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Numeratica — financial planning calculations

debt_vs_invest

Debt vs invest. Numeratica POST /v1/debt-vs-invest — returns JSON with result_id, engine_version, and a not-advice disclaimer (seed echoed for reproducible Monte Carlo where applicable). See the input schema for the accepted fields.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "debt_vs_invest"
  }
}

Input Schema

NameRequiredDescriptionDefault
seedNo
loan_balanceNo
extra_monthlyNo
horizon_yearsNo
marginal_rateNo
annual_fee_rateNo
expected_returnNo
num_simulationsNo
loan_annual_rateNo
return_volatilityNo
interest_deductibleNo
loan_minimum_paymentNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.7/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It discloses that the tool returns JSON with a disclaimer and uses Monte Carlo simulation with optional reproducible seed, but does not mention side effects, authentication needs, rate limits, or whether it is a read-only operation.

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

Conciseness3/5

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

The description is a single sentence that quickly states purpose and endpoint, but it is brief to the point of being sketchy. It could be better structured by front-loading the core purpose and then detailing parameters or usage.

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

Completeness2/5

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

Given 12 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the return format details beyond a few fields, nor does it help an AI agent understand how to set parameters for Monte Carlo simulations or compare with similar tools like debt_payoff.

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

Parameters1/5

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

Schema description coverage is 0% and the description adds no parameter meaning beyond the schema types. The advice 'See the input schema for the accepted fields' does not provide any semantics, leaving 12 parameters completely unexplained.

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 'Debt vs invest' and mentions it is a Numeratica POST endpoint returning JSON with result_id and engine_version, indicating it compares debt vs investing using Monte Carlo simulations. However, it does not distinguish from sibling tools like 'debt_payoff' which might have a different purpose.

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 provides no guidance on when to use this tool versus alternatives, no exclusions, and no context about prerequisites such as requiring specific financial parameters. It simply names the endpoint and output format.

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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