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ninetails-io

gnucash-mcp

income_by_source

Generate income breakdown by source for a specified period, with optional grouping by month, quarter, or year to compare performance across periods.

Instructions

Get income breakdown by source for a period.

Returns a compact aligned text table by default. Use verbose=true for the full structured dict.

Args: start_date: Start of period (YYYY-MM-DD) end_date: End of period (YYYY-MM-DD) depth: Hierarchy depth for grouping (1 = top-level categories, 2 = subcategories) verbose: If true, return the structured dict. group_by: Optional "month", "quarter", or "year" — split the range into sub-period columns and return a multi-period TSV table (source rows, one column per period plus Total and Avg). Overrides verbose.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNo
verboseNo
end_dateYes
group_byNo
start_dateYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The description discloses return format behavior: compact text table by default, structured dict with verbose=true, and a multi-period TSV table with Total/Avg columns when group_by is set. It also explains the group_by overrides verbose interaction. This provides meaningful behavioral context, though it doesn't address side effects/limits (which are largely irrelevant for a read-only report).

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?

Reasonably compact given it documents 5 parameters and return formats. The parameter descriptions are integrated into the Args block. Each sentence earns its place, though the parameter documentation duplicates what could be inferred from schema in part.

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?

The tool has an output schema and 5 params (2 required). The description covers all parameter semantics including depth meaning, verbose behavior, and the group_by multi-period output. It is self-contained for a read-only reporting tool. No annotation coverage exists but the description compensates with return-format detail.

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 description coverage is 0%, so the description carries full burden. It documents all 5 parameters well: start/end date format (YYYY-MM-DD), depth meaning (1 vs 2 mapping to category levels), verbose behavior, and group_by options with detailed output implications (month/quarter/year sub-period columns, Total and Avg). 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?

Specific verb+resource: 'Get income breakdown by source for a period.' This clearly distinguishes from sibling report tools (spending_by_category, cash_flow, balance_sheet) by naming the income-by-source scope and period constraint. Clear and differentiated.

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?

Implicit usage context is clear: it's a report/category breakdown tool analogous to spending_by_category. The description doesn't explicitly name when-not-to-use or alternative tools, but the 'income by source' vs 'spending by category' distinction in sibling names provides contextual signal. No explicit exclusions or when-to-use guidance is stated in the text itself.

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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