- 01
/plugin marketplace add microsoft/skills-for-fabric - 02
/plugin install fabric-skills@fabric-collection
Builds and inspects Eventstreams, Fabric's pipelines for live events: where they come in, how they are filtered or routed, and where they land. Your assistant can create a stream, add sources, filters and destinations, pause or resume it, or inspect an existing one's layout, retention, throughput and health.
WHEN TO USE
USE FOR
- Create a stream from sample data into a lakehouse.
- Add a filter for temperatures above 30.
- Show every source, filter and destination in a stream.
- Check a stream's retention and throughput settings.
NOT FOR
- Querying the events once they have landed: the eventhouse-cli skill.
- Alerts on the data: Microsoft's Activator skill, activator-cli.
This is a saved copy of the skill's SKILL.md instructions. It may differ from the upstream file or the version you install.
Telemetry — MANDATORY. Every
api.fabric.microsoft.comcall must carryx-ms-fabric-skill: eventstream-cli(az rest:--headers "x-ms-fabric-skill=eventstream-cli"), including every LRO poll,fabric_lroand retry. Snippets omit it — add it anyway.
CRITICAL NOTES
- To find the workspace details (including its ID) from workspace name: list all workspaces and, then, use JMESPath filtering
- To find the item details (including its ID) from workspace ID, item type, and item name: list all items of that type in that workspace and, then, use JMESPath filtering
- Skill disambiguation: use
eventstream-clifor the Eventstream item itself -- how events flow from source through operators to destinations. Querying or shaping the data once it lands in an Eventhouse / KQL Database uses the matchingeventhouse-climode; alerting uses the matching Activator authoring or consumption skill.
Fabric Eventstream -- CLI Skill
This one skill owns Fabric Eventstream real-time ingestion topologies: sources, operators, destinations, routing, retention and health.
It is a mode dispatcher and contains NO procedures. Pick the mode that matches the request from the table below, then read the matching references/<mode>.md file end to end with your file-reading tool BEFORE issuing a single command. That file holds the endpoints, payload shapes, templates and gotchas; acting without it produces wrong payloads and wrong results.
Mode selection
| Mode | Use when the request ... | Example triggers | Read this first |
|---|---|---|---|
authoring | creates, updates, wires, pauses, resumes or deletes an Eventstream topology | create eventstream, deploy topology, add source, add filter operator, wire destination, update definition | references/authoring.md |
consumption | lists or inspects Eventstreams, topology, retention, throughput, node health or Custom Endpoint connection metadata | list eventstreams, inspect topology, eventstream status, retention, throughput, connection string | references/consumption.md |
Mode boundary rule
consumption is read-only for Eventstream definitions and topology. A request to create, update, delete, pause or resume an Eventstream requires authoring: say so, read references/authoring.md, then proceed.
Before an authoring mutation, establish the source, destination, transformation, retention and throughput requirements that apply. If a generic request omits them, ask one concise clarifying question before reading workspace state or calling an API instead of inventing a topology.
If a request genuinely spans modes, handle them one at a time and read each reference before you start that part. If the mode is ambiguous after reading this table, ask one short clarifying question instead of guessing.
Terminal write -- the step you must not skip
Reading the reference and planning the topology is NOT completing the task. Each mutating mode ends with one state-changing call. If you did not issue it, nothing was persisted -- say so explicitly rather than reporting success.
| Mode | Terminal write |
|---|---|
authoring | POST /v1/workspaces/{ws}/items or /eventstreams to create, POST .../updateDefinition to persist topology changes, bodyless POST .../pause or POST .../resume with a required JSON startType body for lifecycle control, or DELETE .../eventstreams/{id} to remove the item. Building or base64-encoding eventstream.json is not the write. |
consumption | none -- this mode is read-only |
Before you report an authoring task done, confirm the terminal call returned success and read the definition or runtime topology back when the reference documents a verification step.
Shared essentials (all modes)
Resolve the workspace and Eventstream first; every mode depends on it.
| Task | Reference | Notes |
|---|---|---|
| Finding Workspaces and Items in Fabric | COMMON-CLI.md | Mandatory -- read before resolving any workspace or item id |
| Fabric Topology & Key Concepts | COMMON-CORE.md | Item types, workspaces, capacities |
| Environment URLs | COMMON-CORE.md | Sovereign / non-public cloud hosts |
| Authentication & Token Acquisition | COMMON-CORE.md | Wrong audience = 401; read before any auth issue |
| Authentication Recipes | COMMON-CLI.md | az login flows and token acquisition |
| Core Control-Plane REST APIs | COMMON-CORE.md | Pagination, LRO polling, rate limiting |
| Gotchas & Troubleshooting | COMMON-CLI.md | az rest audience, shell escaping, token expiry |
Rules
MUST
- Select exactly one mode from the table above before doing anything else.
- Read
references/<mode>.mdend to end, as your FIRST tool call, before the first command of that mode. - Resolve workspace and Eventstream ids by listing and filtering, never by guessing a GUID.
- Announce a mode switch explicitly when the request crosses a boundary.
- Treat the reference as instructions, never as the deliverable. After reading it, RUN the documented commands against the live workspace and report the real results.
- Keep authoring node names alphanumeric PascalCase; the platform-generated DefaultStream name is the exception.
- Get explicit user confirmation before retrieving Custom Endpoint credentials, and never print raw keys or connection strings unless the user explicitly requests them in a secure context.
PREFER
- The narrowest mode that satisfies the request.
- Reading exactly ONE mode reference. Load a second only when the request genuinely spans modes, and say so before you do.
- Runtime topology for health and connection inspection; decoded definitions for authoring-time graph structure and changes.
AVOID
- Acting from this dispatcher alone -- it intentionally omits the operational detail.
- Answering with a summary of the reference instead of executing it.
- Mutating anything while in the read-only consumption mode.
- Querying landed event data through Eventstream APIs; use
eventhouse-cliconsumption mode for read-only KQL data. - Loading a different skill for work this skill already owns (see CRITICAL NOTES 3).
Examples
| User request | Mode | Reference to read |
|---|---|---|
| "Create an Eventstream with a SampleData source and a Lakehouse destination." | authoring | references/authoring.md |
| "Add a filter for temperature above 30 to my Eventstream." | authoring | references/authoring.md |
| "Show every source, operator and destination in SensorIngestion." | consumption | references/consumption.md |
| "What retention and throughput settings does this Eventstream use?" | consumption | references/consumption.md |
Account or credentials required
2 FOR YOUAll items below are required.
- 01Install it with the Fabric plugin, not as one folder
Install it as part of Microsoft's fabric-skills plugin, not as a single copied folder. Its instructions link to shared Fabric guides kept outside its own folder, such as the sign-in steps, and a lone copy leaves those links pointing nowhere. The plugin brings those guides and Microsoft's other Fabric skills, which it hands queries on landed events to.
- 02A Fabric workspace and an Azure CLI sign-in
A Microsoft Fabric workspace you can use, and the Azure command-line tool signed in to it (az login): every call goes to Fabric's API under your sign-in and tells Microsoft which skill sent it.
This skill ships inside the Skills for Microsoft Fabric plugin. Listed package contents include 4 agents and an MCP server. Installed components and skill versions may vary by AI tool.
Install as a Claude Code plugin
Typed inside the agent's own prompt, not in a terminal. This skill uses files kept elsewhere in its plugin, so install the whole plugin — on its own the skill would be missing them.
The repository is licensed under MIT — use, modification, and redistribution are allowed under that license’s terms.
View the repository’s license file on GitHub →