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klinikal

beanie-mcp

by klinikal

run_query

Query a Beancount ledger using BQL to retrieve financial data. Returns columns and rows, with truncation after 200 rows.

Instructions

Query the Beancount ledger using BQL.

Returns a dict with: columns — list of column name strings rows — list of rows, each a list of value strings truncated — true if the result was cut at 200 rows total_rows — full result count before any truncation error — present (instead of the above) if the BQL is invalid

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesA BQL query, e.g. 'SELECT account, sum(position) WHERE account ~ "Expenses" GROUP BY account'. Results are capped at 200 rows — add LIMIT for smaller sets.
Behavior5/5

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

Details the return structure (columns, rows, truncated, total_rows, error), truncation behavior at 200 rows, and error handling for invalid BQL. Since no annotations are provided, the description fully covers behavioral aspects.

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 concise, with each bullet point serving a purpose. It efficiently communicates input, output, and error conditions without redundancy.

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 single-parameter query tool with no output schema, the description is complete. It covers input format, output structure, truncation, and error handling. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes the 'query' parameter with an example. The tool description adds value by mentioning the 200-row cap and suggesting LIMIT usage. With 100% schema coverage, this extra context justifies a score above baseline.

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?

Clearly states it queries a Beancount ledger using BQL. The verb 'Query' is specific, and it distinguishes itself from 'bean_check' by focusing on querying rather than checking.

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?

Provides usage context: it is used to query the ledger with BQL. Mentions adding LIMIT for smaller result sets, but does not explicitly discuss when to use this tool over alternatives or when not to use it.

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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