get_area_average

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

Description lacks behavioral traits such as idempotency, side effects, or authentication needs. It only explains output structure and parameter defaults, which is minimal for a tool with no annotations.

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, front-loaded with purpose, and every sentence adds value. No redundancy or fluff.

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?

Output schema exists (not shown) but description explains return structure adequately. Parameter coverage is sufficient for operation, though lacks error or behavior details.

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 has 0% description coverage, but description adds meaning by explaining radius_km controls the area and forecast_days sets the horizon. However, lat and lon are not explicitly described, though implied by context.

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?

Description uses specific verb 'Get' and resource 'pollen aggregates over a radius' and distinguishes from siblings by framing it for higher-level questions, clearly indicating its focus on area aggregates over time.

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?

Description explicitly states when to use the tool with examples ('is tree or grass pollen worse this week?') and implies it is for area-based queries rather than point-specific data, but does not directly mention when not to use or compare to siblings like get_pollen.

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