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

Annotations already mark readOnlyHint=true, so the description need not dwell on safety. It adds meaningful context: the metric is derived from YoY growth, z-scored against a 33.5-year baseline, includes trend and z_score, updates weekly, and 'leads equipment orders and industrial hiring.' This goes beyond a simple read-only disclosure.

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 three sentences with distinct roles: definition, use-case guidance, and update frequency. It is front-loaded with the core output and contains no filler or redundancy.

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 one optional parameter and no output schema, the description covers the purpose, main output fields, methodology, and relevant use cases. It does not elaborate on the 0-100 scale interpretation or output structure, but the key information is present.

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 input schema has 100% coverage for the single optional 'days' parameter, including its behavior and Gold tier requirement. The tool description does not add parameter-specific details, so the baseline score of 3 applies.

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 the tool's function: 'Returns a 0-100 US manufacturing-construction boom score' with detailed methodology (YoY growth, z-scoring). It also lists standard output components (trend, z_score, composite baseline stats). The specific terminology distinguishes it from broader economic indices.

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?

Provides explicit triggers: 'Call when the user asks about fab/factory buildout, reshoring, CHIPS-era capex, or industrial construction momentum' and when timing equipment-supply, construction-bid, or logistics decisions. It does not name alternatives or state when not to use, but the use cases are precise enough to guide selection.

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