get_lender_denial_stats

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

With no annotations provided, the description carries the full burden and does so thoroughly: it discloses the data source (CFPB HMDA 2025), the exact denominator definition (actions 1,2,3; loan_type 2), the historical nature of the observation, top-100 coverage limits, and explicit caveats that it is not a prediction or recommendation. This is exemplary disclosure.

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 appropriately sized, with the core purpose and metrics in the first sentence, followed by coverage, methodology, and disclaimers. Every sentence contributes meaningful information, and nothing is redundant 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?

Despite having no output schema and no annotations, the description is self-sufficient: it explains what metrics will be returned, the data source and calculation basis, coverage constraints, and important caveats. The tool is simple with one parameter, and the description fully compensates for the missing structured metadata.

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 description coverage is 100% for the single 'lender' parameter, already stating name, slug, or 20-char LEI. The description repeats these identifiers but adds the context that only top-100 lenders are covered, which mildly supplements parameter understanding without providing new syntactical details beyond the schema.

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 clearly specifies the tool returns FHA denial statistics for one lender, identified by name, slug, or LEI, and enumerates the exact metrics (actual denial rate, peer-median comparison, mix-adjusted expected rate). It also distinguishes itself from sibling tools by emphasizing 'one lender' and limiting coverage to top-100 FHA lenders.

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 provides clear context for when to use the tool: for per-lender FHA denial stats, with coverage limited to top-100 lenders. It does not explicitly name alternatives like get_national_fha_stats or get_state_denial_stats, nor state when not to use this tool, but the per-lender focus and coverage limit imply appropriate usage.

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