Query Cost of Living (CPI)

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

No annotations are provided, so the description carries the full burden. It does disclose the data source, the coverage limit (17 metros), and the shape of the returned content (overall inflation rate plus category breakdown, YoY rates, monthly trends), which is useful. It does not say what happens for a metro outside the 17, whether this is cached/rate-limited, or how fresh the data is.

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 short, front-loaded paragraphs with no filler; the source and scope lead, and the returned dimensions follow. Slightly abbreviated but nothing wasteful.

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 single-parameter read tool with no output schema, the description covers source, coverage, and return shape adequately. The main omission is behavior for unsupported cities and whether metro names must match a fixed list.

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 coverage is 100% and the single 'city' parameter is documented with examples in the schema itself. The description adds no extra parameter detail, so baseline 3 is appropriate when the schema fully covers the input.

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 a specific resource (Consumer Price Index / cost-of-living data) with its authoritative source (Bureau of Labor Statistics) and the scope of coverage (metro areas, category breakdown). An agent can tell this is the CPI/inflation tool, though it does not explicitly contrast itself with close siblings like query_economics, query_city_data, or compare_demographics.

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?

It gives a scope constraint ('17 metros available') that implicitly bounds when the tool is applicable, but there is no explicit when-to-use, when-not-to-use, or alternative-tool guidance. With ~28 siblings that overlap on city data, the absence of routing guidance is a real gap.

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