spatial_link

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

No annotations are provided, so the description carries full burden. It describes the spatial join operation and that it computes mean values. However, it does not disclose potential edge cases (e.g., no overlapping regions) or performance implications. Adequate but not rich.

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 well-structured: one-line purpose, brief explanation, use cases, then clear Arg list and Returns. It is front-loaded with the key action and every sentence adds value.

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 8 parameters (7 required) and an output schema, the description explains all inputs and the output format. It covers the spatial join, aggregation method, and administrative regions. The presence of an output schema reduces the need to detail return values.

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 0%, so description must compensate. The 'Args:' section explains each parameter with examples and allowed values for datasets. It adds meaningful context beyond the schema's type definitions.

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 starts with 'Aggregate raster climate data to administrative regions (NUTS3 or country).' This is a specific verb+resource that clearly states the tool's purpose. It distinguishes from siblings like query_climate (likely returns raw data) and geocode (address lookup).

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 says 'Useful for regional comparison, portfolio screening, or joining climate data with official statistics by administrative area.' This provides clear usage context. It implies when to use it (for spatial aggregation) versus alternatives, but does not explicitly mention when not to use or name sibling tools.

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