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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds real value beyond that: the 'Pro:' tier signal and the caveat that rankings are not downloads or revenue and that absent/unavailable charts remain unknown, which sets correct expectations about data meaning and gaps.

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?

It is compact and front-loads the returned data categories, with the operational hint and the semantics caveat following. Sentences are dense with information, though the 'Pro:' fragment is slightly cryptic and no words are wasted overall.

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 usefully enumerates the return categories, which covers the output side reasonably. But for a 6-parameter query tool with 0% schema coverage and no annotations on parameters, the near-total silence on days/chart/limit/offset leaves the definition incomplete for correct invocation.

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 0%, so the description carries the burden of explaining the six parameters, yet it only touches symbol (omit for global) and gestures at country via 'country spreads'. days, chart, limit and offset are entirely unexplained, leaving the agent to guess at their semantics despite the tool documenting them nowhere else.

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 enumerates the specific data the tool returns – app chart rank, rank velocity, rating-count growth, country spreads, ownership mapping, source evidence – so an agent knows it is an app-attention data query. It is clear and specific, but never names or contrasts itself with close siblings like apps.rank_history or market.attention, so sibling differentiation is missing.

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 provides one concrete usage directive – 'Omit symbol for the global board' – which tells the agent how to switch between scoped and global queries. However, there is no guidance on when to choose this tool over apps.rank_history or market.attention, and no prerequisites or exclusions, so usage is only partially implied.

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