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

Annotations include readOnlyHint=true and openWorldHint=true. The description adds context: it's a read-only fetch, explains metrics under 'base', and notes that spent is in account currency. This goes beyond annotations without contradiction.

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 well-structured and front-loaded with the main purpose. It uses clear bullet-like guidance (e.g., 'use day/week/month ONLY for...'). Every sentence adds value, though it could be slightly more concise.

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 11 parameters, no required, and no output schema, the description covers usage patterns well: grouping, sorting, total, pagination. It lacks explicit return format details, but the guidance is sufficient for correct invocation.

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% (baseline 3). The description adds meaning by explaining default behavior for period (summary), giving examples for sortBy (base.spent), and describing autoPaginate as fetching all pages. This adds value 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 states the tool fetches performance statistics from the VK Ads v3 statistics service for ad plans, ad groups, or banners. It specifies default grouping and provides guidance on when to use alternative groupings. This is specific and distinct from sibling tools like create_ or list_ tools.

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 gives explicit guidance on when to use summary vs day/week/month grouping, explains server-side sorting with sortBy + order, and describes the total field to avoid manual summation. However, it does not explicitly compare to alternative tools among siblings, but the tool's purpose is unique enough.

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