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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuine behavioral context the schema does not: the default date window of 30 days and the fact that results are aggregated/grouped rather than raw records. It does not say anything about result size, pagination or what happens when both filters and grouping are supplied.

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?

Two sentences, front-loaded with the metric inventory and the grouping dimension, and the default range tacked on last where it belongs. The measure list is dense but every item is informative; no filler prose.

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?

With five undocumented parameters, no output schema, and one enum, the description should do more: it leaves the date range semantics and the link_id/offer_id filters unexplained and says nothing about the shape of the response beyond grouping. For a metrics tool this is adequate but leaves real gaps an agent must guess at.

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 0%, so the description must carry parameter meaning. It partially does: it names the three grouping values (day, offer, link) and anchors earnings to UZS, but it never explains date_from/date_to semantics, what link_id or offer_id filtering does, or whether filter and group_by must be consistent (e.g. group_by=link with offer_id).

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?

It names the concrete resource (aggregated performance metrics) and enumerates the measures returned — orders, approved, delivered, rejected, approval/delivery rates, earnings in UZS — plus the grouping dimensions. That is far more specific than the title 'Statistics'. It stops short of differentiating itself from the sibling get_insights, so it is clear but not sibling-aware.

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?

There is no statement of when to use this versus get_insights or list_orders, and no exclusions or prerequisites. The only usage-adjacent fact is the default window ('last 30 days'), which tells the agent what happens by default but not when to choose this tool.

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