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semantic_model_create_tmdl

Create a semantic model in Microsoft Fabric by loading TMDL definitions from .tmdl and .pbism files in a specified directory.

Instructions

Create a new semantic model with a TMDL definition (long-running). Reads .tmdl and .pbism files from the specified directory.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionNoDescription of the semantic model
displayNameYesDisplay name for the semantic model
workspaceIdYesThe workspace ID
filesDirectoryPathYesPath to a directory containing .tmdl and .pbism files

Schema Changelog

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

  1. First observedv2.8.0

TDQS

A3.7/5.0
Behavior3/5

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

Annotations only indicate that this is not read-only and not destructive, which aligns with a create operation. The description adds useful behavioral context by flagging the operation as 'long-running' and specifying that it reads local files. However, it does not disclose what the caller receives after invocation, whether there is an operation ID to poll, or what happens if the files are invalid or already used.

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 two sentences with no fluff. The main action and the long-running nature are front-loaded, and the second sentence provides the essential input mechanism. Every word earns its place.

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?

The description covers the tool purpose, file types, and long-running nature, and the schema documents all parameters. However, with no output schema and no explanation of what a caller should do after triggering this long-running operation, an agent is left uncertain about how to retrieve the result or check status. This is a meaningful gap for a creation operation.

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?

The input schema already describes all four parameters, including filesDirectoryPath as 'Path to a directory containing .tmdl and .pbism files.' The tool description largely restates this same information, so it adds no meaningful parameter-level meaning beyond what the schema provides. Baseline 3 is appropriate.

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 uses a specific verb and resource: 'Create a new semantic model with a TMDL definition.' It also clarifies the file-based input by mentioning '.tmdl and .pbism files,' which distinguishes this tool from the sibling semantic_model_create_bim without needing to inspect either schema.

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

Usage Guidelines3/5

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

The description implies the tool is appropriate when creating a semantic model from a directory of TMDL/PBISM files, but it never explicitly names semantic_model_create_bim as the alternative for BIM-based creation or states when not to use this tool. The usage context is reasonably clear, but the exclusion guidance is missing.

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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