楽天市場手数料計算機
rakuten-fee-calculatorシステム利用料+決済手数料+ポイント→利益を正確計算 (Browser-based tool)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
rakuten-fee-calculatorシステム利用料+決済手数料+ポイント→利益を正確計算 (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?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals the calculation formula but omits key traits such as how the tool operates (browser-based), what inputs it expects, whether it makes any external calls, or any limitations. The parenthetical 'Browser-based tool' is minimal and doesn't explain behavior.
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 a single sentence that is easy to scan and front-loads the core purpose. The parenthetical 'Browser-based tool' adds marginal value, but overall it's appropriately concise without wasteful filler.
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 a browser-based tool with no parameters and no output schema, the description should explain how the user interacts with it and what result to expect. It only provides a formula, missing details about workflow, output format, or any edge cases. This is insufficient for an agent to confidently invoke the 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?
Since there are zero parameters, the schema offers nothing to document. The description adds meaning by explaining the calculation inputs (system fee, payment fee, points) even though they aren't structured as parameters. This compensates well for the empty schema.
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 specifies a clear calculation: system usage fee + payment processing fee + points → profit. The verb '計算' and resource '利益' are specific, and the formula distinguishes it from generic calculators. However, it doesn't explicitly differentiate from sibling Rakuten calculators like rakuten-rpp-calculator.
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?
No guidance is provided on when to use this tool versus other calculator siblings. There is no mention of suitable scenarios, prerequisites, or alternatives, leaving the agent to infer usage purely from the name and title.
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.