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create_bank_payment

Destructive

Record a bank payment in Billy to mark an invoice or bill as partially or fully paid, posting a real accounting transaction.

Instructions

Record a bank payment in Billy to mark an invoice or bill as (partially) paid. Creates a bankPayment associated with the subject via 'invoice:' or 'bill:'. For invoices money is deposited (debit); for bills it is withdrawn (credit). WARNING: this posts a real accounting transaction.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
verboseNoReturn the full Billy response. Default false: compact records with key fields only (saves ~90% context)
cashSideNoOverride side: 'debit'=deposit (invoices), 'credit'=withdrawal (bills). Defaults based on subjectType.
entryDateYesPayment date (YYYY-MM-DD)
feeAmountNoBank/provider fee (positive, recorded as expense)
subjectIdYesID of the invoice or bill being paid
cashAmountYesAmount deposited/withdrawn in the cash account's currency
subjectTypeYesWhat is being paid
feeAccountIdNoExpense account for the fee (required when feeAmount set)
cashAccountIdYesBank account ID (must have isPaymentEnabled=true; see list_accounts)
organizationIdNoOrganization ID (auto-resolved when omitted)
cashExchangeRateNoExchange rate: 1 subjectCurrency = cashExchangeRate cashAccountCurrency. Required when the cash account's currency differs from the invoice/bill currency.
Behavior5/5

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

The description explicitly warns 'WARNING: this posts a real accounting transaction,' adding critical behavioral context beyond the annotations' destructiveHint: true. It also clarifies the debit/credit direction for invoices vs bills. 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 concise and well-structured, starting with purpose, then behavior details, and ending with a warning. It is efficient and front-loaded, though could be slightly more structured with bullet points.

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 11 parameters, full schema coverage, and no output schema, the description covers core behavior, side effects, and critical warnings. It could mention the return value (e.g., created bank payment) but is otherwise complete.

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?

With 100% schema coverage, the description adds value by providing extra context for key parameters, e.g., 'cashAccountId: must have isPaymentEnabled=true; see list_accounts' and 'feeAccountId required when feeAmount set.' This goes beyond the schema descriptions.

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 it records a bank payment to mark an invoice or bill as paid, specifying the association via 'invoice:<id>' or 'bill:<id>'. It differentiates from sibling tools as no other tool records bank payments.

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?

The description implies usage for marking payments and warns about posting a real accounting transaction, but does not explicitly list alternatives or when not to use it. The context is clear enough for an AI agent to infer appropriate use.

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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