Review insights & what got worse

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so the safety profile is covered. The description adds genuinely new behavioral context: flat pricing regardless of pages or countries, the versionDelta fallback to a 3-day window, and the shape of the returned analysis.

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 lead sentence front-loads the recommended-use case, followed by a tight inventory of outputs and representative queries. Despite its length, nearly every clause carries distinct information (pricing, platforms, fallback behavior) with no filler.

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 correctly carries the burden of explaining return contents, and it does so in detail. Combined with rich annotations and a fully documented 8-param schema, an agent has everything needed to call 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. The description goes slightly beyond the schema by explaining the versionDelta semantics that underpin since_version (latest vs earlier, with fallback) and the pooling effect implied by countries, adding meaning the schema alone does not convey as a whole.

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 names a specific verb (analyses reviews) and enumerates exactly what is returned: rating distribution, per-version averages, top complaint phrases, versionDeltas, and sample quotes. It positions itself as 'best first call for any question about an app's user feedback,' which implicitly separates it from the raw-listing and comparison 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 trigger questions ('why are users unhappy with X', 'what broke in the last update') and points to search_apps for obtaining ids. However, it never explicitly excludes siblings like get_app_reviews (raw reviews) or compare_apps (cross-app comparison), leaving the agent to infer the routing.

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