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nikolaymokh-dev

vk-ads-mcp

get_statistics_breakdown

Retrieve ad statistics broken down by demographics (age, gender, region) or technical attributes (placement, OS, device type) for campaigns, ad groups, or banners.

Instructions

Statistics sliced by a dimension.

Args: entity: campaigns | ad_groups | banners. ids: comma-separated IDs. group_by: one of age, gender, region, placement, os, device_type. metrics: metric group.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entityYes
idsYes
date_fromYes
date_toYes
group_byYes
metricsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. The description does not mention whether the tool is read-only, any rate limits, pagination, data freshness, or what happens on failure. The existence of an output schema partially mitigates this, but the description itself adds no behavioral context beyond the parameter list.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and uses a bullet list for args, which is reasonable. However, it omits two required parameters, making it incomplete. The front-loading is acceptable with a brief sentence followed by args, but the omission reduces the effectiveness of the structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With six parameters (five required) and an output schema, the description should cover all parameters and provide context on usage. It fails to mention date_from and date_to, does not explain what 'metric group' means, and offers no differentiation from sibling statistics tools. This leaves the overall description incomplete for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. While it provides allowed values for entity and group_by, and hints at ids being comma-separated, it completely omits two required parameters: date_from and date_to. This omission is critical and misleading, as a user might not know those parameters exist. The description does not sufficiently clarify all parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Statistics sliced by a dimension,' which conveys the main purpose of retrieving statistics broken down by a dimension. It also lists entity types and group_by options, clarifying the resource. However, it could be more explicit about the action (e.g., 'Retrieve statistics breakdown') and does not fully differentiate from similar siblings like get_statistics_day or get_statistics_summary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides allowed values for entity and group_by, giving implicit guidance on how to use the tool. However, no explicit guidance is given on when to use this tool versus alternatives (e.g., get_statistics_day or get_statistics_summary), nor are there any exclusions or when-not-to-use statements.

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

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