calculate_engagement

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

With no annotations provided, the description must carry the behavioral disclosure burden. It clarifies that metrics are based on view count, but does not specify the exact formulas, result format (percentages vs. ratios), or any edge cases. It implies a read-only calculation but does not confirm safety behavior explicitly.

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, tightly structured sentence that front-loads the action and resource, names the computed metrics, and states the basis for calculation. There is no redundant or vague filler.

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 one-parameter calculation tool, the description provides the essential context: what is computed and based on what. The only minor gap is the lack of explicit return-format details, but overall an agent has enough information to invoke 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?

The schema already covers the only parameter with a clear description ('YouTube video URL or video ID'), and schema coverage is 100%. The tool description adds no additional parameter detail, which is acceptable under the high-coverage baseline but does not exceed it.

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 states a specific verb ('Calculate'), a clear resource ('a YouTube video'), and the concrete outputs (like rate, comment rate, overall engagement rate). This makes it immediately distinguishable from sibling tools such as get_video_metadata or get_video_comments.

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 intended use is implied by the name and description, but there is no explicit guidance about when to choose this tool over alternatives, no prerequisites, and no exclusion conditions. It is adequate but relies entirely on inference.

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