無音/フィラー自動カット
yt-silence-cutWhisper-WebGPU で無音とフィラーを検出、ジャンプカット風テンポに一発編集 (Browser-based tool)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
yt-silence-cutWhisper-WebGPU で無音とフィラーを検出、ジャンプカット風テンポに一発編集 (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 full responsibility for disclosing behavior. It notes the tool is browser-based and uses Whisper-WebGPU, but it does not indicate whether the edit is destructive, whether a new file is created, if the original is preserved, or any limitations (e.g., file size, browser requirements). The phrase 'one-click edit' implies a mutation but leaves side effects unclear.
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, compact sentence that front-loads the core action (detect and edit) and includes essential context (browser-based, Whisper-WebGPU). There is no redundant or filler content; every word contributes to understanding the tool's purpose.
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's simplicity (0 parameters, no output schema, no annotations), the description conveys the main function but omits practical details such as what the output is (e.g., a downloadable video file), whether the edit is reversible, and any browser/device constraints. It is minimally sufficient but leaves room for the agent to ask about workflow and side effects.
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 tool has zero parameters, so the schema provides no information to explain. Per the rubric, a baseline of 4 is appropriate for tools with no params; the description does not need to compensate for missing schema details and does not add any parameter-related noise.
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: detecting silence and fillers with Whisper-WebGPU and editing into a jump-cut style tempo. It uses a specific verb ('detect' and 'edit') and names the resource (audio/video content), distinguishing it from siblings like yt-denoise (noise reduction) or yt-lufs (loudness).
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 usage context: when you want to remove silences and fillers from video for a jump-cut effect. However, it does not explicitly state when to use this tool versus alternatives like yt-pattern-interrupt or yt-quick-polish, nor does it mention any exclusions or prerequisites.
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.