再生数シミュレーター
views-simulator登録者数×CTR×インプレッションから再生数を試算 (Browser-based tool)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
views-simulator登録者数×CTR×インプレッションから再生数を試算 (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?
No annotations exist, so the description must carry the full burden of behavioral disclosure. It mentions 'browser-based tool' but fails to clarify that the input schema is empty (0 parameters), creating ambiguity about how the mentioned inputs (subscriber count, CTR, impressions) are supplied. It also doesn't discuss output format, limitations, or any data handling.
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, well-structured sentence that conveys the formula and tool type without unnecessary words. It is front-loaded with the essential information, making it highly efficient.
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?
For a simple calculator, the formula provides the core understanding. However, the mismatch between the described inputs and the empty schema, along with the absence of usage context (e.g., platform, how to invoke), leaves gaps. No output schema exists, so the description should have clarified more about the expected user interaction and result.
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 is empty and parameter count is 0, so the baseline is 4. The description adds conceptual meaning by naming the three key inputs (subscriber count, CTR, impressions), even though they are not formal schema parameters. This helps an agent understand what the tool expects, despite the schema not reflecting it.
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 purpose: 'Calculate estimated view count from subscriber count × CTR × impressions' with the specific verb '試算' (estimate/calculate) and a precise formula. This distinguishes it from sibling tools like revenue calculators or CTR predictors.
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 explicit guidance is given on when to use this tool vs alternatives, nor any exclusions or prerequisites. The description merely states what it does, leaving the agent to infer usage context. Sibling tools like youtube-revenue-calculator exist, but no differentiation is provided.
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.