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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: the default operating-only filter, the capacity floor, and the effect of include_minor=true. It does not mention pagination or rate limits, but the annotations carry the main burden.

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 compact and front-loaded: it opens with the resource, then data fields, then example questions, then parameter guidance. Every sentence earns its place with no repetition of schema 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 read-only query tool with no output schema, the description covers the dataset, fields, example questions, and key parameter behaviors. It does not explain the return format or pagination, but the annotations and schema cover the safety and parameter basics, and the example questions make the tool's purpose fully clear.

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 56%, so the schema documents fuel, limit, status, include_minor, and min_capacity_mw. The description adds meaning by explaining the default operating-only filter and capacity floor, and by giving example usage for fuel. It does not fully compensate for the undocumented lat/lon parameters, but those are self-explanatory bounding-box coordinates.

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 a specific verb ('Query'), a precise resource ('unit-level power plants from the Global Energy Monitor — Global Integrated Power Tracker (GIPT)'), and enumerates the data fields and example questions. It clearly distinguishes this tool from sibling query tools by naming the exact dataset and scope.

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 example questions and explains when to use include_minor=true and fuel. It does not explicitly name sibling alternatives or state when not to use this tool, but the context is clear enough for an agent to select it for power-plant queries.

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