Get Ad Account Insights

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds substantial behavioral detail by enumerating the full set of returned metrics (performance, cost, engagement, conversions, video, quality), which goes beyond the bare read-only annotation. It does not contradict any annotation, and it gives the agent concrete expectations about the output contents.

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 organized into Args and Returns sections, which is helpful, but it is quite verbose – the Returns section lists over 30 metric names, many of which are self-explanatory and could be summarized. It duplicates some parameter info already fully covered by the schema. It is not front-loaded beyond the first sentence, and the length may reduce skimmability.

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 the tool's complexity (multiple filtering options and a rich set of return metrics), the description covers the arguments and return metrics thoroughly. It omits mention of the response_format parameter, but that is fully described in the schema with a default of 'markdown'. It also does not discuss rate limits or required permissions, but for a read-only tool with annotations confirming safety, this is acceptable. The description provides enough for an agent to call it correctly.

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 (83%), so the schema already documents parameters. The description adds value by providing an example for ad_account_id (act_123456789) and explicitly stating that 'since' overrides 'date_preset' – a behavioral nuance not present in the schema. It also lists example breakdown dimensions, though the schema already enumerates them. This exceeds the baseline for high-coverage schemas.

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 'Gets performance insights for a Meta ad account' – a specific verb, resource, and scope. It distinguishes itself from sibling insight tools (e.g., meta_get_campaign_insights, meta_get_ad_insights) by explicitly naming 'ad account', though it does not name alternatives directly.

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 no guidance on when to use this tool instead of the many insight-related siblings (campaign, adset, ad, Instagram account). It does not mention any exclusions or conditions. The agent must infer usage from the resource type alone.

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