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ninetails-io

gnucash-mcp

list_budgets

Read-only

List budgets from a GnuCash book. Supports pagination via offset and limit, compact text summary by default, or full JSON with verbose mode.

Instructions

List all budgets in the book.

Leads with a Showing X-Y of Z budgets line, then a compact one-line-per-budget format by default. Page with offset; limit=0 returns the count only. Use verbose=true for the full JSON envelope.

Args: verbose: If false (default), compact text output — optimized for reading and token efficiency. If true, structured JSON, for when you need machine-readable fields rather than a report. limit: Page size (default 50, max 250). 0 = count only. offset: 0-indexed first row to return (default 0).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
verboseNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.2

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already mark readOnlyHint=true, and the description adds substantial behavioral detail: a 'Showing X-Y of Z budgets' preamble, compact one-line-per-budget default output, pagination semantics, count-only mode at limit=0, and the compact-vs-JSON split for verbose. This goes well beyond the annotations and tells the agent exactly what to expect.

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 efficiently organized: a one-sentence purpose, a compact behavior paragraph, and a concise Arg list. Every sentence adds value, and the most important behavioral facts are front-loaded before the parameter details.

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

Completeness5/5

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

For a list tool with three optional parameters, an output schema, and read-only annotations, the description is complete. It covers output format, pagination, count-only mode, and verbose behavior, so an agent has everything needed to invoke it correctly without further inference.

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%, but the description fully compensates. It explains verbose's two output modes, limit's default/max/count-only behavior, and offset's 0-indexed meaning — none of which are in the bare schema. This is excellent parameter documentation.

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 'List all budgets in the book,' a specific verb and resource that clearly distinguishes this from sibling tools like get_budget or get_budget_report. It also defines what the output looks like, so an agent knows exactly what this tool does.

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 gives clear operational guidance: how to page with offset, how limit=0 changes behavior, and when to use verbose mode for JSON output. It does not explicitly name sibling tools or exclusion conditions, but the 'all budgets' phrasing and output details make the intended use clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.