get_ad_account_insights

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

No annotations are provided, so the description bears the full behavioral disclosure burden. It does add two genuinely useful traits: attribution for the current local day is preliminary, and results are paginated via limit/after/before. It does not mention return format, default granularity when unspecified, or rate limits, but for a read-style reporting tool the disclosed caveats are meaningful and non-obvious.

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?

Four short sentences, purpose front-loaded first, and each sentence earns its place: purpose, data-quality caveat, breakdown pattern, pagination. There is no redundancy, filler, or repetition of schema content.

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?

For a 13-parameter tool with no output schema and no annotations, the description is reasonably thorough—it covers purpose, a data-quality caveat, breakdown usage, and pagination. It leaves gaps around response shape, default behavior when no time_ranges/time_granularity are supplied, and prerequisites, which matter more because there is no output schema to fill those in.

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 77%, so the schema already documents most parameters well. The description adds modest value beyond the schema by explaining how parameters combine ('Use time_ranges + fields + segments for breakdowns') and by associating pagination cursors with the limit/after/before fields, but it does not fully compensate for the ~23% of parameters lacking schema descriptions.

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 and resource ('Get ad account insights') plus an aggregation behavior ('by time granularity'), which is clear and unambiguous. It implicitly separates itself from sibling insights tools (get_campaign_insights, get_ad_group_insights, get_ad_insights) via the resource scope, but it never names or contrasts them, so differentiation is implicit rather than explicit.

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 offers parameter-composition guidance ('Use time_ranges + fields + segments for breakdowns') and flags pagination, which implies when the tool's features are useful. However, it provides no explicit guidance on when to choose this tool over the sibling insights tools (campaign/ad group/ad/conversion level) or any exclusions, leaving tool-selection context to be inferred.

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