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

Annotations already establish the tool is read-only, idempotent, and non-destructive. The description adds useful context by specifying that it returns a Markdown table of date, rank, and total results scanned per day, and clarifies it is based on day-by-day snapshots stored by Appskyline. No contradictions with annotations are present.

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 description is two sentences, no filler, and the key action is front-loaded in the first sentence. The second sentence names the concrete return format only, so every word earns 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?

Given the read-only annotations, complete input schema, and the existence of an output schema, the description gives enough information for an agent to call and interpret the tool. It covers scope, time granularity, and the Markdown table output without requiring excessive inference.

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 input schema gives full descriptions for all parameters, including terms, store enums, country codes, and the limit behavior. The description adds no new parameter-level detail beyond restating the app, term, and country context. Since schema coverage is 100%, the baseline of 3 is appropriate.

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 and resource: it gets the historical ranking timeseries for an app, term, and country across day-by-day snapshots. This clearly differentiates it from sibling tools like get_keyword_rank by emphasizing 'historical' and 'day-by-day' data. The return format is also stated, leaving no doubt what the tool does.

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 clearly implies this is for historical rank trends rather than current rank lookup, which is enough to distinguish it from get_keyword_rank. However, it does not explicitly say 'use this instead of X' or state exclusions, so it stops short of giving full decision criteria.

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