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Superset MCP Integration

by aptro

superset_sqllab_estimate_query_cost

Estimate SQL query execution costs before running them to optimize database performance and resource allocation in Apache Superset.

Instructions

Estimate the cost of executing a SQL query

Makes a request to the /api/v1/sqllab/estimate endpoint to get approximate cost information for a query before executing it.

Args: database_id: ID of the database sql: SQL query to estimate schema: Optional schema name

Returns: A dictionary with estimated query cost metrics

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
database_idYes
sqlYes
schemaNo
Behavior3/5

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

With no annotations provided, the description carries full burden. It discloses that this is a read-only estimation operation (not execution) and mentions it makes an API request, but doesn't provide details about rate limits, authentication requirements, error conditions, or what specific cost metrics are returned. It adds some behavioral context but leaves significant gaps.

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 structured with a clear purpose statement first, followed by implementation details, then parameter and return value sections. Every sentence adds value with zero wasted words. The four-sentence structure is front-loaded and appropriately sized for this tool.

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

Completeness3/5

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

Given no annotations, no output schema, and 0% schema description coverage, the description does an adequate but incomplete job. It covers the basic purpose and parameters but lacks details about authentication, error handling, rate limits, and the structure of the returned cost metrics. For a tool that estimates query costs, more context about what 'cost' means in this system would be helpful.

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

Parameters3/5

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

With 0% schema description coverage, the description must compensate but only partially succeeds. It lists the three parameters with brief explanations, but doesn't provide format details, constraints, or examples. The 'schema' parameter is noted as optional, which helps, but overall the parameter documentation is minimal given the schema provides no descriptions.

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 clearly states the tool's purpose with specific verb ('Estimate') and resource ('cost of executing a SQL query'), and distinguishes it from siblings like 'superset_sqllab_execute_query' by focusing on estimation rather than execution. The first sentence directly answers what the 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 provides clear context for when to use this tool ('to get approximate cost information for a query before executing it'), which implicitly suggests it should be used prior to execution. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among siblings, though the context implies 'superset_sqllab_execute_query' is the logical follow-up.

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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