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

No annotations are present, so the description carries the full burden of behavioral disclosure. It only restates the high-level action and output content; it doesn't reveal return shape, aggregation, timezone/date handling, or account scoping behavior.

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?

Single sentence with high signal-to-noise, front-loaded with the action and key context. No wasted words.

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 tool with no annotations and no output schema, this is too sparse. An agent is left without return-value structure, parameter semantics, or selection criteria relative to sibling tools.

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?

With 0% schema description coverage, the description should compensate by explaining date_from, date_to, and account_ids. It establishes a date-range concept but doesn't specify formats, defaults, or how account_ids affects results.

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?

States the verb 'Get', the resource 'engagement trend', and lists metric types and a date range. It clearly describes the core action but doesn't distinguish itself from sibling metrics tools like get_post_metrics or get_stats_overview.

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?

Does not specify when to prefer this tool over sibling metrics/trend tools, nor any exclusions or prerequisites. The date-range mention only implies the use case rather than providing explicit guidance.

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