get_weather

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

No annotations are provided, so the description carries full burden. It adequately describes the return format (formatted weather summary with temperature, wind speed, humidity) and provides example values. It is transparent about being a read operation, though it does not cover error handling or units.

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 concise: a single paragraph with clear 'Args' and 'Returns' sections, front-loaded with purpose. No unnecessary words.

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?

With a simple input schema (2 required numbers) and the presence of an output schema, the description covers the essential information. It effectively explains what the tool does and what it returns, making it complete for agent use.

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%, meaning the schema provides no descriptions. The description adds specific examples (e.g., 52.52 for Berlin) for latitude and longitude, adding meaningful context beyond the schema's type and title.

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 it retrieves current weather data using latitude and longitude, which is a specific verb+resource, and distinguishes well from unrelated sibling tools (get_joke_of_the_day, predict_age_by_name).

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?

No explicit guidance on when to use this tool vs alternatives. However, the sibling tools are unrelated, so usage context is implicitly clear, but no exclusions or alternatives are mentioned.

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