get_hourly_forecast

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

With no annotations, the description carries the full burden. It discloses that the tool returns 24 rows, requires the date to be within the 16-day forecast horizon, and interprets the date as local at the location. This is strong transparency, though it doesn't detail error handling for out-of-range dates.

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 and well-structured, with the core purpose stated first, followed by usage guidance and constraints. Every sentence adds value, and the length is appropriate for the tool's complexity.

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?

The description is self-contained: it explains the return granularity, usage scenarios, alternatives, and date constraints. Even without an output schema, an agent knows what to expect and how to invoke it correctly.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful context to the 'date' parameter by stating the 16-day horizon and local-date interpretation, which enhances the agent's understanding beyond the 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?

The description clearly states the tool provides an hour-by-hour forecast for one day, specifically focusing on when rain arrives. It differentiates from the sibling get_forecast by emphasizing the single-day scope and the hourly granularity.

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 this tool (when the day matters more than the week) and when not to, pointing to get_forecast for multi-day outlooks. Also warns about the 24-row return being wasteful for week-long questions.

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