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

Annotations already declare readOnlyHint=true and openWorldHint=true, and the description adds useful context: data comes from FRED, is national and monthly, and has a specific pricing model ($0.002 USDC per successful call via x402, no charge for failures). It does not, however, describe rate limits, update latency, or output structure beyond what the output schema provides.

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 what the tool returns and the source, then adds the key limitation, then the pricing detail. Every sentence contributes directly to correct tool selection and invocation; there is no redundant or filler text.

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?

Given one optional parameter, full schema coverage, an output schema, and annotations covering safety and openness, the description is complete: it states the data source, metrics, geography, frequency, limitations, and billing model. An agent has enough information to decide when to call it and what to expect.

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 sole parameter 'months' has 100% schema description coverage ('Months of history, 1 to 24 (default 6)'), so the schema already does the explanatory work. The description does not add any further meaning about the parameter, which is the baseline expectation when schema coverage is high.

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 names the specific resource (US truck freight demand and capacity proxies), the source (FRED), the frequency (monthly), and the exact metrics returned (Cass shipments/expenditures, implied cost per shipment, ATA tonnage). It also explicitly distinguishes the dataset from lane-level tender rejection and load-board feeds, which separates it from sibling logistics tools like truck_loadboard_rate.

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?

It clearly frames the appropriate use case as national, monthly demand/capacity proxies and explicitly warns that it is not lane-level tender rejection or load-board data. However, it does not name a specific sibling alternative or state a positive 'use this when' condition beyond the implied national-vs-lane distinction.

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