get_video_analytics

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

Annotations already mark this readOnly=true, idempotent=true, and non-destructive, so those are covered. The description adds meaningful behavioral context beyond the annotations: it is backed by Vimeo's reporting API, it requires a paid plan, and a free account returns an explanatory message rather than a hard error. That addition is genuinely useful for an agent deciding whether and how to call the tool.

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?

Three concise sentences. The first sentence states the purpose and main outputs; the second and third add the paid-plan caveat and free-account behavior. No wasted words, and the most decision-relevant information is front-loaded.

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 read-only analytics tool with a fully documented parameter schema and no output schema, the description covers the core purpose, the paid-plan requirement, and the free-account behavior. It does not detail return format or pagination, but given the output schema is absent and the tool is a getter, the provided context is sufficient for an agent to call it 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 each parameter is already documented in the schema. The description adds no parameter-specific detail beyond the schema, but it does not need to. Baseline 3 applies because the schema carries the parameter meaning.

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 names a specific verb ('Get real analytics for a video') and identifies the resource (video analytics) with exactly what data is returned: views over time, unique viewers, finish rate, and traffic sources. It is clearly distinct from sibling tools like get_video or get_video_stats because it describes the reporting-specific scope.

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 explicitly tells the agent when this tool is relevant (reporting/analytics data) and gives important usage context: it relies on Vimeo's reporting API and requires a paid plan. It also discloses what happens on a free account—a plain explanation rather than an error—so the agent can set expectations and avoid misinterpreting the response. This is strong usage guidance.

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