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

Annotations declare readOnlyHint=true, and the description reinforces non-destructive behavior. It adds meaningful context about the data source (monthly FRED series), the exact weighting formula, the high-stress threshold, and the update frequency ('Updates: monthly'), which informs the agent about data recency and interpretation.

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 compact and front-loaded: the first sentence conveys the core value and composition; the second sentence covers usage guidance and update cadence. Every sentence provides distinct value with no filler.

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?

The description explains the returned fields (score, trend, load_level, composite_z_score, driver YoY rates), the composite methodology, the threshold interpretation, and the appropriate usage contexts. The optional history parameter is fully specified in the schema, so the description's omission is acceptable. Without an output schema, the description still gives the agent enough knowledge to invoke and interpret the tool.

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 the single optional `days` parameter fully described in the schema. The tool description does not mention the parameter or add semantics beyond the schema, so it meets the 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 opens with a specific verb ('Returns') and a measurable resource ('0-100 digital infrastructure load index'), specifies its composition (electricity generation 60% + data-processing PPI 40% YoY z-scores), lists the output fields, and includes a threshold (>70=high stress). This clearly distinguishes it from other adw tools as a specialized infrastructure load indicator.

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 explicitly lists trigger scenarios: 'data center demand, cloud capacity strain, compute cost pressure, or infrastructure buildout' and decision contexts: 'timing capacity expansion, reserved-instance purchases, or auto-scaling budgets'. It does not mention when not to use the tool or name alternatives, but provides strong situational guidance.

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