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

Annotations already declare readOnlyHint=true, so the safety profile is known. The description adds useful behavioral context: a 12-month rolling window, aggregate KPIs, and data freshness, which tells the agent what kind of data to expect without contradicting the annotations.

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 two compact sentences with no filler. The first sentence front-loads the metric scope and the second gives actionable usage guidance, so every part earns its place.

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?

With no parameters and no output schema, the description adequately covers what the tool returns and when to call it. It specifies the KPIs, the time window, geographical scope, and data-freshness inclusion, which is enough for an agent to decide and invoke 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?

The tool has zero parameters, so there are no parameter semantics to clarify. The schema fully covers the parameter surface, and the description's mention of city-wide scope and time window is sufficient contextual orientation.

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 names a specific verb and resource ('City-wide Dubai sales KPIs') and enumerates the exact metrics returned. This clearly distinguishes it from location-, building-, and trend-specific sibling tools.

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?

'Good first call for broad questions' gives clear guidance on when to use the tool. It does not explicitly mention alternatives, but the city-wide scope implies that more specific questions should use sibling tools like get_building_stats or get_location_stats.

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