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ninetails-io

gnucash-mcp

cash_flow

Calculate net cash inflows and outflows for a given period across bank and cash accounts, with options to filter internal transfers and group by month, quarter, or year.

Instructions

Calculate cash flow (inflows and outflows) for a period.

Scope is BANK and CASH accounts by default. Credit-card and investment movements are not cash flow (they're liability / asset changes — use balance_sheet). An explicit account= of any type works but the default scope is narrow.

Internal transfers (transactions with no INCOME or EXPENSE leg — transfer to savings, currency wallet shuffle, paying a credit card from checking) are filtered by default. The default totals answer "where did money come from and where did it go?" rather than "every debit and credit." Pass include_transfers=true for the gross flow (e.g. for reconciling against a bank statement).

Args: start_date: Start of period (YYYY-MM-DD) end_date: End of period (YYYY-MM-DD) account: Optional specific account to analyze (defaults to all cash/bank accounts) include_transfers: When False (default), filter internal transfers. When True, include every cash/bank movement regardless of category. group_by: Optional "month", "quarter", or "year" — split the range into sub-period columns and return an Inflows / Outflows / Net trend table (TSV).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNo
end_dateYes
group_byNo
start_dateYes
include_transfersNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that internal transfers are filtered by default, explains what the default totals represent, and clarifies that account= of any type works despite the narrow default. It does not, however, disclose return format beyond the group_by TSV case, or any auth/permission requirements. Still, the core filtering behavior is well documented.

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 well-structured with a clear summary paragraph followed by an Args section. It is moderately long but every sentence earns its place — scope definition, exclusion guidance, filtering behavior, and use cases are all packed efficiently. The prose is tight and front-loaded with the core purpose before diving into edge cases.

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?

There is an output schema present, so the description doesn't need to explain all return values. For a 5-parameter analytical tool with subtle default behaviors (narrow scope, transfer filtering), the description covers the key semantic complexity comprehensively. It could mention output format for the default case (beyond the TSV mention for group_by), but the presence of an output schema mitigates this gap.

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 description coverage is 0%, so the description must fully compensate for all 5 parameters. It does: start_date/end_date get format hints (YYYY-MM-DD), account gets default behavior explained, include_transfers gets detailed True/False semantics, and group_by gets the allowed values plus output behavior ('split the range into sub-period columns, Inflows/Outflows/Net trend table'). This is strong compensation for zero schema coverage.

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 a clear verb+resource+scope statement: 'Calculate cash flow (inflows and outflows) for a period.' It explicitly defines the default scope (BANK and CASH accounts) and distinguishes itself from balance_sheet for credit-card/investment movements. The distinction from siblings is notable and specific.

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?

The description explicitly states when NOT to use this tool (credit-card/investment movements should use balance_sheet), explains the default filtering behavior for internal transfers, and gives a concrete use case for include_transfers=true ('reconciling against a bank statement'). It also explains the conceptual distinction between 'where did money come from' vs 'every debit and credit.'

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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