App Store and Google Play reviews

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

Annotations already declare readOnlyHint, openWorldHint and non-destructive behavior, so safety is covered. The description goes beyond them with two genuinely useful operational facts an agent cannot get from structured fields: a hard cap of 500 reviews per call and explicit Apify cost ($0.08/1,000 reviews, $0.05-$0.07 on paid plans).

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?

Four tight sentences, front-loaded with what the tool returns before moving to accepted inputs, filtering, limits and cost. Dense and useful, though some of the input/limit material duplicates the schema rather than earning its 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?

With no output schema, the description correctly enumerates the return fields; it also covers input formats, filtering, sort options, per-call limits and pricing. Nothing an agent needs to invoke it correctly is missing, aside from sibling routing which is scored elsewhere.

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 description coverage is 100%, so every parameter is already documented with defaults, enums, ranges and examples. The description's parameter mentions (input formats, star filtering, country/language, 500 cap) largely restate the schema rather than adding syntax or edge-case meaning, so the 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?

The description names a specific verb+resource (fetch app reviews) and enumerates the returned fields (rating, title, text, date, reviewer, version, votes, developer reply), so the agent knows exactly what it gets. It does not distinguish itself from the sibling analyze_app_reviews, which is the obvious confusion risk.

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?

Usage is implied rather than stated: 'Filter by star rating (e.g. 1-2 stars for complaints)' hints at the complaint-mining use case, and the accepted input formats are listed. But there is no when-to-use/when-not guidance and no routing to analyze_app_reviews for aggregate analysis.

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