GadgetHumans API Hub

mortgage

Compute mortgage repayment, total interest and the loan-to-value ratio. Pure CPU, instant.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "principal": "<principal>"
    },
    "name": "mortgage"
  }
}

Input Schema

Name	Required	Description
`rate`	No	Annual rate percent
`years`	No	Term in years
`principal`	Yes	Loan amount

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 8, 2026
RemovedNov 6, 2026

Changed4 schema fields changedNov 3, 2026

addedInput schema / properties / principal

Added value: +{
+  "description": "Loan amount",
+  "type": "number"
+}

addedInput schema / properties / rate

Added value: +{
+  "description": "Annual rate percent",
+  "type": "number"
+}

addedInput schema / properties / years

Added value: +{
+  "description": "Term in years",
+  "type": "number"
+}

addedInput schema / required
```
Added value: +[
+  "principal"
+]
```

AddedNov 2, 2026

TDQS

B3.3/5.0

Behavior3/5

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

With no annotations, the description must carry behavioral disclosure. It usefully states that the tool is pure CPU and instant, and it names the computed outputs, but it omits key assumptions such as amortization method and what happens when optional rate or years are omitted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, front-loaded with the core computation, with no wasted wording. The performance note is compact and relevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple, and the schema is fully documented, but the description does not explain default behavior for optional rate and years even though only principal is required. It does name the return values, which helps compensate for the absence of an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents principal, rate, and years. The description adds no parameter-level meaning beyond that baseline and only names the outputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: compute mortgage repayment, total interest, and LTV ratio. It is clear what the tool produces, but it does not distinguish itself from sibling tools such as mortgage_calculator, loan, or loan_calculator.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no when-to-use guidance and does not mention alternatives or exclusions, despite several overlapping calculator siblings. 'Pure CPU, instant' is performance context, not usage guidance.

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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