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semantic_model_refresh

Triggers a refresh of a semantic model in Power BI using workspace and model IDs. Ensures data is up to date for reports and analytics.

Instructions

Trigger a refresh of a semantic model via the Power BI API

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceIdYesThe workspace ID (Power BI group ID)
semanticModelIdYesThe semantic model/dataset ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv2.8.0

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already indicate a non-read-only, non-destructive operation, but the description adds little beyond that. The word 'Trigger' hints that the refresh may be asynchronous, but the description does not disclose that the operation may be long-running, what side effects occur, or that semantic_model_get_refresh_history can be used to monitor progress.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no fluff. The phrase 'via the Power BI API' adds little value, but the overall structure is efficient and easy to parse.

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

Completeness2/5

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

For a triggering operation with no output schema, the description is too thin. It does not explain the asynchronous nature of the refresh, what a successful invocation looks like, or how to verify the refresh status, which are important for an agent to correctly handle the tool's result.

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?

Schema description coverage is 100%, with both workspaceId and semanticModelId already documented. The description adds no parameter-level meaning, which is acceptable given the schema carries that burden.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Trigger a refresh') and the resource ('semantic model'), so an agent can tell this is the refresh operation rather than a list, create, or delete sibling. However, it does not explicitly contrast itself with related tools such as semantic_model_get_refresh_history, so it stops short of the strongest sibling-differentiating clarity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given about when to use this tool versus alternatives, prerequisites, or follow-up steps. The wording only implies 'if you need to refresh a semantic model, use this', but there is no explicit context or comparison with related semantic_model operations.

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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