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DesktopCommanderPy

hana_execute_query

Execute SQL queries on SAP HANA Cloud, returning formatted SELECT results, affected row counts for DML, and stored procedure outputs. Limits rows to prevent full table dumps.

Instructions

Ejecuta una sentencia SQL en SAP HANA Cloud y devuelve los resultados.

Para consultas SELECT devuelve una tabla formateada con los resultados. Para INSERT/UPDATE/DELETE devuelve las filas afectadas. Para CALL (stored procedures) devuelve el resultado del procedure.

El número de filas está limitado para evitar volcar tablas enteras. Usa max_rows para ajustar el límite.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesSentencia SQL a ejecutar (SELECT, CALL, etc.). Una sola sentencia.
schemaNoSchema a usar. Vacío = usar el configurado por defecto.
max_rowsNoMáximo de filas a devolver. Default 200.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Describes row limit and per-SQL-type behavior. No annotations provided, so description carries burden; lacks details on error handling or read-only nature but sufficient for basic understanding.

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?

Six sentences, well-structured, front-loaded with action, no redundant information.

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?

Covers output expectations for different SQL types and row limit. Lacks error handling or timeout info, but adequate given sibling tools and output schema existence.

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?

Schema covers all three params with descriptions. Description adds nuance about row limiting to avoid dumping tables, providing value beyond schema.

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 executes SQL in SAP HANA Cloud, distinguishes SELECT, DML, and CALL behaviors. Distinct from siblings like hana_describe_table and hana_execute_ddl.

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?

Explains row limit and max_rows usage for controlling output. Does not explicitly contrast with sibling tools or state when not to use, but context is clear.

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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