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ScottyOmega

YNAB MCP Server

split_transaction

Divide one transaction across multiple budget categories so each portion gets its own amount and memo. Use it when a single charge belongs to several categories.

Instructions

Splits a single transaction across multiple categories with different amounts — e.g. a $75 haircut charge where $50 goes to your category and $25 goes to a category tracking money owed by someone else. Provide at least 2 splits; their amounts must add up to the transaction's total. This cannot be undone via this tool and does not work on transactions that are already split.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
splitsYesThe portions to split the transaction into. Must sum to the transaction's total amount.
budget_idNoThe budget ID, or 'last-used' for the most recently used budget.last-used
transaction_idYesThe ID of the transaction to split.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.9.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose two important traits: irreversibility ('cannot be undone via this tool') and a precondition (fails on already-split transactions). It does not mention permission requirements or side effects on budget/category balances, so it is strong but not exhaustive.

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?

Front-loaded verb, followed by a compact illustrative example and then the key constraints. Every sentence earns its place; the example is genuinely clarifying rather than filler.

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 mutation tool with no annotations and no output schema, the description covers the critical safety and precondition facts an agent needs. It stops short of describing what happens to the original transaction record or any confirmation/return behavior, but the essentials are present.

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%, so the baseline is 3, but the description adds real meaning: the minimum of two splits and the requirement that portions sum to the transaction total, reinforcing the array-level constraint beyond per-field docs. It adds little on budget_id or transaction_id, which the schema already documents.

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?

States a specific verb and resource ('Splits a single transaction across multiple categories') and clarifies the mechanics with a concrete example ($75 haircut split into $50/$25). An agent can distinguish this from siblings like categorize_transaction without opening a schema.

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

Usage Guidelines4/5

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

Gives clear applicability constraints (at least 2 splits, amounts must sum to the total, does not work on already-split transactions), which tells the agent when the tool is valid. It does not, however, explicitly name the alternative (e.g. categorize_transaction) for the single-category case, leaving that routing to inference.

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