get_conversion_insights

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

With no annotations, the description carries the behavioral disclosure burden. It reveals the HTTP method, the required invocation parameters, and the totals-vs-daily output distinction, which is helpful. It does not explicitly state that this is a read-only operation or describe response/error behavior, but the 'Get' verb and 'attributed conversion totals' wording make the non-mutating intent reasonably clear.

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 tight: three sentences with no filler, and the result type is front-loaded before endpoint and parameter details. It earns its length, though the endpoint line and some parameter guidance partially duplicate schema 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?

Given 8 parameters, no annotations, and no output schema, the description provides enough to invoke the tool correctly: required fields, segmentation options, and grouping semantics. It does not mention entity_ids, ad_account_id, or include_zero_rows, but those are adequately documented in the schema, so the overall context is sufficient.

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 high at 88%, so the baseline is 3, and the description adds value beyond the schema. It connects aggregation_level and time_ranges as the required pair, spells out breakdown options as device/country, and clarifies that group_by_entity splits results by campaign/ad_group/ad, which is more concrete than the schema's 'entity_id' phrasing.

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 operation: 'Get attributed conversion totals or daily values' and names the resource endpoint, POST /conversions/insights. It is specific enough to identify the tool's purpose, but it does not explicitly distinguish itself from sibling insights tools like get_campaign_insights or get_ad_insights beyond the conversion-focused wording.

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 concrete usage context: it names the required parameters (aggregation_level + time_ranges), explains when to use breakdown for segmentation, and clarifies what group_by_entity does. However, it does not explicitly state when this tool should be chosen over the other insights siblings, so it stops short of full exclusionary guidance.

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