extract_chapters

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 the core behavior (reading the video description and returning chapters) and the return shape, but it does not describe edge cases such as missing chapters, malformed timestamps, or whether any errors can occur.

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, efficient sentence with no filler. It front-loads the action and resource, then states the output shape. Every component earns its place.

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 one-parameter extraction tool, the description is largely complete: it names the input, the source, and the return value. It lacks only minor context like behavior when the video description contains no chapters, but this is not a critical gap given the low complexity.

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?

Schema description coverage is 100%: the schema already documents the url parameter as 'YouTube video URL or video ID'. The tool description adds no further parameter-level detail, so the baseline score of 3 is appropriate.

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 uses a specific verb ('Extract') and resource ('chapter timestamps from a YouTube video's description'), and clarifies the output ('structured chapter list with titles and start times'). This clearly distinguishes it from sibling tools like get_transcript, get_video_metadata, and get_most_replayed, which target different data.

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 tool is for extracting chapter timestamps, but it provides no explicit guidance on when to choose it over related siblings such as get_video_metadata or get_most_replayed. There are no usage conditions, exclusions, or alternative routing cues.

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