FHA denial statistics for a US state (two-letter code). Historical observation computed from the public CFPB HMDA 2025 record (actions 1,2,3; loan_type 2). Not a prediction about any individual application. Attribution: FinanceRateCalc, CC BY 4.0.
| Name | Required | Description | Default |
|---|---|---|---|
| state | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses the data source (public CFPB HMDA 2025), the specific selection criteria (actions 1,2,3; loan_type 2), and clarifies that it is a historical observation, not a prediction. This provides substantial transparency beyond the bare tool name, though it omits details like response format or rate limits.
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 three sentences long, with no redundant words. It efficiently packs the tool's purpose, data source, computation criteria, and a disclaimer into a compact, well-ordered format.
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 simple one-parameter tool with no output schema, the description provides sufficient context: what the tool returns (state-level FHA denial statistics), how it is computed, and a caveat about its non-predictive nature. It does not describe the return value structure, but the absence of an output schema and the simplicity of the tool make this acceptable.
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 only defines 'state' as a string with length constraints, but the description adds essential meaning by specifying 'US state (two-letter code)'. This clarifies the expected format and domain, compensating for the schema's lack of description and the 0% schema_description_coverage.
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 states 'FHA denial statistics for a US state (two-letter code)' and specifies the exact data source and calculation criteria. This unambiguously identifies the tool's function and distinguishes it from sibling tools like 'get_national_fha_stats' (national scope) and 'get_lender_denial_stats' (lender scope).
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 implies usage for state-level FHA denial statistics through its explicit 'US state' scope, but it does not explicitly contrast with alternatives or state when not to use it. The sibling tool names provide context, but the description itself lacks direct use-case guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct data scope: national, state, lender, metro gap, door effect, lender listing, and claim certification. The purposes are clearly separable even though several tools concern FHA denial statistics.
Tool names follow a consistent verb_noun snake_case pattern: get_* for retrievals, list_lenders for enumeration, and check_claim_contract for validation. There are no convention clashes or vague single-word names.
Seven tools is well-scoped for a focused statistics and claim-validation server. Each tool serves a distinct purpose and none feel redundant or bolted on.
The surface covers the main read-only operations: national, state, lender, metro, and door-level stats plus lender listing and claim contract verification. Minor gaps include retrieval of full contract metadata or other statistic categories, but core workflows have no dead ends.