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wealth-engine

wealth-engine

by Jaume9
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Debt Payoff Planner (Avalanche vs Snowball)

debt_payoff

Simulate debt payoff using avalanche and snowball methods. Compare months to debt-free and total interest to choose the best strategy.

Instructions

Plan how to get out of debt fastest. Simulates month-by-month payoff of multiple debts using the avalanche (highest interest first) and/or snowball (smallest balance first) methods, rolling freed-up payments onto the next target. Reports months to debt-free, total interest, and which strategy wins.

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": {
      "debts": "<debts>",
      "monthlyBudget": "<monthlyBudget>"
    },
    "name": "debt_payoff"
  }
}

Input Schema

NameRequiredDescriptionDefault
debtsYesThe list of debts to pay off.
strategyNoWhich strategy to run. 'compare' (default) runs both and recommends the cheaper one.
monthlyBudgetYesTotal dollars available for debt each month (must be >= sum of minimum payments).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It explains the simulation behavior, including rolling freed-up payments and reporting months to debt-free and total interest. However, it does not disclose any underlying assumptions or limitations, such as interest rate constancy.

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?

The description is two sentences, concise and well-structured. It front-loads the core action and includes key details without unnecessary words.

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

Completeness4/5

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

Given no output schema, the description mentions expected results (months to debt-free, total interest, winning strategy). It covers the main behavior and output, though it could mention edge cases or prerequisites (e.g., ensuring monthlyBudget >= sum of minimum payments).

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

Parameters4/5

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

Schema coverage is 100% with descriptions for all parameters. The tool description adds context about avalanche vs. snowball methods and rolling payments, enhancing understanding beyond the schema. It does not add new parameter details but reinforces their use.

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

Purpose5/5

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

The description clearly states the tool's purpose: planning debt payoff using avalanche and/or snowball methods, simulating month-by-month, and reporting results. The title and content distinguish it from sibling tools like budget_analyzer and loan_amortization.

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

Usage Guidelines3/5

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

The description does not provide explicit guidance on when to use this tool versus siblings. It only describes what it does, leaving the agent to infer usage context from the tool's name and category.

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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