get_forecast

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

Without annotations, the description carries the burden. It explains a non-obvious behavior: dates are interpreted as local dates at the destination, not server dates. This provides useful transparency. It does not mention side effects, but as a read-only forecast tool, none are implied.

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 and informative, using examples and clarifications without unnecessary repetition. It flows logically from purpose to usage nuances to edge cases, 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?

The description covers the tool's purpose, key behaviors, and relationship to a sibling tool. Since there is no output schema, it does not need to detail return structure, and the input parameters are fully described in the schema. An agent has sufficient information to decide when and how to call the tool.

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?

The schema already provides descriptive text for all four parameters (startDate, endDate, location, days), covering their format and meaning. The tool description adds context about default behavior when no dates are given, but this does not enhance the understanding of individual parameters beyond the schema, so it remains at the baseline of 3.

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 daily weather forecasts with highs, lows, rain, and wind. It distinguishes itself from get_typical_weather by explicitly mentioning that tool for longer-range historical data, making the purpose unambiguous relative to at least one sibling.

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 gives concrete guidance on when and how to use the tool: provide dates if known, otherwise the anchor is today at the destination. It explicitly directs users to get_typical_weather for trips further out. However, it does not explicitly contrast with get_hourly_forecast, leaving some ambiguity about when daily vs. hourly is appropriate.

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