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

Annotations already establish that this is a safe, read-only, idempotent, non-open-world operation. The description adds substantial behavioral context by disclosing the returned market signals: dated project counts at 500 kW+, permitted/building status, MW by stage and capacity basis, top developers, grid connection policy condition, current-hour carbon intensity and power price, and applicable data-centre rule counts.

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 front-loaded with the core purpose and then adds use examples and supported market lists. It is dense and the first sentence is long, but every part contributes useful selection or input guidance, with little wasted wording.

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 one-parameter aggregate market tool with no output schema, the description is complete enough: it explains the market parameter, lists valid geographies, and enumerates the main return-value categories. An agent can decide whether to call it and what kind of answer to expect.

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 schema already documents the single market parameter at 100% coverage. The description meaningfully extends this by enumerating supported metros (London, Frankfurt, Paris, Amsterdam, Dublin, Milan, Madrid, Oslo) and a long list of supported countries, reducing ambiguity about valid values.

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 a specific resource and scope: a dated European data-centre market overview covering project counts, MW by stage, developers, grid connection conditions, carbon intensity, power price, and rules. It is distinguishable as an aggregate overview, though it does not explicitly name sibling tools such as grid_connection_status or grid_carbon_and_price_now as alternatives.

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 concrete use cases such as "data centres in Germany", "Frankfurt data centre market", and "who is building data centres in Spain", which clearly indicates when the tool applies. It does not explicitly state when not to use it or name the more specific sibling tools for individual metrics.

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