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 discloses that it is AI-driven, operates in-browser, and returns second-level intervention suggestions. Yet it does not explain how the video input is supplied, what the exact output format is, or any privacy/processing implications.

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 with a useful parenthetical note about being browser-based. Every phrase adds value and is front-loaded with the core 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 no output schema and no parameters, the description covers the main purpose and output granularity, but leaves gaps about how the tool receives the video and what the actual deliverable looks like (e.g., timestamp list, annotated timeline). It is adequate but not fully complete for agent invocation.

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 context about the tool's output (seconds) but does not need to explain parameter semantics since none exist.

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?

Description clearly states the tool detects monotonous segments (単調区間) that cause viewer attrition and proposes B-roll/zoom/cut intervention points in seconds. This specific verb+resource combination distinguishes it from sibling video tools like yt-silence-cut or yt-denoise.

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 implied usage is for video creators who need to identify dull sections and decide where to insert visual changes. However, it does not mention alternatives or when not to use it, such as other yt tools for audio or reframing. Context is present but not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.