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AxLabs

Banana Accounting MCP Server

by AxLabs

Account interest

banana_interest
Read-only

Calculate interest on an account, group, or class for a selected period, using a positive rate for debit balances or a negative rate for credit balances.

Instructions

Return the calculated interest on an account/group/class. Positive rate calculates interest on debit amounts, negative on credit amounts.

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.
rateYesInterest rate in percent with a dot decimal separator, e.g. "2.5" or "-8.0".
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".
accountYesAccount/group/class selector: an account id ("1000"), group ("Gr=6"), balance class ("BClass=1"), or pipe-separated accounts ("1000|1010|1020").
frequencyNoFrequency: D=daily, W=weekly, M=monthly, Q=quarterly, S=semesterly, Y=yearly.
Behavior4/5

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

The description adds the important behavior of how positive/negative rates affect debit vs credit amounts, which goes beyond the readOnlyHint annotation. This gives the agent operational insight without contradicting the readOnlyHint.

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 clearly conveys the core function without redundancy. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the tool has 6 parameters including period, frequency, and filter, the description doesn't explain how these interact with the calculation. The sign convention is helpful, but the overall behavior is not fully specified for edge cases.

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?

The input schema fully describes all 6 parameters with examples (e.g., account selector syntax, rate format), so the description doesn't need to add param details. The description minimally references account/group/class, which is already in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Return the calculated interest on an account/group/class' with a specific verb and resource, making the primary function clear. However, it doesn't distinguish from similar tools like banana_budget_interest, so it's not fully differentiated.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description gives a calculation rule but no context about prerequisites, selection criteria, or exclusions.

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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