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

Annotations already declare a safe read, and the description goes well beyond them: data freshness (up to an hour old via fetched_at), the null-vs-zero semantic rule with reporting instructions, the TikTok exception where numbers aggregate videos rather than daily account stats, and the one-brand-per-report constraint. That is genuinely new operational context an agent could not infer from the annotations.

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?

It is one front-loaded paragraph that leads with what the tool returns before the caveats. Dense but nearly every clause carries information; the TikTok parenthetical and null instruction are slightly awkward but earn their place.

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?

There is no output schema, so the description must carry the return shape, and it does: metrics, comparison window, and post-level engagement fields. Freshness, aggregation semantics and null handling round out everything needed to interpret results 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 100%, so both parameters are already documented, including the enum and the 'needed when the connection covers more than one' note. The description restates the social_group_id condition and implies platform selects the account, adding little beyond the schema — baseline 3 applies.

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?

It states a concrete resource (one social account's performance) and enumerates exactly what the report contains: followers, a 7-day window with prior-period deltas, and latest posts with their engagement counts. The platform list and the TikTok aggregation caveat further pin it down, so it is clearly not get_brand, list_accounts or get_post.

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 one conditional routing hint — pass social_group_id from list_accounts when the connection covers several brands — which is real guidance. But it never says when to prefer this over siblings like get_post or get_posting_activity, nor any exclusion; usage is otherwise implied by the data it returns.

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