execute_daxExecute a DAX query against a Power BI dataset and return the resulting table for automation or analysis.
Ejecuta una consulta DAX contra un dataset y devuelve la tabla resultante.
| Name | Required | Description | Default |
|---|---|---|---|
| daxQuery | Yes | Consulta DAX, ej: EVALUATE INFO.VIEW.TABLES() | |
| datasetId | Yes | ID del dataset | |
| workspaceId | Yes | ID del workspace |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It only states that it returns a result table, but does not disclose whether the operation is read-only, what happens on error, or any authentication requirements. This is a significant gap for a tool that could be long-running or have side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no wasted words. The verb and resource are stated immediately, and the return type is mentioned. It is as concise as possible while conveying the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 required parameters, no output schema, and no annotations, the description is too thin. It does not explain the expected query format, potential errors, authentication needs, or the structure of the returned table. An agent might struggle to know what constitutes a valid invocation or what to expect back.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents each parameter (workspaceId, datasetId, daxQuery). The description adds no additional information about parameter usage or relationships, so it meets the baseline but does not go beyond it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb 'Ejecuta' (executes) and a clear resource 'consulta DAX contra un dataset' (DAX query against a dataset). It clearly distinguishes itself from sibling tools like list_reports, refresh_dataset, etc., which are about listing and refreshing rather than querying.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for executing DAX queries but does not explicitly state when to use it versus alternatives, nor does it mention any exclusions or prerequisites. The siblings are clearly different in function, but no explicit guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.