住民税シミュレーター
resident-tax-calc住民税の年額・月額を瞬時に計算。所得割・均等割の内訳表示 (Browser-based tool)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
resident-tax-calc住民税の年額・月額を瞬時に計算。所得割・均等割の内訳表示 (Browser-based tool)
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds useful context ('Browser-based tool', 'instantly') and mentions output breakdown, but it does not disclose side effects, limitations, or whether any external data is needed. For a calculator, this is minimally sufficient but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences: the first states the core function, the second adds breakdown detail and environment. It is front-loaded with the main purpose and contains no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description is complete for its complexity. It covers the calculation scope, breakdown, and the browser-based nature, which are the essential details for an agent to decide and invoke this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline is 4. The description adds semantic context by naming the calculation components (所得割・均等割), which gives meaning to the tool's function, even though it does not explain specific inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: calculating annual and monthly resident tax (住民税) and displaying a breakdown of income-based and per-capita portions. The verb '計算' (calculate) and specific resource '住民税' distinguish it from sibling tax calculators.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used when a user wants to calculate resident tax, but it does not explicitly contrast with sibling tools like freelance-tax-calc or take-home-pay-calc, nor does it provide when-not-to-use guidance. This is acceptable for a straightforward calculator, but not exceptional.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.