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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely non-obvious behavior beyond that: the statistics are precomputed asynchronously, so results can be stale or empty on new publications.

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?

Purpose is front-loaded in the first sentence and the second sentence carries only substantive detail (dimensions, enums, caveat). The list-heavy second sentence is dense but every element maps to an actual output field, so little is wasted.

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 describing return values, and it does: per-country/state counts, totals of countries and states with subscribers, and overlapping publications. Combined with the async caveat, an agent has enough to call and interpret it 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 the baseline is 3, but the description adds value by giving concrete ISO examples (us, gb) and state codes (ny, ca) and by framing paid_only as 'all subscribers or paid only' rather than merely restating the flag. It stops short of explaining how the counts are aggregated.

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 opening sentence names the resource and the two distinct outputs (subscriber geography and overlapping publications), and the second sentence pins down the exact surface: 'Returns Analytics > Statistics > Audience'. An agent can distinguish this from list_subscribers or get_publication_stats from the text alone.

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 establishes the context in which the tool makes sense (audience geography / reader overlap) and closes with a caveat that effectively says when not to bother: a new publication has empty lists while Substack computes in the background. It does not, however, name alternative sibling tools for related questions.

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