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gnucash-mcp

list_scheduled_transactions

Read-only

View scheduled recurring transactions from your GnuCash book with compact summaries or detailed JSON, including pagination and enabled-only filtering.

Instructions

List all scheduled transactions.

Leads with a Showing X-Y of Z scheduled transactions line, then a compact one-line-per-schedule format by default. Page with offset; limit=0 returns the count only. Use verbose=true for structured JSON with GUIDs, splits, dates, etc.

Args: enabled_only: If True, only show enabled schedules. Default True. 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
enabled_onlyNo

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?

Beyond the readOnlyHint annotation, the description discloses concrete output behavior: the 'Showing X-Y of Z scheduled transactions' header line, a compact one-line-per-schedule default, limit=0 count-only mode, and verbose JSON containing GUIDs, splits, and dates. These traits are invisible in both the schema and annotations, so the description carries real behavioral weight.

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 front-loaded with the one-sentence purpose, then a tight output-format paragraph, then a clean Args block. No sentence is filler; the token-efficiency note and sentinel-value documentation each earn their place.

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 read-only, four-parameter list tool with an output schema, the description covers everything an agent needs: output shape, pagination mechanics, filtering default, and the verbose mode decision. With the output schema present for return-value structure, nothing material is missing.

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 bears the full burden — and it pays it in full. Every parameter gets semantic detail: enabled_only's filtering effect, verbose's two output modes, limit's page size plus the sentinel '0 = count only' and max of 250, and offset as a 0-indexed row pointer.

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 specific verb+resource pair: 'List all scheduled transactions,' which unambiguously identifies the operation and resource. This distinguishes it from siblings such as list_transactions (actual posted transactions) and get_upcoming_transactions (only upcoming schedules), even without naming them.

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 explicit mode-selection guidance: compact text output is 'optimized for reading and token efficiency,' while verbose=true is for 'structured JSON' when machine-readable fields are needed rather than a report. It does not, however, state when to prefer this tool over siblings like get_upcoming_transactions or list_transactions.

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