Get performance insights for account, campaign, ad group, or ad scope. Supports fields, filters, sort, product/country/device segments, time ranges, and cursor pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | ||
| after | No | ||
| limit | No | ||
| scope | Yes | ||
| before | No | ||
| fields | No | ||
| filters | No | ||
| includes | No | ||
| segments | No | ||
| entity_id | No | ||
| time_range | No | ||
| response_format | No | concise | |
| time_granularity | No | daily | |
| aggregation_level | No | ||
| override_segment_group_order | No |
Changes observed during successful MCP inspections.
Input schema / properties / aggregation_levelAdded value: +{
+ "enum": [
+ "ad_account",
+ "campaign",
+ "ad_group",
+ "ad"
+ ],
+ "type": "string"
+}Input schema / properties / includesAdded value: +{}Input schema / properties / override_segment_group_orderAdded value: +{}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context about cursor pagination and supported features (segments, time ranges), but does not cover other behavioral traits such as rate limits, data freshness, or authorization requirements. With annotations, the bar is lower, and the description provides moderate added value.
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 a single sentence that immediately states the purpose and lists supported features. It is concise, front-loaded, and contains no superfluous information.
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 and 15 parameters, the description is too high-level. It does not explain the response format, aggregation behavior, or how parameters interact. For a complex tool, more detail is needed to ensure proper agent usage.
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 compensate. It mentions high-level parameter categories (fields, filters, sort, segments, time ranges, pagination) but does not map them to the actual schema parameter names or provide detailed semantics for each of the 15 parameters. This is insufficient for a tool with many parameters.
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 verb 'Get' and resource 'performance insights' for specific scopes (account, campaign, ad group, ad). It distinguishes from sibling tools that retrieve single entities (e.g., get_account, get_campaign) by focusing on aggregated performance data.
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 implies usage for retrieving performance insights with various parameters like fields, filters, sort, and pagination, but does not explicitly state when to use this tool versus alternatives like get_campaign or list_campaigns. It lacks when-not or alternative tool references.
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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