get_climate_context

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

No annotations present, so description must disclose all behaviors. It specifies 'land only', data sources (ERA5, WMO normals), and query format requirements. It also transparently notes that alternative phrasings will fail, giving clear behavioral expectations.

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?

Description is two efficient paragraphs: first states core purpose and data context, second provides vital usage guidelines. Every sentence adds value, no redundancy. Front-loaded with the essential function.

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 tool's single parameter and presence of an output schema, the description covers all needed aspects: what it does, when to use, how to phrase queries, and failure modes. Nothing essential is missing.

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% coverage, but description compensates thoroughly by detailing the exact required structure of the 'query' parameter, including multiple valid patterns and explicit examples. This adds essential semantic meaning beyond the bare schema.

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 clearly states it provides statistically rigorous weather/climate context using forecast and historical percentiles. It explicitly contrasts with simple weather queries by emphasizing 'how unusual' conditions are, effectively distinguishing its purpose from basic weather tools.

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?

Explicitly states when to use: needing unusualness relative to history. Provides exact query formats and warns against failing phrasings. No sibling tools exist, but description fully covers usage context and constraints.

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