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

Annotations already indicate readOnlyHint=true and openWorldHint=false. The description adds valuable context: data source (FRED DGORDER), monthly frequency, history start year, calculation basis, returned fields, and update cadence ('Updates: monthly'). This goes well beyond 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 two sentences. The first sentence packs the core function, data source, formula, scale, history, and output fields. The second sentence gives concrete usage triggers and update frequency. No filler, every sentence earns its place.

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 covers purpose, source, formula, output fields, usage triggers, and update frequency. The optional 'days' parameter is fully documented in the schema, so no critical invocation context is missing. Output schema is absent, but the description compensates by naming return fields.

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 description coverage is 100% for the single optional 'days' parameter, fully explaining its behavior and tier requirement. The tool description itself does not elaborate on parameters, 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 'Returns a 0-100 US durable-goods orders momentum score' with the data source (FRED DGORDER), calculation method (recent vs trailing-mean % deviation, scaled), history since 1996, and output fields (momentum_score, recent_value, deviation_pct). This is specific and distinct from other likely indicators in the catalog.

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 the user asks about business capex acceleration, capital spending, manufacturing demand, factory or equipment orders, or the industrial cycle, or when timing capacity expansion, industrial equipment sales, or capex-cycle positioning decisions.' It does not, however, provide when-not-to-use guidance or mention alternative sibling tools, so it stops short of a 5.

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