Статистика кампании

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

While annotations already mark the tool as read-only, idempotent, and non-destructive, the description adds substantial behavioral context: the response shape (data[] and totalData), exact metric set, currency (rubles), date semantics (inclusive, max 100 days), the inability to merge campaigns, per-day granularity, the API credit cost and apiPointBalance field, and a recommendation to prefer wide periods. This goes 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 efficient — every sentence adds information (metrics, units, period limits, limitations, quota behavior). It is slightly longer than strictly necessary and could be split into bullets, but no sentence is filler, so it remains well-structured and front-loaded with the core purpose.

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?

Combined with the schema (all 3 parameters documented) and annotations (readOnly, idempotent), the description fully covers the tool: response shape (data[] and totalData), metrics and units, date handling, limitations, campaignId source, and API quota implications. There is no ambiguity left for an agent.

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 schema already documents all three parameters at 100% coverage, so the baseline is 3. The description adds meaningful context: the inclusive period semantics, max 100 days, the source of campaignId (list_campaigns), and the trade-off between wide vs. narrow periods due to API quota. This extra context justifies a 4.

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 states a specific verb (returns statistics) and resource (a single campaign), enumerates the metrics returned (views, clicks, ctr, spend, cpm, cpc, video metrics), and explicitly differentiates itself from sibling tools by noting it cannot aggregate multiple campaigns or go below daily granularity.

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 provides clear usage context: it handles one campaign over a date range, the period is inclusive up to 100 days, campaignId comes from list_campaigns, and it advises using one wide period over many narrow calls due to weekly API quota. It does not explicitly say 'use group_stats instead for per-group granularity,' but the limitation 'cannot merge multiple campaigns' and 'no finer-than-day granularity' make the boundaries clear. The quota hint effectively guides call batching.

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