AI Capacity Index

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

Annotations already establish readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context beyond those: refresh cadence ('Refreshed Fridays 14:00 UTC'), composite-score composition ('depth + diversity + power'), and a data-availability caveat ('cooling-type signals where facility data carries them'). No contradiction with 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 front-loaded with the core ranking purpose, then supplies return fields, refresh timing, use cases, and exclusions in compact sentences. Every sentence earns its place; there is no repetition of the input schema or annotation fields.

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 tool with two optional parameters, an output schema, and read-only annotations, the description covers what the tool returns, what the ranking means, when it was refreshed, when to use it, and when to use alternatives. Nothing an agent needs to select or invoke it correctly is missing.

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 100%, so the input schema already documents limit and horizon with ranges and defaults. The description adds conceptual framing by tying horizon to '30/60/90 days' and 'deployable_mw,' but it does not add parameter-specific syntax beyond the schema. Baseline 3 is appropriate because the schema carries the parameter-documentation burden.

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 opens with a specific verb and resource: 'ranks data center markets' by 'where 100MW of AI training capacity can land in the next 30/60/90 days.' It is immediately distinguishable from siblings by explicitly stating what it is not ('Do NOT use for a general best-markets ranking... or forward grid-emergence').

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 explicit use contexts ('AI capex planning, GPU cluster siting, hyperscaler deal forecasting') and explicit alternatives with the condition that selects them: use rank_markets for general best-markets ranking and grid_transition_radar for forward grid-emergence. This leaves no ambiguity about when to invoke this tool.

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