Get Global Power

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

Annotations already signal read-only, idempotent, non-destructive. The description adds meaningful behavioral context: the dataset scope (182k units, 170+ countries), the semantics of pipeline=true being exactly the forward set (announced + pre-construction + construction), and the return shape (summary of total MW by fuel + count by status plus largest units). It does not contradict 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?

Though fairly long, every sentence earns its place: use-case scoping, dataset scale, filter options, return summary, example calls, and explicit exclusions. The key 'when to use' instruction is front-loaded, and the negative routing is clearly placed at the end. Formatting with bold and code examples improves scannability.

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?

Given 7 optional parameters, no enums, and a large sibling set, the description covers the full decision space: what data is available, how each important filter behaves, what the response contains, and which related tools to use instead in specific situations. An output schema exists, so not detailing every return field is acceptable. An agent has everything needed to invoke this tool 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?

Schema coverage is 100%, but the description still adds value by explaining the union semantics of comma-separated fuel values, the exact bbox format (minLng,minLat,maxLng,maxLat), the pipeline filter collapsing multiple statuses, and showing real examples of country and fuel values. This goes well beyond the schema's one-line descriptions.

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 defines a specific verb plus resource: 'power plants/units WORLDWIDE or in a NON-US country' with both operating and forward pipeline. It explicitly differentiates from US-focused siblings by naming get_grid_intelligence, get_grid_scoreboard, and get_power_pipeline as the alternatives, so an agent can select this tool without ambiguity.

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?

It gives explicit when-to-use context (worldwide/non-US, all fuels, including pipeline) and explicit when-not-to-use with named alternatives for US grid telemetry/headroom and US planned-generator feeds. It also provides example queries and a concrete recommended call ('Try: get_global_power country=India pipeline=true').

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