video_auto_chapters

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It explains the operation and output format but does not disclose whether the input video is modified, potential limitations, or side effects. It is adequate but not comprehensive.

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 very concise: two sentences plus clearly labeled Args and Returns sections. Every sentence adds value, and there is no fluff. Well-structured for quick parsing.

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 an output schema, the description's brief mention of return format is sufficient. It covers both parameters well but could specify accepted video formats or error behavior. Overall, fairly complete for a simple 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?

With 0% schema coverage, the description compensates well by explaining input_path as 'Absolute path to input video' and threshold with range (0-1) and default (0.3). This adds significant value beyond the schema's type-only definitions.

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 'Auto-detect scene changes and create chapters' and explains it analyzes video for scene cuts and returns chapter timestamps. This distinguishes it from sibling tools like video_detect_scenes by explicitly mentioning chapter creation with description tuples.

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 usage when auto-generating chapters from scene detection but does not explicitly state when to use this tool vs alternatives like video_detect_scenes. No exclusions or prerequisites are mentioned.

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