Get Email Analytics

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

The description goes beyond annotations by disclosing that results are cached for 5 minutes and that response times are null when data is insufficient. This adds valuable behavioral context that annotations (readOnlyHint, openWorldHint) do not cover.

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 two sentences long, front-loading the key purpose and details. Every sentence adds value without redundancy or filler, making it efficient for an AI agent to process.

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 no parameters and an output schema exists, the description covers all necessary context: components of analytics, caching behavior, and null handling. It is complete for a self-contained read-only analytics tool.

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?

There are no parameters, and the schema coverage is 100% (empty). The description adds meaning beyond the schema by explaining what the analytics include, such as top senders/recipients and peak hours, which is not inferable from the input 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 provides advanced analytics across inbox and sent, listing specific components: top senders/recipients, peak activity hours, attachment stats, and response times. It distinguishes itself from siblings like get_email_stats and get_volume_trends by detailing its scope and output.

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 does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or context for when not to use it. However, the detailed output list implies its purpose for high-level analytics, but without guidance, it leaves ambiguity.

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