get_channel_videos

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

With no annotations provided, the description carries the full burden and adds valuable behavioral context: it discloses the quota efficiency ('no quota-expensive search.list'), specifies the data source ('uploads playlist internally'), and mentions the type of data returned ('recent public videos' with specific stats). However, it doesn't cover aspects like rate limits, error conditions, or pagination behavior.

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 front-loaded with the core purpose in the first sentence, followed by usage guidance and implementation details. Every sentence adds value without redundancy, making it highly efficient and well-structured for quick comprehension.

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 (2 parameters, no output schema, no annotations), the description is largely complete: it covers purpose, usage, behavioral traits, and implementation. However, without an output schema, it could benefit from more detail on the return format (e.g., structure of the video list), though the stats listed provide some context.

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%, so the schema already fully documents the two parameters (channel_url and limit). The description doesn't add any parameter-specific details beyond what's in the schema, such as explaining URL formats or limit implications. Baseline 3 is appropriate when the schema does the heavy lifting.

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 a list of recent public videos from a channel') and resource ('channel'), including detailed scope ('with per-video stats: views, likes, comments, duration'). It distinguishes from siblings by specifying this is for 'channel analysis' and uses 'uploads playlist internally', unlike tools like get_video_details or get_trending_videos.

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?

It provides explicit usage guidance: 'Use this as your primary dataset tool for channel analysis' and 'Uses the uploads playlist internally — no quota-expensive search.list', which helps differentiate from alternatives like get_top_videos or get_trending_videos that might use different methods or serve different purposes.

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