semantic_model_list
List all semantic models in a Microsoft Fabric workspace by passing its workspace ID.
Instructions
List all semantic models in a workspace
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| workspaceId | Yes | The workspace ID |
List all semantic models in a Microsoft Fabric workspace by passing its workspace ID.
List all semantic models in a workspace
| Name | Required | Description | Default |
|---|---|---|---|
| workspaceId | Yes | The workspace ID |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
v2.8.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only and non-destructive, covering the safety profile. The description adds the workspace-scoped, all-models context but does not disclose additional behavioral traits such as pagination, permissions, or return-value shape; this is acceptable given the annotations but not especially rich.
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?
The description is one tightly written sentence with every word earning its place. It front-loads the action and scope and contains no filler, repetition, or irrelevant detail.
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?
For a read-only list operation with one required, schema-documented parameter, the description, schema, and annotations provide enough for an agent to select and invoke the tool correctly. A minor gap is the lack of any indication of what fields the returned list items contain, but the word 'list' makes the basic return behavior self-evident.
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?
The single parameter workspaceId is fully documented in the input schema with 100% coverage. The description adds no further parameter detail, so it correctly relies on the schema; baseline 3 applies when the schema does the heavy lifting.
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 clear, specific operation: list all semantic models within a workspace. It distinguishes from semantic_model_get_details and the various semantic_model mutation/creation tools without requiring schema inspection.
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 provides clear context for when to use this tool: when a full inventory of semantic models in a workspace is needed. It does not explicitly name an alternative for fetching individual model details, but the sibling tool set makes that distinction straightforward and no misleading guidance is present.
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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