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日本の給与・社会保険・労働法

by io.github.kishida-devil

年間平均による保険者算定(季節変動がある場合)

judge_annual_average

For work whose April-June happens to be its busiest or quietest quarter, where the ordinary calculation would fix a grade that is wrong for eleven months of the year. Available for 定時決定 (since April 2011) and 随時改定 (since October 2018).

The 随時改定 figure is NOT a plain twelve-month average: it is the three-month average of FIXED pay plus the twelve-month average of NON-FIXED pay, so the two are supplied separately, and three distinct grade tests must all pass.

Both routes need the employee's consent and require that the swing recurs every year for reasons inherent to the work — a one-off busy period does not qualify. Neither is something this tool can verify, so both are declared inputs and are echoed back in the response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesregular = 定時決定の年間平均, revision = 随時改定の年間平均.
monthsYesExactly 12 entries. For regular: 前年7月 through 当年6月 in order. For revision: the 9 months BEFORE the pay change, then the 3 months after it.
worker_typeNogeneral = 一般の被保険者 (17-day threshold). part_time_short_hours = 短時間就労者, works shorter hours but meets the three-quarters test (17 days, with a 15-day fallback that exists ONLY in 定時決定). short_time_insured = 短時間労働者 at a 特定適用事業所 (11 days). Defaults to general.
employee_consentYesThe employee has consented. Mandatory condition.
fixed_pay_changeNorevision only.
recurring_annuallyYesThe swing recurs every year for reasons inherent to the work. Mandatory condition.
current_remunerationNorevision only.

Schema Changelog

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

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and handles it well. It reveals that the 随時改定 result is not a plain twelve-month average, explains the fixed/non-fixed split, mentions that three grade tests must pass, and discloses that the tool cannot verify consent or recurrence and merely echoes those declarations back.

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 dense but well-organized: use case first, then route-specific logic, then requirements and limitations. Every sentence contributes information, and there is no filler or repetition.

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 complex tool with seven parameters and no output schema, the description covers the core conditions, formulas, route differences, and input verification. The main gap is that it never explicitly states what the response contains beyond echoing the consent and recurring-annually inputs, such as whether the computed grade is returned.

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%, so the baseline is 3. The description adds meaning by explaining the mixed-average formula, the separate treatment of fixed and non-fixed pay, and the significance of consent and recurring_annually as mandatory echoed inputs. The schema already documents most property-level meaning though.

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 states a specific action: compute the annual-average insurer grade for seasonal work, and distinguishes the two supported routes (定時決定 and 随時改定). It clearly separates this from the ordinary calculation that would produce a wrong grade for most of the year.

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

Usage Guidelines5/5

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

It explicitly tells when to use the tool: when April-June is the busiest or quietest quarter and the ordinary calculation would fix an incorrect grade. It also gives when-not conditions, such as a one-off busy period, and states the mandatory consent and recurring-annual-swing requirements.

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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