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execute_query

Execute SQL SELECT queries on clinical datasets like MIMIC-IV and eICU to analyze tabular EHR data and clinical notes.

Instructions

🚀 Execute SQL queries to analyze data.

Recommended workflow:

  1. Use get_database_schema() to list tables

  2. Use get_table_info() to examine structure

  3. Write your SQL query with exact names

Args: dataset: Dataset name, e.g. 'mimic-iv'. sql_query: Your SQL SELECT query (SELECT only).

Returns: Query results or helpful error messages.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sql_queryYes
datasetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses essential behaviors: only SELECT queries are allowed, returns results or error messages. With no annotations, the description carries the burden; it does not cover rate limits or authorization but is 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?

Very concise, with a bulleted workflow and clear args list. Every sentence adds value; no redundancy. Front-loaded with emoji and purpose.

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?

Complete for the tool's purpose given sibling tools and output schema. Explains workflow with siblings and parameter semantics. Does not elaborate on dataset default behavior, but that is minor.

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?

Despite 0% schema description coverage, the description provides examples for dataset and clarifies sql_query is a SELECT query. This adds meaning beyond the bare schema. Could be improved with SQL dialect details or constraints.

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 queries for data analysis, and specifies SELECT-only. Differentiates from sibling tools like get_database_schema and get_table_info which are for schema exploration.

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 a recommended workflow involving sibling tools, guiding the agent on correct usage sequence. Lacks explicit when-not-to-use statements but implies context through the workflow and SELECT-only constraint.

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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