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Scenarios: Get a what-if scenario with its projected impact

get_scenario
Read-onlyIdempotent
    Get one scenario, its hypothetical changes, and the projected impact.

    Runs the debt-paydown engine on the user's real debts adjusted by this
    scenario's changes and returns the deltas vs their current plan:
    payoff-date change, total-interest change, monthly-payment change,
    net-worth change, and the best paydown strategy under the scenario.

    Args:
        scenario_id: The scenario to analyze.

    Returns:
        {scenario: {...}, items: [...], analysis: {best_strategy,
        interest_delta, monthly_payment_delta, net_worth_delta,
        baseline_payoff_date, scenario_payoff_date, ...}} or
        {"error": "..."} if not found.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scenario_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already mark readOnlyHint, idempotentHint, and destructiveHint, lowering the burden. The description adds valuable context about running the debt-paydown engine, computing deltas against the current plan, and returning an error when the scenario is not found. No contradiction with annotations.

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

Conciseness4/5

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

The description is front-loaded with a clear one-sentence summary followed by a brief explanation and Args/Returns sections. It is well-structured and avoids waste, though the Returns section's '...' placeholder is slightly untidy and could be tightened.

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?

For a single-parameter read-only tool without an output schema, the description covers the main return shape, including several analysis fields and the error case. However, 'items: [...]', 'scenario: {...}', and the trailing '...' leave parts of the return undocumented, making it adequate but not fully complete.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It offers only 'scenario_id: The scenario to analyze,' which essentially restates the parameter name and adds no guidance on sourcing the ID, allowed values, or constraints. This is insufficient for a parameter left undocumented by the schema.

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 states a specific verb and resource: 'Get one scenario, its hypothetical changes, and the projected impact.' It further clarifies the tool's unique function by describing the debt-paydown engine and the return deltas, which clearly distinguishes it from list_scenarios, create_scenario, update_scenario, and delete_scenario.

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 implies use when a user needs a single scenario's projected impact and best strategy, but it never names alternatives or gives exclusion criteria. An agent must infer that list_scenarios is for enumeration and commit_scenario for applying, rather than being told explicitly.

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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