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

No annotations are provided, so the description must fully disclose behavioral traits. It mentions that it returns origination and denial data and that year defaults to 2022, but it omits critical details such as data source, geographic aggregation level, permission requirements, or what happens when only part of the arguments are supplied. This is a significant transparency gap.

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 concise and well-structured: a front-loaded purpose sentence, a brief return/use-case sentence, and a neatly formatted Args section. Every sentence earns its place with no redundancy or filler.

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?

The presence of an output schema reduces the need to explain return values. However, the tool has three optional parameters with no stated interactions or minimum required combination, and there are no annotations for safety or side effects. The description covers the basics but leaves gaps about data scope and partial-argument behavior.

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 schema provides no parameter descriptions (0% coverage), but the description adds meaningful context for each parameter: state uses two-letter abbreviation examples, county_fips uses a five-digit example, and year includes a default. This compensates well, though the relationship between state and county_fips is not explained.

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 'Get mortgage lending patterns disaggregated by race and ethnicity' — a specific verb and resource with a clear modifier. This distinguishes it from siblings like get_aggregate_stats (aggregate) and get_denial_reasons (denial-focused), leaving no ambiguity about its purpose.

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 explicitly states 'Useful for fair lending analysis and identifying disparities in mortgage access,' providing a clear context for when to use this tool. It doesn't explicitly name alternative tools or exclusions, but the use case is sufficiently distinct from siblings.

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