get_account_insights

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

With no annotations provided, the description carries the full behavioral burden. It adds useful operational details: default metric list, supported period values, and the note that exact metrics vary by Graph API version with Meta errors naming the correct metric. However, it does not disclose authentication requirements, account-resolution behavior, or any side effects beyond the implicit read operation.

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 compact and every sentence earns its place. The core purpose is front-loaded, and the parameter notes are terse but information-dense with no filler or redundancy.

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?

The tool has an output schema, so return-value documentation is not required. However, the description fails to clarify the 'account' parameter, which is nullable and defaults to null, and gives no guidance on default-account behavior or when account targeting is needed. These gaps make the definition partially complete for a 3-parameter tool.

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 does explain the values and defaults for 'metrics' and 'period', but the 'account' parameter is left completely undocumented. This partial compensation is better than nothing but still leaves a meaningful gap.

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 identifies the tool as account-level analytics and enumerates the concrete metric types covered (reach, impressions, profile views, follower count). It distinguishes itself from media-level and audience-level siblings through the 'account-level' framing, though it doesn't explicitly name those alternatives.

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?

No explicit guidance is given for when to use this tool versus alternatives like get_media_insights or get_audience_insights. The phrase 'account-level analytics' implies the use case, but the description never states exclusions or conditions that would route an agent to a sibling tool.

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