ai_capacity_index

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral context: refresh schedule ('Refreshed Fridays 14:00 UTC'), return fields (facility_count, operator_count, etc.), and the specific question it answers. No contradictions; adds detail beyond 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 approximately 80 words, front-loaded with purpose and key details, followed by return fields and usage guidance. Every sentence is informative with no redundancy or fluff, achieving high efficiency.

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?

Despite no output schema, the description enumerates return fields (facility_count, operator_count, etc.) and clarifies the composite score. Parameters are fully explained in schema. The description includes refresh schedule, explicit use cases, and alternative tools, making it complete for a query tool of moderate complexity.

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% with descriptions for both 'limit' and 'horizon' parameters. The description does not add explicit parameter details beyond mentioning '30/60/90 days' which aligns with the horizon parameter. Since schema already fully documents parameters, the description provides minimal added semantic value, resulting in a baseline score of 3.

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 uses the specific verb 'ranks' and resource 'data center markets', clearly defining the scope as 'where 100MW AI training capacity can land in 30/60/90 days'. It explicitly distinguishes from siblings like 'rank_markets' and 'grid_transition_radar', making purpose unambiguous.

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 provides explicit when-to-use guidance ('AI capex planning, GPU cluster siting, hyperscaler deal forecasting') and when-not-to-use ('Do NOT use for a general best-markets ranking...or forward grid-emergence'), naming alternative tools. This leaves no ambiguity about appropriate contexts.

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