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

Annotations already declare readOnlyHint=true, and the description adds substantial context: it discloses the data source (BLS CPI), methodology (composite z-score), update cadence (monthly), and output contents (per-staple YoY changes, top driver). This goes beyond the annotation without contradiction.

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?

Two sentences, front-loaded with the core output, followed by concrete use cases and a final update-frequency note. Every phrase adds value with zero redundancy.

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?

Despite having no output schema, the description summarizes return values (0-100 score, per-staple YoY changes, top driver) and provides context for when to use it. The only optional parameter is fully covered by the schema, so nothing essential is missing.

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?

With 100% schema description coverage for the only parameter ('days'), the schema fully explains its behavior and Gold tier requirement. The description does not address parameters, but it doesn't need to; 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 opens with a specific verb and resource: 'Returns a 0-100 US household grocery-burden score' followed by a precise definition of inputs and outputs. This level of detail (BLS CPI, staple list, monthly since 2016) makes the tool's function unmistakable and clearly differentiates it from any generic data tool.

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: grocery inflation, food-at-home costs, egg or beef prices, consumer budget squeeze, and promotional/trade-down/positioning contexts. However, it offers no when-not guidance or named alternatives, so it stops short of a full 5.

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