get_trending_videos

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: it explains the source of results ('category-specific charts'), provides historical context about the Trending page removal, and specifies practical usage notes (e.g., category_id mappings). However, it lacks details on rate limits, authentication needs, or error 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 appropriately sized and front-loaded, starting with the core purpose. Every sentence earns its place: the first states the function, the second provides critical historical context, and the third offers essential usage details. There is no wasted text, and the structure guides the user from general to specific information.

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 moderate complexity (3 parameters, no output schema, no annotations), the description is largely complete. It covers purpose, usage context, and parameter semantics well. However, it lacks details on output format (e.g., what data is returned) and error conditions, which would be helpful for a tool without an output schema.

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 100% description coverage, so the baseline is 3. The description adds significant value by explaining the meaning of category_id values (10 for Music, 20 for Gaming, 43 for Movies, 0 for mixed) and clarifying that results come from category-specific charts, which provides context beyond the schema's technical 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 the specific action ('Returns currently popular YouTube videos') and resource ('YouTube videos'), distinguishing it from siblings like get_top_videos or get_video_details by focusing on trending content. It also specifies the scope ('for a given region and category'), making the purpose explicit and differentiated.

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 provides explicit guidance on when to use this tool by noting that 'YouTube removed its global Trending page' as of July 2025, directing users to category-specific charts. It lists specific category_id values (10, 20, 43, 0) for different use cases, offering clear alternatives within the tool itself without referencing sibling tools.

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