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

Annotations already declare readOnly/idempotent/destructive=false, so the description's job is to add nuance, which it does: the multi-currency warning ('value is summed across currencies, so pass currency or group_by=currency for a clean total') and the rule that granularity is ignored when group_by is set are genuine behavioural disclosures beyond the annotations. It stops short of permissions, rate limits, or data-freshness notes.

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 dense sentences, but front-loaded with the default behaviour and output shape before the optional breakdown path, and every clause carries information (output shapes, currency caveat, use cases). Slightly long, yet nothing is padding.

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 16-parameter tool with an output schema and rich annotations, the description covers the two operating modes, the shape returned by each, the key caveat, and representative questions it answers. Nothing an agent needs in order to call it correctly appears to be missing.

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 coverage is 100%, so the baseline is 3, and the description exceeds it by explaining relationships the schema states only locally: granularity's default of day and its being ignored under group_by, the default ranking metric for order_by, and how currency interacts with the summed value. It adds cross-parameter meaning rather than repeating field definitions.

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?

States a specific verb and resource ('Aggregated conversion/revenue numbers from recorded events') and immediately distinguishes its output shape from the sibling list_analytics_events / get_analytics_clicks / get_analytics_views by declaring both the default timeseries and the group_by breakdown modes. An agent can tell what this returns without opening the schema.

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 'Answers total revenue, revenue by campaign/template/teammate/country, conversions per day, top customers' clause gives strong positive usage cues, and it explains the mode switch (default vs group_by) that selects behaviour. It does not, however, name or exclude the adjacent analytics siblings, so the routing is implied rather than explicit.

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