National FHA denial statistics from the 2025 federal record. 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.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the data source (CFPB HMDA 2025 record), the specific filter criteria (actions 1,2,3; loan_type 2), and importantly clarifies it is 'not a prediction about any individual application'. This is good behavioral context for a read-only statistics tool.
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 two sentences, front-loaded with the core purpose in the first sentence, followed by a caveat and attribution. Every sentence adds value with no unnecessary prose.
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, parameterless statistics tool with no output schema, the description provides enough context: data source, scope, and caveat. It does not describe the exact return format, but given the tool's simplicity and the presence of sibling tools, this is not a significant gap.
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 tool has zero parameters, so the schema fully documents anything relevant. The baseline for 0 params is 4, and the description adds contextual meaning about the fixed data scope, which is sufficient.
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 the tool provides 'National FHA denial statistics from the 2025 federal record', which is specific to national scope and differentiates from sibling tools like state and lender denial stats. However, it lacks an explicit verb like 'returns' or 'lists', relying on the tool name to imply the action.
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 gives useful context (historical observation, not a prediction) and implies national scope, but it does not explicitly state when to use this tool over alternatives or mention any exclusions, such as 'use get_state_denial_stats for state-level data'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.