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

Annotations already declare readOnlyHint=true, so the description adds useful behavioral context beyond that: data source (FRED UMCSENT, University of Michigan), monthly frequency, 0-100 scale, and computation method (recent value vs trailing-mean % deviation). It does not cover rate limits or auth, but those are less relevant for a read-only monthly indicator.

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?

Three sentences, each earning its place: first defines what is returned and how it is calculated, second gives decision-relevant use cases, third states update frequency. It is front-loaded with the return value and free of fluff.

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, full schema coverage, and a read-only annotation, the description covers purpose, data provenance, and output fields. It omits the Gold-tier requirement and the history return mode, but these are fully documented in the schema, so the context is still complete enough for correct invocation.

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%, with the 'days' parameter fully documented in the input schema. The description does not mention this parameter or add any additional semantic meaning, 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?

Description opens with the specific verb 'Returns' and resource 'US consumer-sentiment momentum score', and details output fields (momentum_score, recent_value, deviation_pct). It clearly distinguishes this tool from siblings by naming the data source (FRED UMCSENT) and the specific domain (US consumer sentiment).

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?

Explicitly states 'Call when the user asks about US consumer sentiment improving or deteriorating, consumer confidence, or household spending mood, or when timing promotional budgets...' This gives clear use cases, but does not mention alternative tools or when not to use this one, so it lacks exclusions.

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