ruiromano/powerbi-agentic-plugins/fabric-cli

Name: fabric-cli
Author: ruiromano

Claude Code and agent skill by ruiromano/powerbi-agentic-plugins

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community

By ruiromano
Design
ruiromano/powerbi-agentic-plugins
Plugin fabric
plugins/fabric/skills/fabric-cli/SKILL.md
Updated 18 Sep 2026
Version 1.0.01 version recorded

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Use Microsoft Fabric CLI (fab) to manage workspaces, semantic models, reports, notebooks, lakehouses, and other Fabric resources via file-system metaphor and commands. Use when deploying Fabric items, running jobs, querying data, managing OneLake files, or automating Fabric operations. Invoke this skill automatically whenever a user mentions the Fabric CLI, fab, or Fabric.

Install

npx vskill@latest install ruiromano/powerbi-agentic-plugins/fabric-cli

SKILL.md

Microsoft Fabric CLI Operations

Note: If you have access to a Bash tool (e.g., Claude Code), execute fab commands directly via Bash rather than using an MCP server.

Expert guidance for using the fab CLI to programmatically manage Fabric

When to Use This Skill

Activate automatically when tasks involve:

Mention of the Fabric CLI, Fabric items, Power BI, fab, or fab commands
Managing workspaces, items, or resources
Deploying or migrating semantic models, reports, notebooks, pipelines
Running or scheduling jobs (notebooks, pipelines, Spark)
Working with lakehouse/warehouse tables and data
Using the Fabric, Power BI, or OneLake APIs
Automating Fabric operations in scripts

Critical

Before first use, ask the user if they have Fabric admin access, any API restrictions, or preferences for Fabric/Power BI API usage
Remind the user to add their Fabric access level and preferences to their agent memory files (e.g., CLAUDE.md) for future sessions
If workspace or item name is unclear, ask the user first, then verify with fab ls or fab exists before proceeding
The first time you use fab run fab auth status to make sure the user is authenticated. If not, ask the user to run fab auth login to login
Always use fab --help and fab <command> --help the first time you use a command to understand its syntax, first
Always try the simple fab command alone, first before piping it
Always use -f when executing command if the flag is available to do so non-interactively
Ensure that you avoid removing or moving items, workspaces, or definitions, or changing properties without explicit user direction
If a command is blocked in your permissions and you try to use it, stop and ask the user for clarification; never try to circumvent it
Use fab in non-interactive mode. Interactive mode doesn't work with coding agents
When working with Fabric item code definitions for CRUD, load the assets/*-definitions.md files to understand more about definition format when calling the fab import operations.

First Run

bash

fab auth login          # Authenticate (opens browser)
fab auth status         # Verify authentication
fab ls                  # List your workspaces
fab ls "Name.Workspace" # List items in a workspace

Variable Extraction Pattern

Most workflows need IDs. Extract them like this:

bash

WS_ID=$(fab get "ws.Workspace" -q "id" | tr -d '"')
MODEL_ID=$(fab get "ws.Workspace/Model.SemanticModel" -q "id" | tr -d '"')
 
# Then use in API calls
fab api -A powerbi "groups/$WS_ID/datasets/$MODEL_ID/refreshes" -X post -i '{"type":"Full"}'

Quick Start

New to Fabric CLI? Here are some references you can read:

Quick Start Guide - Copy-paste examples
Querying Data - Query semantic models and lakehouse tables
Semantic Models - TMDL, DAX, refresh, storage mode
Reports - Export, import, visuals, fields
Notebooks - Job execution, parameters
Workspaces - Create, manage, permissions
Full Command Reference - All commands detailed
Command Reference Table - At-a-glance command syntax

Command Reference

Command	Purpose	Example
Finding Items
`fab ls`	List items	`fab ls "Sales.Workspace"`
`fab ls -l`	List with details	`fab ls "Sales.Workspace" -l`
`fab exists`	Check if exists	`fab exists "Sales.Workspace/Model.SemanticModel"`
`fab get`	Get item details	`fab get "Sales.Workspace/Model.SemanticModel"`
`fab get -q`	Query specific field	`fab get "Sales.Workspace" -q "id"`
Definitions
`fab get -q "definition"`	Get full definition	`fab get "ws.Workspace/Model.SemanticModel" -q "definition"`
`fab export`	Export to local	`fab export "ws.Workspace/Nb.Notebook" -o ./backup`
`fab import`	Import from local	`fab import "ws.Workspace/Nb.Notebook" -i ./backup/Nb.Notebook`
Running Jobs
`fab job run`	Run synchronously	`fab job run "ws.Workspace/ETL.Notebook"`
`fab job start`	Run asynchronously	`fab job start "ws.Workspace/ETL.Notebook"`
`fab job run -P`	Run with params	`fab job run "ws.Workspace/Nb.Notebook" -P date:string=2025-01-01`
`fab job run-list`	List executions	`fab job run-list "ws.Workspace/Nb.Notebook"`
`fab job run-status`	Check status	`fab job run-status "ws.Workspace/Nb.Notebook" --id <job-id>`
Refreshing Models
`fab api -A powerbi`	Trigger refresh	`fab api -A powerbi "groups/<ws-id>/datasets/<model-id>/refreshes" -X post -i '{"type":"Full"}'`
`fab api -A powerbi`	Check refresh status	`fab api -A powerbi "groups/<ws-id>/datasets/<model-id>/refreshes?\$top=1"`
DAX Queries
`fab get -q "definition"`	Get model schema first	`fab get "ws.Workspace/Model.SemanticModel" -q "definition"`
`fab api -A powerbi`	Execute DAX	`fab api -A powerbi "groups/<ws-id>/datasets/<model-id>/executeQueries" -X post -i '{"queries":[{"query":"EVALUATE..."}]}'`
Lakehouse
`fab ls`	Browse files/tables	`fab ls "ws.Workspace/LH.Lakehouse/Files"`
`fab table schema`	Get table schema	`fab table schema "ws.Workspace/LH.Lakehouse/Tables/sales"`
`fab cp`	Upload/download	`fab cp ./local.csv "ws.Workspace/LH.Lakehouse/Files/"`
Management
`fab cp`	Copy items	`fab cp "dev.Workspace/Item.Type" "prod.Workspace" -f`
`fab set`	Update properties	`fab set "ws.Workspace/Item.Type" -q displayName -i "New Name"`
`fab rm`	Delete item	`fab rm "ws.Workspace/Item.Type" -f`

Core Concepts

Path Format

Fabric uses filesystem-like paths with type extensions:

/WorkspaceName.Workspace/ItemName.ItemType

For lakehouses this is extended into files and tables:

/WorkspaceName.Workspace/LakehouseName.Lakehouse/Files/FileName.extension or /WorkspaceName.Workspace/LakehouseName.Lakehouse/Tables/TableName

For Fabric capacities you have to use fab ls .capacities

Examples:

"/Production.Workspace/Sales Model.SemanticModel"
/Data.Workspace/MainLH.Lakehouse/Files/data.csv
/Data.Workspace/MainLH.Lakehouse/Tables/dbo/customers

Common Item Types

.Workspace - Workspaces
.SemanticModel - Power BI datasets
.Report - Power BI reports
.Notebook - Fabric notebooks
.DataPipeline - Data pipelines
.Lakehouse / .Warehouse - Data stores
.SparkJobDefinition - Spark jobs

Full list: 35+ types. Use fab desc .<ItemType> to explore.

Essential Commands

Navigation & Discovery

bash

# List resources
fab ls                                    # List workspaces
fab ls "Production.Workspace"             # List items in workspace
fab ls "Production.Workspace" -l          # Detailed listing
fab ls "Data.Workspace/LH.Lakehouse"      # List lakehouse contents
 
# Check existence
fab exists "Production.Workspace/Sales.SemanticModel"
 
# Get details
fab get "Production.Workspace/Sales.Report"
fab get "Production.Workspace" -q "id"    # Query with JMESPath

Creating & Managing Resources

bash

# Create workspace after using `fab ls .capacities` to check capacities
fab mkdir "NewWorkspace.Workspace" -P capacityname=MyCapacity
 
# Create items
fab mkdir "Production.Workspace/NewLakehouse.Lakehouse"
fab mkdir "Production.Workspace/Pipeline.DataPipeline"
 
# Update properties
fab set "Production.Workspace/Item.Notebook" -q displayName -i "New Name"
fab set "Production.Workspace" -q description -i "Production environment"

Copy, Move, Export, Import

bash

# Copy between workspaces
fab cp "Dev.Workspace/Pipeline.DataPipeline" "Production.Workspace"
fab cp "Dev.Workspace/Report.Report" "Production.Workspace/ProdReport.Report"
 
# Export to local
fab export "Production.Workspace/Model.SemanticModel" -o /tmp/exports
fab export "Production.Workspace" -o /tmp/backup -a  # Export all items
 
# Import from local
fab import "Production.Workspace/Pipeline.DataPipeline" -i /tmp/exports/Pipeline.DataPipeline -f
 
# IMPORTANT: Use -f flag for non-interactive execution
# Without -f, import/export operations expect an interactive terminal for confirmation
# This will fail in scripts, automation, or when stdin is not a terminal
fab import "ws.Workspace/Item.Type" -i ./Item.Type -f  # Required for scripts

API Operations

Direct REST API access with automatic authentication.

Audiences:

fabric (default) - Fabric REST API
powerbi - Power BI REST API
storage - OneLake Storage API
azure - Azure Resource Manager

bash

# Fabric API (default)
fab api workspaces
fab api workspaces -q "value[?type=='Workspace']"
fab api "workspaces/<workspace-id>/items"
 
# Power BI API (for DAX queries, dataset operations)
fab api -A powerbi groups
fab api -A powerbi "datasets/<model-id>/executeQueries" -X post -i '{"queries": [{"query": "EVALUATE VALUES(Date[Year])"}]}'
 
# POST/PUT/DELETE
fab api -X post "workspaces/<ws-id>/items" -i '{"displayName": "New Item", "type": "Lakehouse"}'
fab api -X put "workspaces/<ws-id>/items/<item-id>" -i /tmp/config.json
fab api -X delete "workspaces/<ws-id>/items/<item-id>"
 
# OneLake Storage API
fab api -A storage "WorkspaceName.Workspace/LH.Lakehouse/Files" -P resource=filesystem,recursive=false

Job Management

bash

# Run synchronously (wait for completion)
fab job run "Production.Workspace/ETL.Notebook"
fab job run "Production.Workspace/Pipeline.DataPipeline" --timeout 300
 
# Run with parameters
fab job run "Production.Workspace/ETL.Notebook" -P date:string=2024-01-01,batch:int=1000,debug:bool=false
 
# Start asynchronously
fab job start "Production.Workspace/LongProcess.Notebook"
 
# Monitor
fab job run-list "Production.Workspace/ETL.Notebook"
fab job run-status "Production.Workspace/ETL.Notebook" --id <job-id>
 
# Schedule
fab job run-sch "Production.Workspace/Pipeline.DataPipeline" --type daily --interval 10:00,16:00 --start 2024-11-15T09:00:00 --enable
fab job run-sch "Production.Workspace/Pipeline.DataPipeline" --type weekly --interval 10:00 --days Monday,Friday --enable
 
# Cancel
fab job run-cancel "Production.Workspace/ETL.Notebook" --id <job-id>

Table Operations

bash

# View schema
fab table schema "Data.Workspace/LH.Lakehouse/Tables/dbo/customers"
 
# Load data (non-schema lakehouses only)
fab table load "Data.Workspace/LH.Lakehouse/Tables/sales" --file "Data.Workspace/LH.Lakehouse/Files/daily_sales.csv" --mode append
 
# Optimize (lakehouses only)
fab table optimize "Data.Workspace/LH.Lakehouse/Tables/transactions" --vorder --zorder customer_id,region
 
# Vacuum (lakehouses only)
fab table vacuum "Data.Workspace/LH.Lakehouse/Tables/temp_data" --retain_n_hours 48

Common Workflows

Semantic Model Management

bash

# Find models
fab ls "ws.Workspace" | grep ".SemanticModel"
 
# Get definition
fab get "ws.Workspace/Model.SemanticModel" -q definition
 
# Trigger refresh
fab api -A powerbi "groups/$WS_ID/datasets/$MODEL_ID/refreshes" -X post -i '{"type":"Full"}'
 
# Check refresh status
fab api -A powerbi "groups/$WS_ID/datasets/$MODEL_ID/refreshes?\$top=1"

Execute DAX:

bash

fab api -A powerbi "groups/$WS_ID/datasets/$MODEL_ID/executeQueries" -X post \
  -i '{"queries":[{"query":"EVALUATE TOPN(5, '\''TableName'\'')"}]}'

DAX rules: EVALUATE required, single quotes around tables ('Sales'), qualify columns ('Sales'[Amount]).

For full details: semantic-models.md | querying-data.md

Report Operations

bash

# Get report definition
fab get "ws.Workspace/Report.Report" -q definition
 
# Export to local
fab export "ws.Workspace/Report.Report" -o /tmp/exports -f

This is the start of the file. Read the full SKILL.md on GitHub.

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Source

SKILL.md in the repositoryCheckingplugins/fabric/skills/fabric-cli/SKILL.md

Popularity

Repository stars: 61
Repository forks: 12
7-day trend score: 21

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 17 May 2026, 5 months ago.

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