get_forecast

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state return format, caching behavior, error conditions (e.g., non-US coordinates), whether it's a read-only operation, rate limits, or what the output structure looks like. For a tool with zero annotation coverage, this is a notable gap.

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?

Highly concise with zero wasted words. The description is two short lines plus two parameter examples. Every sentence earns its place, and it is appropriately front-loaded with the core purpose first.

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 tool has an output schema which reduces the need to explain return values, and only 2 parameters with good examples. However, for a tool with no annotations, the description still omits important behavioral context like error handling for invalid coordinates, whether lat/long are validated to US bounds, and any rate limit or API dependency caveats. Adequate for a simple tool but with real gaps.

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 0%, but the description does add modest value by giving example values for both parameters (40.7128 for NYC, -74.0060 for NYC), illustrating the decimal degrees format and expected range. However, it doesn't add constraints like valid ranges, coordinate systems (WGS84 assumption), or relationship between the two params beyond what's obvious from 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 states what the tool does with a specific verb+resource: 'Get a National Weather Service forecast for a US latitude/longitude.' This is clear and specific. However, it does not differentiate from the sibling tool get_alerts, though the tools are clearly distinct enough (forecast vs alerts) that context suggests the distinction is obvious.

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 implies usage context (US lat/long coordinates for NWS forecasts) but provides no explicit guidance on when to use this versus get_alerts, nor any exclusions or prerequisites. The geographic scoping ('US') is useful but the tool name itself carries much of the usage implication.

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