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

Annotations already declare this as a safe, read-only, closed-world operation, so the safety burden is lifted. The description adds useful behavioral context by naming the returned metrics and the top post, but it does not disclose auth requirements, rate limits, or output formatting details.

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?

Two tight sentences with no filler. The core operation and return contents are front-loaded, and the second sentence efficiently supplies usage triggers.

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 simple read-only analytics tool with fully documented parameters and a clear annotation profile, the description adequately covers what is returned and when to invoke it. It stops short of detailing output structure or aggregation behavior, but no output schema exists to carry that burden.

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 100%, so both the window and platform parameters are already fully documented in the input schema. The description only refers generically to a time window and adds no syntax, default, or enum context beyond what the schema provides, making baseline 3 appropriate.

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: it retrieves engagement totals for named metrics plus the top post within a time window. It is clearly an analytics/performance tool, distinct from siblings like get_post or get_voice_insights, but it does not explicitly differentiate itself from those siblings.

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?

It gives concrete user-intent examples such as asking how posts performed, how yesterday went, or how they're trending. This provides clear usage context, though it does not state when to use an alternative tool or any exclusions.

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