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Delete Item from Workspace

delete_item

Remove items like notebooks, lakehouses, or reports from a Microsoft Fabric workspace by specifying the workspace name, item name, and item type.

Instructions

Delete an item from a Fabric workspace.

Deletes the specified item from the workspace. The item is identified by its display name and type. Common item types include: Notebook, Lakehouse, Warehouse, Pipeline, Report, SemanticModel, Dashboard, etc.

Parameters: workspace_name: The display name of the workspace. item_display_name: Name of the item to delete. item_type: Type of the item to delete (e.g., "Notebook", "Lakehouse"). Supported types: Notebook, Lakehouse, Warehouse, Pipeline, DataPipeline, Report, SemanticModel, Dashboard, Dataflow, Dataset.

Returns: Dictionary with status and success/error message.

Example: python result = delete_item( workspace_name="My Workspace", item_display_name="Old Notebook", item_type="Notebook" )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspace_nameYes
item_display_nameYes
item_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool deletes items but doesn't mention critical behavioral aspects like whether deletion is permanent, requires specific permissions, has confirmation prompts, or affects dependencies. The example shows a basic call but lacks context about consequences or error handling.

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 well-structured with clear sections (purpose, parameters, returns, example) and uses bullet points for readability. While somewhat verbose, each sentence adds value. The example is helpful but could be more concise.

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?

For a destructive mutation tool with no annotations, the description is moderately complete. It explains parameters and return format, and an output schema exists. However, it lacks crucial behavioral context about deletion consequences, permissions, and error conditions that would be essential for safe usage.

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

Parameters4/5

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

With 0% schema description coverage, the description compensates well by explaining all three parameters: workspace_name, item_display_name, and item_type. It provides examples of item types and lists supported values, adding meaningful context beyond the bare schema. However, it doesn't specify format constraints or validation rules.

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 specific action ('Delete') and resource ('item from a Fabric workspace'), distinguishing it from sibling tools like 'list_items' or 'create_semantic_model'. It explicitly mentions the item is identified by display name and type, providing clear differentiation.

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 provided on when to use this tool versus alternatives. While sibling tools like 'delete_activity_from_pipeline' or 'delete_measures_from_semantic_model' exist for specific item types, the description doesn't mention these alternatives or provide context for choosing between them.

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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