get_current_temperature

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

With no annotations provided, the description fully bears the behavioral disclosure burden. It discloses return format (temperature, Swiss German description, swimming suitability) and implies a read-only operation. It could add more about data freshness or error conditions, but the provided information is sufficient for safe invocation.

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 three concise sentences with no redundancy. Each sentence provides essential information: action, use case, and output details.

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?

For a simple tool with one parameter and an output schema, the description is fairly complete. It covers purpose, usage guidance, and output format. Minor gaps like error handling or data freshness are not critical given the tool's simplicity.

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 100% with a descriptive parameter for 'city' that includes default and examples. The description adds no additional parameter semantics beyond the schema, so a baseline score of 3 is appropriate.

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's purpose: 'Get current water temperature for a city.' It distinguishes from sibling tools by focusing on quick temperature checks and water-specific queries, contrasting with other tools like 'compare_cities' or 'get_forecasts'.

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 advises use for 'quick temperature checks and simple how warm is the water? questions,' implying when to choose this tool. It does not explicitly name alternatives or state when not to use, but the context of sibling tools provides clear differentiation.

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