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 frequency, the calculation formula, and the specific output fields (trend, wages_yoy_pct, core_cpi_yoy_pct, wages_z/cpi_z). It does not mention error handling or rate limits, but for a read-only data retrieval tool, this is adequate transparency.

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 not bloated—two sentences pack the essential methodological, output, and usage details. It front-loads the primary return value ('0-100 wage-price spiral risk score') before diving into components and when to use it. Some might find it slightly long, but every clause 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?

With no output schema, the description compensates by listing the key return fields and explaining the risk score's meaning. It covers the tool's purpose, methodology, update frequency, and use cases. The only minor gap is a lack of explicit explanation for the 'trend' field, but this does not undermine overall completeness for a read-only indicator tool.

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 input schema has 100% description coverage for the only parameter ('days'), providing a complete explanation of its optional use, maximum value, and Gold tier requirement. The description does not add parameter-specific information, which is acceptable since the schema already carries the full semantic load. Baseline 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 begins with a specific verb ('Returns') and a precise resource ('0-100 wage-price spiral risk score'), then details the exact methodology (YoY avg hourly earnings + YoY core CPI, equal-weight z-scores vs 36-month window). It clearly distinguishes this tool from generic economic metrics by naming the output components and threshold (>50 = rising risk), making it easy to identify from the many sibling tools.

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 states when to call the tool: 'Call when the user asks about wage-price spirals, wage growth vs inflation, sticky core inflation, or labor-cost pass-through, or when timing rate-hike exposure, bond duration shifts, or nominal-vs-TIPS allocation.' This is strong positive guidance, but it does not mention any when-not-to-use cases or alternative tools, so it falls slightly 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.