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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the description is not carrying the safety burden. It still adds genuinely useful context beyond them: data reflects 'as GrowthDept last read them' (a freshness/staleness caveat) and Google Play only surfaces reviews with words from the last 7 days, which is a real coverage limitation an agent would otherwise misread as completeness. It does not say what happens when the business is not a mobile app or how many reviews are returned.

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?

A single sentence with the precondition front-loaded, then the returned fields, then the Google Play caveat. Since there is no output schema, the field enumeration earns its words rather than being redundant. No filler or hedging.

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 and no parameters, the description takes on the burden of describing return content, and it does so field by field while flagging the 7-day Google Play window and the cached-read freshness. Remaining gaps are minor: no ordering guarantee, no indication of result volume, and no stated behavior for a non-app business.

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 tool takes zero parameters and the schema is an empty object, so there is no parameter meaning to add and the baseline of 4 applies. The description correctly avoids inventing filters, though the absence of any filtering language is itself worth knowing.

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?

Names a specific resource (neueste App Store and Google Play reviews) and specifies the exact fields returned: id, stars, words, existing store reply, and drafted reply. The scope is narrowed to 'a business that is a mobile app,' which tells an agent the precondition. It does not name or differentiate itself from siblings such as app_store_listing, check_app_stores, or draft_review_reply, so it stops short of a 5.

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: 'For a business that is a mobile app' signals the applicable context, but there is no explicit when-to-use or when-not-to-use guidance. An agent must infer that app_store_listing covers listings rather than reviews and that draft_review_reply acts on the drafted replies mentioned here. No alternatives are named.

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