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

Annotations already declare readOnlyHint=true, and the description enriches this by disclosing the monthly update cadence, history length, and calculation formula (recent value vs trailing-mean % deviation). It adds context about the data source and output fields, going beyond the structured 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?

Two sentences efficiently pack the metric definition, output fields, data source, calculation, use cases, and update frequency. Every clause contributes information with no filler or repetition.

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 simple read-only tool with no required parameters and no output schema, the description covers all necessary context: return fields, data source, calculation, history, update cadence, and usage scenarios. The optional parameter is fully described in the schema, so nothing essential is missing.

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 single optional parameter 'days' is fully documented in the schema with a clear description, constraints, and tier requirement, so the baseline is 3. The tool description does not discuss the parameter, but since schema coverage is 100%, no additional semantic value is expected.

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 returns a 0-100 US retail-sales momentum score with specific output fields (momentum_score, recent_value, deviation_pct). It names the data source (FRED RSAFS) and the calculation methodology, making it distinct despite the opaque tool name.

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 when to call the tool: when users ask about US consumer spending, retail sales trends, demand acceleration/slowing, or business applications like inventory replenishment and revenue guidance. It does not name alternative tools or provide when-not-to-use conditions, but the context is clear and actionable.

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