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

Annotations already declare readOnlyHint=true, so the read-only nature is known. The description goes beyond by revealing the calculation window (recent-3mo vs trailing-baseline), underlying data sources and weights, monthly update cadence, and the list of returned fields. This adds meaningful behavioral context without contradicting the 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 three sentences long, front-loaded with the core output and methodology, followed by explicit use cases and update frequency. Every sentence adds distinct, valuable information with no filler or repetition of schema/annotation content.

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 data index tool with no output schema, the description adequately explains the output fields and the index's construction. It covers frequency, scope, and use cases. However, it does not explicitly interpret the index direction (e.g., higher vs lower meaning) or address potential edge cases like the 'days' history parameter behavior, though the schema covers that.

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% because the single optional 'days' parameter has a thorough description including type, range, and the Gold tier requirement. The tool description itself does not add parameter details, but the schema already carries the full semantic weight, so the baseline 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 opens with a specific verb ('Returns') and clearly defines the resource: a 0-100 US freight activity and regulatory-demand index. It details the methodology (z-scores of ATA tonnage, BTS Services Index, border crossings with weights 45/35/20) and names the output fields (score, percentile, trend, top_drivers, source_lineage), distinguishing it from any generic sibling tool.

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 states when to call the tool: 'Call when the user asks about freight demand, trucking activity, carrier utilization, truck tonnage, or cross-border freight, or when timing spot surcharges, load-board pricing, or dispatch capacity.' This is clear context, though it does not mention when not to use it or point to alternative tools.

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