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

Annotations already establish that this is a read-only, idempotent, non-destructive operation, so the description has a lower burden. It adds useful behavioral context by naming the exact metrics returned, defining engagements as likes plus comments plus shares, and specifying per-platform numbers and top 5 posts by views.

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 a single front-loaded sentence that first establishes the scope and then lists the returned metrics. There is no filler, and every listed item appears relevant to an agent deciding whether to call the tool.

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?

With no output schema, the description carries the burden of explaining return values, and it does list the main metrics, per-platform breakdown, and top 5 posts. It could be more complete about the response structure, but it provides enough for an agent to understand the tool’s output.

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 100%, and the single parameter already documents its 7–90 range and default value. The description reinforces that days means the last N days, which adds a little semantic clarity, but it does not provide meaningfully richer details beyond the schema.

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 that the tool returns aggregate totals for a lookback window, and it enumerates the specific metrics returned. It does not explicitly distinguish itself from related siblings such as get_post_analytics, so it falls short of the top score for sibling differentiation.

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 implies usage by saying it returns totals for the last N days, which suggests an aggregate analytics-summary use case. However, it gives no explicit when-to-use guidance, no exclusions, and does not point to alternatives like get_post_analytics or get_best_times.

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