---
name: fabric-cli-core
description: Use Microsoft Fabric CLI (fab) to manage workspaces, semantic models, reports, notebooks, and Fabric resources. Activate when users mention fab, Fabric CLI, or…
---

# fabric-cli-core

Use Microsoft Fabric CLI (fab) to manage workspaces, semantic models, reports, notebooks, and Fabric resources. Activate when users mention fab, Fabric CLI, or…

# fabric-cli-coreby microsoft
Use Microsoft Fabric CLI (fab) to manage workspaces, semantic models, reports, notebooks, and Fabric resources. Activate when users mention fab, Fabric CLI, or…

`npx skills add https://github.com/microsoft/fabric-cli --skill fabric-cli-core`Download ZIPGitHub

## Fabric CLI Core

This skill defines safe, consistent defaults for an AI agent helping users operate Microsoft Fabric via the Fabric CLI (`fab`).

## 1 - Fabric CLI mental model (paths and entities)

### Automation Scripts

Ready-to-use Python scripts for core CLI tasks. Run any script with `--help` for full options.

ScriptPurposeUsage`health_check.py`Verify CLI installation, auth status, and connectivity`python scripts/health_check.py [--workspace WS]`
Scripts are located in the `scripts/` folder of this skill.

### Paths and Entities

* Treat Fabric as a filesystem-like hierarchy with consistent dot (.) entity suffixes in paths (e.g., `.Workspace`, `.Folder`, `.SemanticModel`).

* The hierarchy structure is:

* Tenant: The top-level container for everything.

* Workspace: Personal or team workspace holding folders, items, and workspace-level elements.

* Folder: Container for organizing items within a workspace (supports ~10 levels of nesting).

* Item: Individual resource within a workspace or folder (e.g., Notebook, SemanticModel, Lakehouse).

* OneLakeItem: OneLake storage item residing within a Lakehouse (tables, files, etc.).

* Prefer and generate paths like:

* `/Workspace1.Workspace/Notebook1.Notebook`

* `/Workspace1.Workspace/FolderA.Folder/SemanticModel1.SemanticModel`

* `/Workspace1.Workspace/FolderA.Folder/lh1.Lakehouse/Tables` (OneLakeItem)

* When a user provides an ambiguous identifier, ask for the full path (or infer with stated assumptions).

## 2 - Modes (interactive vs command line)

* Be explicit about which mode a user is in:

* Interactive mode behaves like a REPL and runs commands without the `fab` prefix.

* Command line mode runs one command per invocation and is best for scripts/automation.

* The selected mode is preserved between sessions. If a user exits and logs back in, the CLI resumes in the same mode last used.

* When you provide instructions, show commands in command line mode unless the user says they're in interactive mode.

## 3 - Authentication (public-safe guidance)

* Prefer these auth patterns and do not invent new flows:

* Interactive user: `fab auth login` (browser/WAM where supported).

* Service principal (secret/cert): use environment variables / secure mechanisms; avoid embedding secrets in files.

* Service principal (federated credential): use the federated token environment variable (`FAB_SPN_FEDERATED_TOKEN`) and do not persist the raw token.

* Managed identity: supported for Azure-hosted workloads; no credentials required.

* Never ask users to paste secrets into chat or print them back.

## 4 - Sensitive data handling (strict)

* Never log or output tokens, passwords, client secrets, or raw federated tokens.

* Validate all user inputs that could affect security:

* Paths: Sanitize file paths and API parameters.

* GUIDs: Validate resource identifiers before use.

* JSON: Validate JSON inputs for proper format.

* If a user shares sensitive strings, advise rotating/regenerating them and moving to secure storage.

## 5 - Hidden entities and discovery

* Hidden entities are special resources not normally visible, following a dot-prefixed naming convention (similar to UNIX hidden files).

* Tenant-level hidden entities (accessed from root):

* `.capacities` — `fab ls .capacities` / `fab get .capacities/<name>.Capacity`

* `.gateways` — `fab ls .gateways` / `fab get .gateways/<name>.Gateway`

* `.connections` — `fab ls .connections` / `fab get .connections/<name>.Connection`

* `.domains` — `fab ls .domains` / `fab get .domains/<name>.Domain`

* Workspace-level hidden entities (accessed within a workspace):

* `.managedidentities` — `fab ls ws1.Workspace/.managedidentities`

* `.managedprivateendpoints` — `fab ls ws1.Workspace/.managedprivateendpoints`

* `.externaldatashares` — `fab ls ws1.Workspace/.externaldatashares`

* `.sparkpools` — `fab ls ws1.Workspace/.sparkpools`

* To show hidden resources, recommend `ls -a` / `ls --all`.

## 6 - Errors and troubleshooting guidance

* When describing failures, include:

* What the command was trying to do

* The likely cause

* The next actionable step

* If the CLI surfaces an error code/message, keep it intact and do not paraphrase away the key identifiers. (Fabric CLI emphasizes stable error codes/messages.)

* Include request IDs for API errors to aid debugging when available.

## 7 - Output conventions for the agent

* Default to concise, runnable steps.

* When recommending commands, include:

* Preconditions (auth, correct workspace/path)

* Expected result

* How to verify (e.g., follow-up `fab ls` / `fab get`)

## 8 - Safety defaults

* Ask before suggesting commands that delete, overwrite, or change access/permissions.

* If the user explicitly confirms, proceed with a clear rollback note when possible.

## 9 - Platform and troubleshooting reference

* Supported platforms: Windows, Linux, macOS.

* Supported shells: zsh, bash, PowerShell, cmd (Windows command prompt).

* Python versions: 3.10, 3.11, 3.12, 3.13.

* CLI file storage (useful for troubleshooting):

* Config files are stored in `~/.config/fab/`:

* `cache.bin` — encrypted auth token cache

* `config.json` — non-sensitive CLI settings

* `auth.json` — non-sensitive auth info

* `context-<session_id>` — path context for command-line mode sessions

* Debug logs are written to:

* Windows: `%AppData%/fabcli_debug.log`

* macOS: `~/Library/Logs/fabcli_debug.log`

* Linux: `~/.local/state/fabcli_debug.log`

## 10 - Critical operational rules

* First run: Always run `fab auth status` to verify authentication before executing commands. If not authenticated, ask the user to run `fab auth login`.

* Learn before executing: Always use `fab --help` and `fab <command> --help` the first time you use a command to understand its syntax.

* Start simple: Try the basic `fab` command alone first before piping or chaining.

* Non-interactive mode: Use `fab` in command-line mode when working with coding agents. Interactive mode doesn't work with automation.

* Force flag: Use `-f` when executing commands if the flag is available to run non-interactively (skips confirmation prompts).

* Verify before acting: If workspace or item name is unclear, ask the user first, then verify with `fab ls` or `fab exists` before proceeding.

* Permission errors: If a command is blocked by permissions, stop and ask the user for clarification; never try to circumvent it.

## 11 - Common item types

ExtensionDescription`.Workspace`Workspace container`.Folder`Folder within workspace`.SemanticModel`Power BI dataset/semantic model`.Report`Power BI report`.Dashboard`Power BI dashboard`.Notebook`Fabric notebook`.Lakehouse`Lakehouse`.Warehouse`Data warehouse`.DataPipeline`Data pipeline`.SparkJobDefinition`Spark job definition`.Eventstream`Real-time event stream`.KQLDatabase`KQL database`.MLModel`ML model`.MLExperiment`ML experiment`.Capacity`Fabric capacity (hidden)`.Gateway`Data gateway (hidden)`.Connection`Connection (hidden)
Use `fab desc .<ItemType>` to explore any item type.

## 12 - Command references

For detailed command syntax and working examples, see:

* Quick Start Guide — Copy-paste examples for common tasks

* Full Command Reference — All commands with flags and patterns

* Semantic Models — TMDL, DAX queries, refresh, storage modes

* Notebooks — Job execution, parameters, scheduling

* Reports — Export, import, rebind to models

* Workspaces — Create, manage, permissions

* Querying Data — DAX and lakehouse table queries

* API Reference — Direct REST API access patterns

* Create Workspaces — Workspace creation workflows

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**Source**: https://github.com/microsoft/fabric-cli/tree/HEAD/.ai-assets/skills/fabric-cli-core
**Author**: microsoft
**Discovered via**: mcpservers.org