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Glama

Social Insurance Calc

social-insurance-calc

Health, pension, and employment insurance from standard monthly income.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ageNoAge
industryNoIndustry typegeneral
prefectureNoPrefecturetokyo
monthlySalaryYesMonthly salary in JPY

Schema Changelog

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

  1. Changed6 schema fields changed
    • addedInput schema / $schema
      Added value: +"http://json-schema.org/draft-07/schema#"
    • addedInput schema / properties / age
      Added value: +{
      +  "default": 30,
      +  "description": "Age",
      +  "maximum": 100,
      +  "minimum": 15,
      +  "type": "number"
      +}
    • addedInput schema / properties / industry
      Added value: +{
      +  "default": "general",
      +  "description": "Industry type",
      +  "enum": [
      +    "general",
      +    "construction",
      +    "agriculture"
      +  ],
      +  "type": "string"
      +}
    • addedInput schema / properties / monthlySalary
      Added value: +{
      +  "description": "Monthly salary in JPY",
      +  "minimum": 0,
      +  "type": "number"
      +}
    • addedInput schema / properties / prefecture
      Added value: +{
      +  "default": "tokyo",
      +  "description": "Prefecture",
      +  "enum": [
      +    "tokyo",
      +    "osaka",
      +    "aichi",
      +    "kanagawa",
      +    "hokkaido",
      +    "fukuoka"
      +  ],
      +  "type": "string"
      +}
    • addedInput schema / required
      Added value: +[
      +  "monthlySalary"
      +]
  2. First observed

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description must carry behavioral disclosure. It reveals only the insurance categories and the 'standard monthly income' basis, but does not state whether results are monthly or annual, employee-only or total, or how age, prefecture, and industry affect the calculation.

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 a single sentence with no filler and starts with the core purpose. It is concise, though the brevity leaves out usage and behavior details, which is more a completeness concern than a conciseness flaw.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given four parameters, no annotations, and no output schema, the description should explain what the tool returns and how inputs influence results. It only lists insurance types, leaving rate complexity, output format, and calculation assumptions unexplained.

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?

The input schema already describes all four parameters with descriptions and enums, so the baseline is 3. The description adds little beyond framing monthlySalary as 'standard monthly income,' which the schema already conveys as 'monthly salary in JPY.'

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 identifies the resource and scope: health, pension, and employment insurance computed from standard monthly income. It is clear enough in context of the title, though it lacks an explicit verb and does not explicitly differentiate from sibling calculators like nhi-calc or take-home-pay-calc.

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?

There is no guidance on when to use this tool versus related insurance/tax calculators. No prerequisites, scenarios, or exclusions are mentioned, so the agent receives no decision support beyond the bare purpose.

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

B3.1/5.0
Disambiguation2/5

Multiple tools have overlapping purposes, such as bg-remover, bg-remover-pro, pro-matting, and takumi all performing background removal, and upscaler/upscaler-pro being redundant. With 202 tools, an agent may easily select the wrong one despite detailed descriptions.

Naming Consistency4/5

Most tools use a consistent kebab-case format with descriptive names like pdf-compress, image-resizer, and tax-return-calc. Exceptions like 'takumi', 'pro-matting', and '-pro' suffixes (bg-remover-pro, upscaler-pro) are minor deviations relative to the total.

Tool Count1/5

202 tools is an extreme mismatch for an MCP server, far exceeding the typical 3-15 well-scoped range. The sheer volume makes it unwieldy for an agent to efficiently navigate and select the right tool.

Completeness4/5

The tool set provides extensive coverage across many domains, including PDF operations (20+ tools), image editing, financial calculations, e-commerce fee estimation, and YouTube utilities. Minor gaps exist in cross-tool integration, but the breadth is highly comprehensive for the apparent purpose.

Resources