sg_rainfall

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

With no annotations, the description must disclose behavioral traits itself. It adds context about freshness ('real-time') and coverage ('76 weather stations'), but does not describe output format, update intervals, or any potential caveats. The read-only nature is implied by 'Get', but not explicitly stated.

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 one concise sentence with no filler, front-loading the purpose and key attributes. Every part is informative.

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 zero-parameter read tool, the description covers the key aspects: what data, where, freshness, and coverage. It omits the response structure, but given the simplicity and the lack of an output schema, the description is largely adequate.

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 tool has zero parameters, so the schema is trivially complete. The description adds no parameter-specific behavior, but none is needed; the baseline for zero-parameter tools is 4.

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 retrieves real-time rainfall readings across Singapore, naming the specific resource and geographic scope. This distinguishes it from sibling tools like sg_weather or sg_air_quality, which cover other data domains.

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 for rainfall-specific queries, with 'real-time rainfall readings' making the use case explicit. However, it does not explicitly mention alternatives or exclusions, such as 'for general weather use sg_weather', leaving that distinction implicit.

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