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

Annotations already declare readOnlyHint=true, and the description adds valuable context beyond that: monthly update cadence, z-scoring vs. 36-month window, the 0-100 scale with 50=neutral, and the list of returned fields. It doesn't explain every field's semantics, but for a read-only indicator the safety profile is handled by 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 dense but purposeful, with a clear sequence: what it returns, when to call it, and update frequency. The first sentence is a long parenthetical-heavy construction, but every clause adds substantive information and there is 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?

Given no output schema, the description compensates well by explaining the score's meaning, data source, methodology, and use cases. The returned fields are listed by name, and most are self-explanatory (e.g., core_cpi_yoy_pct, real_wage_gap_pct), though 'trend' is left vague. Overall, an agent has enough context to invoke the tool correctly.

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 `days` is fully described in the schema, including optionality, range, behavior (daily history vs. snapshot), and the Gold tier requirement. The description itself does not mention this parameter, but because schema coverage is 100%, the baseline of 3 is appropriate.

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 opens with a strong verb and concrete resource: 'Returns a 0-100 monthly consumer discretionary-squeeze score.' It defines the metric's formula, scale, and neutral point, making it unmistakably distinct from any generic economic or spending tool. The purpose is fully clear.

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?

Explicit call-when guidance is provided: 'Call when the user asks about consumer spending pressure, inflation outpacing wages, real wages, purchasing power, or cost-of-living squeeze, or when timing retail promotions...' This is high-quality context, but it lacks any 'when not to use' or explicit alternative comparisons, 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.