Regional distribution

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

Annotations already include readOnlyHint and openWorldHint, so the description's additional details add value: it specifies the 30-day lookback, explains affinityIndex interpretation, and clarifies regionMode grouping. No contradictions.

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 three concise sentences: first introduces the tool and time range, second explains output fields, third covers parameters and mapping. No redundancy, well front-loaded.

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?

Despite no output schema, the description covers all necessary context: parameter semantics, output row structure, and cross-reference to list_regions for id mapping. For a read-only tool with two params, it is complete.

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 coverage is 100%, baseline 3. The description adds extra meaning for regionMode by explaining the 'all', 'cities', and 'regions' options with context (only cities vs. only oblasts/subjects). This is more than the enum enumeration.

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 clearly states the tool returns 'how demand for a phrase is distributed across regions' and specifies output fields (region id, count, share, affinityIndex). This distinctively separates it from siblings like list_regions (which maps ids to names).

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 implicitly indicates when to use (when regional distribution data is needed) and explains the regionMode parameter. It also references list_regions for mapping ids, but does not explicitly state when not to use or provide exclusions against siblings like top_requests.

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