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ynab_create_account

Create a new account in your YNAB budget. Specify name, type, and optional opening balance to add checking, savings, credit card, or other accounts.

Instructions

Create a new account in a YNAB budget.

Args:

  • budget_id (string, optional): Budget UUID. Omit to use the default budget.

  • name (string, required): Account name.

  • type (string, required): One of: checking, savings, creditCard, cash, lineOfCredit, otherAsset, otherLiability.

  • balance (number, optional): Opening balance in dollars. Default: 0.

  • dry_run (boolean, optional): Preview the request without creating. Default: false.

Returns: account object with id, name, type, balance fields.

Examples:

  • Create checking account: set name="My Checking", type="checking"

  • Dry run: set dry_run=true to preview without saving

Write safety: call without confirmation_token to preview. Execute the identical validated request with the short-lived confirmation_token returned by that preview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
typeYes
balanceNo
dry_runNo
budget_idNo
confirmation_tokenNoShort-lived, single-use token returned by the immediately preceding preview of this exact validated request.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already indicate mutation (readOnlyHint=false) and non-destructiveness. The description adds the preview/execute pattern with dry_run and confirmation_token, which is critical behavioral context for safe usage. It also notes default values and optionality, adding value beyond 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 well-organized: a one-line summary, structured Args/Returns/Examples sections, and a separate safety note. Every sentence adds value with no redundancy or fluff.

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?

Given 6 parameters, limited schema descriptions, and available output schema, the description covers all necessary aspects: purpose, parameters, return value, examples, and the preview/execute workflow. It is complete for an agent to use effectively.

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

Parameters5/5

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

Schema coverage is only 17%, but the description compensates by explaining each parameter's meaning, allowed values (e.g., type enum), defaults, and optionality. It also provides examples and clarifies the role of confirmation_token in the safety note.

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 'Create a new account in a YNAB budget.' The verb 'create' and resource 'account' are specific, and it distinguishes from sibling tools like ynab_create_transaction by focusing on account creation.

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 includes examples and a preview/execute pattern, but it does not directly compare this tool to alternatives (e.g., when to create an account vs. a transaction). No explicit exclusions or when-not-to-use guidance is provided.

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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