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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds genuine behavioral value by disclosing the return envelope (aggregate totals, recent daily rows, top territories) and the important per-store caveat that metric names differ by store. This is a real gotcha that would trip an agent unaware of it.

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 sentences, each earning its place: purpose statement, return-value preview, and the per-store metric-naming caveat. There is no redundancy, filler, or repetition of schema content, and the verb-priority front-loading makes the purpose immediately clear.

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?

The description is largely self-sufficient: it explains what the tool returns, scopes it to the required app/store identity, and flags the most likely source of confused expectations (store-specific metric names). The output schema explains the return values, and annotations cover the safety profile. A small residual gap is that the interplay among days, startDate, and endDate is left entirely to the schema without a hint about precedence.

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 the schema carries fully documented parameters (appId, store, days, startDate, endDate). The description confirms the app/store/date-window scope but adds no new parameter-level meaning beyond what the schema already provides. A baseline 3 is correct for a schema that does the heavy lifting.

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 uses a specific verb ('Summarize') with a concrete resource and scope: downloads, installs, uninstalls, crashes, and other store-reported engagement totals for one Appskyline app over a date window. The metric list and the single-app/single-store scope make it readily distinguishable from siblings such as keyword tools, list_apps, and store-listing tools.

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 gives clear context for when the tool applies: pulling store-reported engagement totals for a single app over a date range. There are no explicit exclusions or named alternatives, but the metric scope ('downloads, installs, uninstalls, crashes') plus the per-store reporting caveat is enough for an agent to route to this tool rather than a keyword or metadata tool.

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