes the per-capita exemption.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoMunicipality in Japanese, e.g. 横浜市. Used for designated-city rates and the three city rules held.
flagsNo
salaryNoGross employment income for the year, bonuses included.
spouseNoSpouse's 合計所得金額 for the year (0 if none).
dependantsNo
mutual_aidNo
prefectureYesPrefecture of the employer's 適用事業所 — English ("Tokyo"), Japanese ("東京" or "東京都"), or JIS code 1-47. Health insurance rates differ by prefecture; pension does not.
grade_levelNo級地 (1, 2 or 3) for the per-capita exemption threshold.
income_yearYesYear the income was earned: 2025 (fiscal 2026 tax) or 2026 (fiscal 2027 estimate).
disabilitiesNo
other_incomeNo
total_incomeNoUse instead of salary when the income is not (only) employment income: 合計所得金額 excluding salary.
casualty_lossNo
life_insuranceNoPremiums PAID; the resident-tax deduction (cap 70,000) is computed here.
designated_cityNoSet when the city is one of the 20 指定都市 and you did not pass city.
other_donationsNoOther qualifying donations (basic 10% credit only).
housing_loan_capNoCap rule for the resident-tax part: 5% (max 97,500) or 7% (max 136,500).
medical_expensesNo
social_insuranceNoSocial insurance paid in the year.
income_adjustmentNo
furusato_donationsNoふるさと納税 paid in the year.
medical_reimbursedNo
housing_loan_unusedNoHousing-loan credit the income tax could not absorb.
specified_relativesNo
earthquake_insuranceNo
disaster_related_expenseNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and discharges most of it: it flags estimate uncertainty, states that the municipality decides the amount and the employer deducts per the 特別徴収税額通知書, and instructs the agent to communicate that. It also states the fiscal-year mapping for income_year and validates accuracy against published examples, though it does not describe return shape or behavior for unsupported input combinations.

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 core purpose is front-loaded in the first clause, and nearly every subsequent clause carries a specific tax rule or caveat, so there is little waste. The density is high and the single run-on paragraph is harder to scan, which keeps it from a 5 for a tool with this many parameters.

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 26-parameter tax calculator with no annotations and no output schema, the description is unusually complete: it covers the main formula, prefecture surtax exceptions, city rules, the estimate caveat, and key inputs like income_year and grade_level. It still leaves some operational details, such as exactly what is returned and how unknown municipalities are handled, to the schema or the agent, so it is not a 5.

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 only 54%, and the description adds meaningful tax semantics beyond the schema: deduction amounts and caps, the 10% levy split with special rules for designated cities, the non-taxable threshold formula with 級地, furusato credits capped at 20%, and city-specific rules. It does not mention all 26 parameters, but it enriches the high-impact ones without contradicting 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 opens with 'Estimate of next fiscal year's resident tax (住民税: 道府県民税 + 市町村民税 + 森林環境税) from the previous year's income and the municipality', naming a specific verb, resource, and input basis. It distinguishes this tool from income-tax siblings by itemizing resident-tax components and even cites matching published worked examples.

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 for when the tool applies: estimating the next fiscal year's resident tax from the prior year's income and municipality, with the explicit 'It is an ESTIMATE' caveat and the instruction to 'Say so.' It does not explicitly name alternatives or state when-not-to-use it, so it stops short of a 5, but the context is unambiguous.

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

A3.8/5.0
Disambiguation4/5

Most tools have distinct, well-defined jobs—payroll calculations, revision judgments, eligibility checks, and data lookups are clearly separated. The main remaining risk is among the standard-remuneration judgment tools and the batch/singleton pairs, but their descriptions are detailed enough to prevent serious misselection.

Naming Consistency3/5

There is a reasonably recognizable pattern with calculate_, judge_, check_, get_, and validate_ groups. However, several noun-phrase names (business_days, consumption_tax, national_insurance, commuting_allowance_exemption) and overlapping verb choices (decide_ vs judge_ vs check_) prevent a fully consistent verb_noun convention.

Tool Count2/5

At 30 tools, the surface is materially larger than the 3–15 range that keeps an agent's selection burden low. Batch variants and three separate standard-remuneration revision tools add complexity, and although the domain is broad, the count feels heavy for an assistant to choose from confidently.

Completeness4/5

The core workflows are well covered: monthly pay, bonuses, overtime, standard-remuneration determination, year-end adjustment, resident tax, leave, worker classification, and invoice validation. Gaps exist around statutory benefit payments such as sickness or maternity allowances and retirement-specific processing, but most payroll and social insurance tasks can be completed without dead ends.

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