activator-cli
Creates and inspects Fabric Activator (Reflex) alerts: rules, their data sources, conditions,…
Owns Fabric Eventstream items end to end: sources, operators, destinations, routing, retention, throughput and connection strings, plus read-only topology checks. Pick it for anything that names an Eventstream, creating and listing included. Where the rows finally land is
$ npx -y skills add microsoft/skills-for-fabric --skill eventstream-cli --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/eventstream-cliContext preview
The summary Claude sees to decide when to auto-load this skill.
Owns Fabric Eventstream items end to end: sources, operators, destinations, routing, retention, throughput and connection strings, plus read-only topology checks. Pick it for anything that names an Eventstream, creating and listing included. Where the rows finally land is
name: eventstream-cli description: "Owns Fabric Eventstream items end to end: sources, operators, destinations, routing, retention, throughput and connection strings, plus read-only topology checks. Pick it for anything that names an Eventstream, creating and listing included. Where the rows finally land is eventhouse-cli."
> **Telemetry — MANDATORY.** Every `api.fabric.microsoft.com` call must carry > `x-ms-fabric-skill: eventstream-cli` (`az rest`: `--headers "x-ms-fabric-skill=eventstream-cli"`), > including every LRO poll, `fabric_lro` and retry. Snippets omit it — add it anyway.
> **CRITICAL NOTES** > 1. To find the workspace details (including its ID) from workspace name: list all workspaces and, then, use JMESPath filtering > 2. 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 > 3. **Skill disambiguation**: use `eventstream-cli` for 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 matching `eventhouse-cli` mode; alerting uses the matching Activator authoring or consumption 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 | 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](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](references/consumption.md) |
`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.
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.
Resolve the workspace and Eventstream first; every mode depends on it.
| Task | Reference | Notes | |---|---|---| | Finding Workspaces and Items in Fabric | [COMMON-CLI.md](../../common/COMMON-CLI.md#finding-workspaces-and-items-in-fabric) | **Mandatory** -- read before resolving any workspace or item id | | Fabric Topology & Key Concepts | [COMMON-CORE.md](../../common/COMMON-CORE.md#fabric-topology--key-concepts) | Item types, workspaces, capacities | | Environment URLs | [COMMON-CORE.md](../../common/COMMON-CORE.md#environment-urls) | Sovereign / non-public cloud hosts | | Authentication & Token Acquisition | [COMMON-CORE.md](../../common/COMMON-CORE.md#authentication--token-acquisition) | Wrong audience = 401; read before any auth issue | | Authentication Recipes | [COMMON-CLI.md](../../common/COMMON-CLI.md#authentication-recipes) | `az login` flows and token acquisition | | Core Control-Plane REST APIs | [COMMON-CORE.md](../../common/COMMON-CORE.md#core-control-plane-rest-apis) | Pagination, LRO polling, rate limiting | | Gotchas & Troubleshooting | [COMMON-CLI.md](../../common/COMMON-CLI.md#gotchas--troubleshooting-cli-specific) | `az rest` audience, shell escaping, token expiry |
Microsoft Fabric Skills are reusable AI assistant instructions for working with Microsoft Fabric. They help GitHub Copilot CLI and compatible AI coding tools understand Fabric workloads, APIs, query patterns, and operational best practices.
Repo: microsoft/skills-for-fabric
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