
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 need to automate Fabric operations.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/microsoft/fabric-cli --skill fabric-cli-core- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads fabric-cli-core automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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.
| Script | Purpose | Usage |
|---|---|---|
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
fabprefix. - Command line mode runs one command per invocation and is best for scripts/automation.
- Interactive mode behaves like a REPL and runs commands without the
- 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.
- Interactive user:
- 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, 3.14.
- CLI file storage (useful for troubleshooting):
- Config files are stored in
~/.config/fab/:cache.bin— encrypted auth token cacheconfig.json— non-sensitive CLI settingsauth.json— non-sensitive auth infocontext-<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
- Windows:
- Config files are stored in
10 - Critical operational rules
- First run: Always run
fab auth statusto verify authentication before executing commands. If not authenticated, ask the user to runfab auth login. - Learn before executing: Always use
fab --helpandfab <command> --helpthe first time you use a command to understand its syntax. - Start simple: Try the basic
fabcommand alone first before piping or chaining. - Non-interactive mode: Use
fabin command-line mode when working with coding agents. Interactive mode doesn't work with automation. - Force flag: Use
-fwhen 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 lsorfab existsbefore 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
| Extension | Description |
|---|---|
.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
FAQ
What does the fabric-cli-core skill do?
Use Microsoft Fabric CLI (fab) to manage workspaces, semantic models, reports, notebooks, and Fabric resources. Activate when users mention fab, Fabric CLI, or need to automate Fabric operations.
How do I install fabric-cli-core?
Run npx skills add https://github.com/microsoft/fabric-cli --skill fabric-cli-core in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/fabric-cli-core/ (personal) or .claude/skills/fabric-cli-core/ (project).
Which AI agents can use fabric-cli-core?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is fabric-cli-core safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains fabric-cli-core?
It is published by microsoft in microsoft/fabric-cli, and it is an official skill from the maker of the technology it covers. It has 150 recorded installs.
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fabric-cli-powerbi
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Open the skill to read its SKILL.md instructions.
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