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oliverames

YNAB MCP Server

by oliverames

Audit Credit Card Payments

audit_credit_card_payments
Read-onlyIdempotent

Compare each credit card's balance to its payment category's available funds to detect underfunded payments. Pinpoints shortfalls that need extra budgeting.

Instructions

Read-only audit of credit card payment categories: for each open credit card / line of credit account, compares the card's balance with its Credit Card Payment category's available balance. In a healthy budget the payment category equals the card balance (sign-flipped) for spending that is budgeted; a shortfall means a future payment is not fully funded (common after overspending or direct debt increases). Reports each card's balance, payment-category balance, difference, and a status. Makes no changes — fix shortfalls by assigning to the payment category via update_month_category. Interpretation note: small transient differences appear while recent transactions are pending/uncleared; treat sub-dollar or same-day differences as timing, not error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
budgetIdNoBudget ID (uses default if not provided)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv5.4.0
    • removedOutput schema / properties / result / description
      Removed value: -"Structured result returned by Audit Credit Card Payments."
  2. Addedv5.1.1

TDQS

A4.7/5.0
Behavior5/5

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

Even though annotations already mark the tool read-only, idempotent, and non-destructive, the description adds valuable behavior: it 'makes no changes,' reports each card's balance/category balance/difference/status, and warns that pending/uncleared transactions can cause transient sub-dollar differences to be treated as timing rather than error. This goes beyond the annotations.

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 front-loaded with the core audit purpose and flows naturally into purpose, healthy/unhealthy interpretation, output contents, non-mutating behavior, and a practical caveat. Every sentence adds information; there is no filler or repetition.

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

Completeness5/5

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

For a read-only audit tool with an output schema and a single optional parameter, the description fully covers what the tool computes, what the results mean, what it does not do, and how to interpret edge cases. Nothing material is missing for an agent to invoke it confidently.

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?

The only parameter, budgetId, is fully described in the schema ('Budget ID (uses default if not provided)'), so schema coverage is 100%. The description adds no budgetId-specific semantics, but none are needed because the schema already handles it; this is the appropriate baseline score.

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 opens with 'Read-only audit of credit card payment categories' and precisely defines the behavior: comparing each open card/line-of-credit balance with the corresponding payment category's available balance. This clearly distinguishes it from generic read tools like get_account or get_category, and from the fix-oriented update_month_category tool.

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

Usage Guidelines5/5

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

It explicitly states when this audit is relevant (healthy budgets show a sign-flipped match; shortfalls indicate underfunded future payments) and gives an actionable alternative: 'fix shortfalls by assigning to the payment category via update_month_category.' This is strong when-to-use and when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.