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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it's safe. The description adds behavioral nuance: GDPNow is reported, not scored, and does not affect classification; missing data yields status 'unavailable' in staleness_flags, which is distinct from zero. These are valuable behavioral details beyond the annotation hints.

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 compact yet information-dense. It front-loads the indicator list, then explains the GDPNow quirk and the unavailable status. Every sentence adds value, and there is no redundant or filler content. The structure is logical: main content first, then edge cases.

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 parameterless read-only tool with an output schema (signaled), the description covers the returned indicators, the classification, and the special handling of GDPNow and missing estimates. Nothing an agent needs to decide whether to call it or interpret results is missing, given the output schema presumably provides field structure.

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 tool has zero parameters, and the schema coverage is trivially 100%. There are no parameter descriptions needed. Per the rubric, a baseline of 4 is appropriate when there are no parameters, and the description does not need to add parameter semantics.

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 states exactly what the tool returns: a specific set of growth indicators (industrial production, consumer sentiment, yield curve, initial claims, GDPNow) and a classification. This is specific and distinguishes it from siblings like get_inflation_indicators, which are not mentioned but clearly different. The verb 'returns' is implied but the resource is precisely enumerated.

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 implies usage for growth-pillar analysis by naming the indicators, and the sibling list confirms alternatives exist. It does not explicitly say 'use this for growth questions, not for inflation' but the content makes the appropriate context clear. There is no explicit exclusion or alternative routing, but the specificity compensates.

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