Campaign statistics

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

Annotations already mark the tool as readOnly and non-destructive. The description goes further by disclosing API point costs, the apiPointBalance in the response, the 100-day maximum period, no sub-day granularity, and that money is in rubles. This enriches the behavioral context well beyond the annotations.

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 dense but well-structured, covering the response shape, metric list, units, constraints, and API cost guidance in a compact paragraph. Every sentence earns its place without 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?

With no output schema, the description fully specifies the return structure (data[] and totalData), all metric names, units, period inclusivity, and quota behavior. This makes the tool self-contained enough for an agent to invoke it correctly and interpret the response.

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 input schema provides 100% coverage of all three parameters, including the inclusive date range and 100-day limit. The description reinforces these points and mentions getting campaignId from list_campaigns, which is also in the schema. It does not add new parameter-specific meaning beyond what the schema already offers.

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 specifies that this tool returns statistics for ONE campaign over a date range, including per-group and per-creative breakdowns. This distinguishes it from sibling tools like group_stats and creative_stats, and the response structure is explicitly outlined.

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?

It explicitly states that aggregation across campaigns is not possible and directs users to list_campaigns to obtain campaignId. It also advises preferring one wide period over many narrow calls to conserve API points. However, it does not explicitly name alternatives for group/creative stats, though the breakdowns imply their existence.

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