get_analytics

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

No annotations are provided, so the description must convey behavioral context. It discloses that the tool returns open and click rates and is scoped to sent emails, but it does not mention error handling, response format, or any side effects. The description adds some value but lacks depth.

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?

One short sentence, front-loaded with the verb, no filler. Communicates the essential purpose efficiently.

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 simple tool with one parameter and no output schema, the description covers the core functionality and gives concrete examples of the returned data. It could mention whether analytics are aggregate or per-recipient, but the current level is adequate for the tool's simplicity.

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 fully describes the id parameter, so the description adds little extra. The only addition is the qualifier 'sent email', implying the id must reference a sent email, not a draft. This is a minor extension beyond the schema.

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 identifies the action (get), the resource (analytics), and the target (a sent email), with examples of the data (open rates, click rates). It distinguishes from sibling tools like get_email and get_subscriber_stats.

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 implies usage for retrieving email analytics but does not explicitly state when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. It is not misleading but provides no direct guidance.

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