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

Annotations already establish read-only, idempotent, non-destructive behavior, and the description adds genuinely new context: the 0.01 USDC per-call cost, the aggregation rule ('Mean of the components available that day' — signaling components may be missing), and precise component formulas with thresholds (0.3 → 0, 0.9 → 100). No contradiction with annotations; the cost disclosure alone is high-value for an agent planning calls.

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 dense but every sentence carries substance: cost, scale, scope, aggregation method, and component definitions all earn their place. The core definition is front-loaded before the component breakdown, though the component list makes it slightly longer than strictly necessary.

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?

With no output schema, the description carries the burden of explaining what the tool returns, and it does — the score scale, the mean-of-available-components rule, and the full component formulas give an agent enough to interpret results. It stops just short of stating the specific return envelope (e.g., score plus per-component breakdown), which would make it fully complete.

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 both parameters (day format/default, gpu normalization+example) are already documented. The description reinforces the two-parameter scope ('one GPU model on one day') but adds no format or syntax detail beyond the schema, which fits the high-coverage baseline 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 states a specific computation: a 0-100 capacity stress score for one GPU model on one day, with scale anchors ('0 slack … 100 tight') and a component list. The scoping phrase 'for one GPU model on one day' helps distinguish it from siblings like capacity_history and capacity_board, though it never names alternatives explicitly.

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 cost warning ('Paid (0.01 USDC per call)') tells the agent to invoke deliberately, and the detailed explanation implies when this tool fits (single-model, single-day composite score). However, there is no explicit guidance on when to use this tool versus capacity_headline, capacity_history, or capacity_board, nor any exclusion conditions.

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