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AxLabs

Banana Accounting MCP Server

by AxLabs

VAT balance

banana_vat_balance
Read-only

Get the current VAT balance for any VAT code or group, supporting period, frequency, and custom transaction filters.

Instructions

Return the current VAT balance figure for a VAT code or VAT group. Supports period, frequency and filter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
docNoAccounting document name as opened in Banana (e.g. "accounting.ac2"). Append "_p1", "_p2" for previous years. Defaults to BANANA_DEFAULT_DOC if set.
typeYesVAT amount type to return (taxable, amount, notdeductible, posted, rowcount).
filterNoJavaScript expression to filter transactions, e.g. filter=row.value("Date")==="2024-01-15". Available: row, rowNr, table.
periodNoPeriod filter: an abbreviation like "Q1"/"3M"/"1Y" or a date range "2024-01-01/2024-03-31".
vat_codeYesVAT code ("V80"), group ("Gr=..."), or pipe-separated codes ("V0|V80").
frequencyNoFrequency: D=daily, W=weekly, M=monthly, Q=quarterly, S=semesterly, Y=yearly.
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the agent knows this is a read-only operation. The description adds that the tool supports period, frequency, and filter, which informs how the result may vary. However, it does not disclose details about return format, edge cases, or the meaning of 'current' relative to period/frequency, leaving some behavioral gaps.

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 a single, front-loaded sentence that immediately states the purpose and then lists the supported parameter types. It contains no filler or redundant information, making it highly concise and well-structured.

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 read-only tool with no output schema, the description gives a clear idea of the return value ('VAT balance figure') and the key modifiers (VAT code/group, period, frequency, filter). While the schema covers all parameters, the description could have clarified how 'current' interacts with period/frequency, but overall it is sufficiently complete for an agent to select and invoke the tool.

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?

Schema description coverage is 100%, so the schema already documents all six parameters fully. The description mentions 'period, frequency and filter' but adds no additional syntax or meaning beyond what the schema provides. Thus the baseline of 3 is appropriate.

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 a specific verb ('Return') and resource ('VAT balance figure for a VAT code or VAT group'), which distinguishes it from sibling tools like banana_vat_report or banana_vat_description. It also mentions the supported filters (period, frequency, filter), providing clear scope.

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 implies that this tool is for retrieving VAT balance figures, but it does not explicitly contrast it with alternatives such as banana_balance or banana_vat_report. No when-not-to-use guidance is provided, so the usage context is only hinted at through the resource and parameter descriptions.

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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