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

Annotations already signal read-only, idempotent, and non-destructive behavior. The description adds value by specifying that the response is a Markdown table of date, rank, and total results scanned, and by clarifying that the timeseries is stored as day-by-day snapshots. No contradiction exists.

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 with no filler. It front-loads the core behavior and then gives a concrete, useful statement of the return format. Every sentence 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?

Between the description, annotations, and output schema, an agent has enough information to call this read-only history tool effectively. The main gap is that the description mentions app, term, and country but omits store as a required dimension, which is a minor contextual omission.

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 has 100% description coverage, so the baseline is 3. The description restates the app/term/country dimensions but adds little param-specific meaning beyond the schema, and it does not mention the required store parameter in the prose.

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 states a precise action: retrieving a historical ranking timeseries for an app, term, and country across snapshots. It clearly differentiates itself from a single-point current-rank lookup and names the data source and content of the response.

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 establishes that this is the tool for historical, day-by-day ranking data, which is enough to point an agent toward this tool when a timeseries is needed. It does not explicitly route away from get_keyword_rank or other sibling tools, but the historical framing is a clear context signal.

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