Traffic Sources Analytics

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=true. The description adds valuable behavioral context: the JSON return shape, possible error (403 with resolution), and that response_format can be markdown (default) or json. No contradictions with annotations.

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 well-organized with clear sections: purpose, args, returns, examples, errors. Every sentence adds value, and the structure is easy to scan. It is appropriately sized for the tool's complexity.

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?

With no output schema, the description compensates by providing the exact JSON structure, column names, and example rows. It covers all parameters, error handling, and usage examples. This makes the description fully complete for an AI agent to invoke the tool correctly.

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 baseline is 3. The description adds extra meaning by showing default values (e.g., 'Defaults to 28 days ago'), providing examples, and clarifying the response_format enum. This enhances understanding beyond the schema alone.

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 tool's purpose: 'Show how viewers find the channel's videos, broken down by traffic source type' and lists example sources. This is a specific verb+resource combination that distinguishes it from sibling analytics tools like youtube_top_videos or youtube_video_performance.

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 example use cases ('Where do my viewers come from?') and demonstrates custom date usage. While it does not explicitly state when not to use or compare to alternatives, the context of sibling tools and the specific focus on traffic sources gives clear usage context.

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