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

Beyond the readOnly/idempotent annotations, it discloses that numbers are from the last sweep rather than live, that each account carries its measurement time, and that unmeasured accounts show no metrics rather than zeroes. It also reveals output ordering, all of which materially affects how an agent interprets results.

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?

Three short sentences front-load the core output and then add necessary ordering and freshness caveats. There is no filler or repetition of annotation/schema content.

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 an output schema present, the description need not enumerate return fields; it covers the critical context around staleness, missing-data semantics, and ordering. A simple one-parameter tool with strong annotations and schema leaves no meaningful gap.

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?

The only parameter, period, has a 100%-coverage schema description explaining the window, default, and null-change semantics. The tool description merely echoes 'over the period,' so the schema carries the meaning; baseline 3 is 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 exactly what the tool reports: per-account followers, posts, total likes, following, and period-over-period movement, with ordering by followers. The title supplies the verb ('Read') and the account-scoped resource distinguishes it from posts_performance and accounts_list.

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 makes its use case clear—reading account performance over 24h/7d—but never states when to prefer it over siblings such as accounts_list or posts_performance, nor does it offer exclusions. The context is reasonably inferable, so it earns an implied-usage score rather than 2.

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