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Activator CLI

MicrosoftOfficialPublished by Microsoft

  • Skill
  • Tool integration
  • Data and AI
  • MIT
  • Low risk

From the author

Creates and inspects Fabric Activator (Reflex) alerts: rules, their data sources, conditions, and the Teams or email action they fire, plus decoding an existing ReflexEntities definition. Choose it whenever someone wants to be told, or something done, when values cross a threshold. The pipeline delivering those values is eventstream-cli.
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The activator-cli skill provides a structured interface for interacting with Microsoft Fabric Activator (Reflex) items. It acts as a mode-based dispatcher that separates authoring tasks (creating, updating, or deleting alert rules, sources, and actions) from consumption tasks (listing, inspecting, and decoding existing definitions). The skill enforces strict validation gates for data sources and requires specific handling of JSON payloads to ensure compatibility with Fabric APIs.

What it does

  • Creates and configures Activator alert rules and data sources.
  • Defines automated actions including Teams notifications, emails, and Fabric item invocations.
  • Inspects and decodes existing ReflexEntities definitions.
  • Lists and filters workspaces and Activator items for management.
  • Validates data sources and signals before rule authoring.
  • Manages the lifecycle of Reflex items through REST API operations.

When to use it

  • When you need to set up automated alerts based on data thresholds.
  • When you need to inspect or audit existing alert rules and their configurations.
  • When you need to integrate Fabric Activator with Teams or email for operational notifications.
  • When you need to programmatically manage Reflex item definitions.

Advantages

  • Provides a clear separation between read-only inspection and state-changing authoring.
  • Includes built-in validation gates to prevent invalid rule creation.
  • Supports complex alert logic including transition-based detectors.
  • Standardizes the handling of Fabric API authentication and telemetry.

Usage examples

“Create an Activator named sales_alert in my workspace.”
The agent will switch to authoring mode, read the authoring reference, and execute the POST request to create the Reflex item.
“Show me all Activators in this workspace.”
The agent will use consumption mode to list and filter the Reflex items within the specified workspace.
“Notify me on Teams when the average temperature goes above 30.”
The agent will validate the temperature source, configure the rule condition, and set up the TeamsMessage action.
“What rule and action are behind SkillsTestActivator?”
The agent will use consumption mode to retrieve and decode the ReflexEntities definition for the specified item.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/microsoft/activator-cli/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip activator-cli.zip -d .agents/skills

Documentation by Microsoft

Telemetry — MANDATORY. Every api.fabric.microsoft.com call must carry x-ms-fabric-skill: activator-cli (az rest: --headers "x-ms-fabric-skill=activator-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 activator-cli for every Fabric Activator / Reflex item — both authoring alert rules and inspecting existing alerts. The streaming topology that feeds an alert belongs to eventstream-cli, the KQL database behind it to eventhouse-cli, and Power BI report questions to fabriciq.

Fabric Activator (Reflex) — CLI Skill

This one skill owns Fabric Activator / Reflex items: alert rules, their sources, their actions, and the ReflexEntities.json definition that holds them.

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, entity schemas, templates and gotchas; acting without it produces invalid ReflexEntities.json payloads and 400s.

The reference is needed to act, not to ask. If the request is under-specified and your next message will be a clarifying question with no Fabric call in it, ask it now and read the reference when you go on to act.

Mode selection

ModeUse when the request ...Example triggersRead this first
authoringcreates, updates, configures or deletes an Activator item, rule, source or actioncreate an alert, create an activator, create a reflex, notify me when, let me know when, take action when, send me an email when, send a teams message when, run a pipeline when, update an alert, delete an alertreferences/authoring.md
consumptionlists, inspects, decodes or explains existing Activators, rules, sources or actionsshow my alerts, what alerts do I have, list activators, inspect this alert, show me the rule, show me the source, get reflex definition, why does this alert firereferences/consumption.md
Mode boundary rule

consumption is read-only. A request to create, update, configure or delete an Activator item, rule, source or action requires authoring: say so, read references/authoring.md, then proceed.

A pure GET / explain request stays in consumption — do not switch to authoring and do not mutate anything to answer it.

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, decoding a definition and assembling entities is NOT completing the task. Authoring ends with one state-changing call. If you did not issue it, nothing was persisted — say so explicitly rather than reporting success.

ModeTerminal write
authoringPOST /v1/workspaces/{ws}/reflexes to create the item, POST /v1/workspaces/{ws}/reflexes/{id}/updateDefinition to persist rules, sources and actions, or DELETE /v1/workspaces/{ws}/reflexes/{id} to remove it. Building, stringifying or base64-encoding ReflexEntities.json is not the write.
consumptionnone — this mode is read-only

Before you report an authoring task done, confirm the terminal call returned an explicit success (HTTP 200/201, or a terminal LRO success for a 202), then read the definition back where the mode reference documents a readback. Power BI sources are the exception: public ALM export can reject an artifact that imported successfully, so an empty or unavailable readback is not proof the write failed — report the updateDefinition result and the readback limitation separately, per references/authoring/powerbi-source.md.

Source validation gate (authoring only)

Before authoring any rule that references a signal, confirm the source is real: resolve it in the requested workspace only, validate that the requested column/field/property exists on it, and observe at least one representative row, event or sample carrying that signal.

Schema-only, zero-row, non-emitting or stale evidence is missing source data. When the source is missing, stop and ask which source and fields provide the signal — do not create a Reflex and do not call updateDefinition on an unrelated existing Activator or Eventstream to force-fit the request, and state plainly that no Activator / Reflex / Eventstream was created or updated. The only exception is an explicit instruction to author against a future / not-yet-emitting source, which you must state as an assumption.

Everything you need to run this gate is on this page. When the request already lacks the source mapping, threshold, recipients or action target, ask for them first — do not read references/authoring.md, and do not call a Fabric API, just to discover that the request is under-specified.

Shared essentials (all modes)

Resolve the workspace and the Activator item first; every mode depends on it — list and filter by display name exactly as CRITICAL NOTES 1 and 2 describe. That recipe is self-contained and is all you need to start.

The table below is optional background living in the shared common/ docs. Open a row only when you actually need that detail. If common/ is not present in your environment, say so in one line and continue with the mode reference — never glob, list or search the filesystem looking for it.

TaskReferenceNotes
Finding Workspaces and Items in FabricCOMMON-CLI.mdPagination and JMESPath filtering detail
Fabric Topology & Key ConceptsCOMMON-CORE.mdItem types, workspaces, capacities
Authentication & Token AcquisitionCOMMON-CORE.mdWrong audience = 401; read before any auth issue
Authentication RecipesCOMMON-CLI.mdaz login flows and token acquisition
Core Control-Plane REST APIsCOMMON-CORE.mdPagination, LRO polling, rate limiting
Fabric Item DefinitionsITEM-DEFINITIONS-CORE.mdBase64-encoded parts structure
Gotchas & TroubleshootingCOMMON-CLI.mdaz rest audience, shell escaping, token expiry

Activator uses the reflexes collection, not the generic items collection: /v1/workspaces/{workspaceId}/reflexes[/{reflexId}].

Rules

MUST
  • Select exactly one mode from the table above before doing anything else.

  • Read references/<mode>.md end to end, as your FIRST tool call, before the first command of that mode. A reply that only asks a clarifying question, and issues no Fabric call, does not need it yet.

  • Pass --resource https://api.fabric.microsoft.com on every az rest call — without it the token audience is wrong and the call returns 401.

  • Call getDefinition as a POST with --body '{}', then Base64-decode the ReflexEntities.json part before inspecting it; a GET returns 405 and an omitted body can return 411.

  • Poll the Location header when create, getDefinition or updateDefinition returns 202.

  • Resolve workspace and Activator 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.

  • In authoring, clear the source validation gate before you author a rule, and build ReflexEntities.json with Python json.dumps() — PowerShell's ConvertTo-Json corrupts the nested JSON strings that definition.instance requires.

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.

  • Read-modify-write over full replacement in authoring: get the current definition, modify the entity array, then update.

  • Transition-based detectors (NumberBecomes, NumberEntersOrLeavesRange, LogicalBecomes) over steady-state conditions in authoring, unless the user explicitly asks for repeated firing while the value stays in the triggered state.

  • A summary view before individual entities in consumption: give the high-level picture, then drill in.

  • Offering an alert when earlier work in this session surfaced a timely operational signal — a spike, failure, anomaly, SLA risk or capacity constraint — rather than waiting to be asked. Ask once, and author nothing until the user agrees.

AVOID
  • Acting from this dispatcher alone — it intentionally omits the entity schemas and templates.

  • Answering with a summary of the reference instead of executing it.

  • Mutating anything while in the read-only consumption mode, including "just to check".

  • Hardcoded workspace or item ids in either mode — always resolve dynamically.

  • Globbing, listing or shell-searching the filesystem for the common/ docs. They are optional background; if a link does not resolve, note it in one line and carry on.

  • Building the Eventstream topology that feeds an alert here; that is eventstream-cli. Querying the KQL data behind an alert is eventhouse-cli.

  • Loading a different skill for work this skill already owns (see CRITICAL NOTES 3).

Examples

User requestModeReference to read
"Create an Activator named eval_smoke_activator in my workspace."authoringreferences/authoring.md
"Notify me on Teams when the average temperature goes above 30."authoringreferences/authoring.md
"Delete the alert that emails me about failed pipeline runs."authoringreferences/authoring.md
"Show me all Activators in this workspace."consumptionreferences/consumption.md
"What rule and action are behind SkillsTestActivator?"consumptionreferences/consumption.md
"Decode this Reflex definition and explain the Power BI source."consumptionreferences/consumption.md

Files

references/authoring/action-types.md

Activator Action Types — Rule Action Bindings

Complete reference for all supported action types that rules can trigger when conditions are met.


Where Actions Live

Actions appear in two places in ReflexEntities.json:

  1. Inside a Rule's ActStep — the action binding (TeamsMessage, EmailMessage) is defined inline as a row in the ActStep

  2. As a standalone entity — fabricItemAction-v1 entities define Fabric items (Pipelines, Notebooks, Spark jobs, Dataflows, Functions/UDFs) that rules can invoke


Action Types Summary

ActionKind (in ActStep)Entity TypeDescription
Teams MessageTeamsMessage(inline in rule)Send a Teams notification
EmailEmailMessage(inline in rule)Send an email
Fabric ItemFabricItemInvocationfabricItemAction-v1Execute a Pipeline, Notebook, Spark job, Dataflow, or Function/UDF

Note: There is no dedicated "Power Automate flow" or "Custom endpoint/webhook" action type in the public definition API.


TeamsMessage

Sends a notification to Microsoft Teams. Recipients are specified by email address.

{
  "name": "TeamsBinding",
  "kind": "TeamsMessage",
  "arguments": [
    { "name": "messageLocale", "type": "string", "value": "" },
    { "name": "recipients", "type": "array", "values": [
        { "type": "string", "value": "[email protected]" },
        { "type": "string", "value": "[email protected]" }
    ]},
    { "name": "headline", "type": "array", "values": [
        { "type": "string", "value": "Alert headline text" }
    ]},
    { "name": "optionalMessage", "type": "array", "values": [
        { "type": "string", "value": "Detailed message body with context" }
    ]},
    { "name": "additionalInformation", "type": "array", "values": [] }
  ]
}
ArgumentTypeRequiredDescription
messageLocalestringnoLanguage/locale (empty string for default)
recipientsarray of stringsyesEmail addresses of recipients
headlinearray of content partsyesMessage title shown in Teams notification
optionalMessagearray of content partsnoDetailed message body
additionalInformationarraynoExtra context data
TeamsMessage Design Guidance
  • Multiple recipients receive independent notifications

  • The headline should be concise and actionable — it's the first thing users see

  • Use optionalMessage for context that helps the recipient understand and act on the alert

  • Inline dynamic content can be mixed into headline / optionalMessage by embedding AttributeReference parts directly in the field's values array

  • For inline message parts, use {"kind":"AttributeReference","type":"complex","arguments":[...]} or {"kind":"EventFieldReference","type":"complex","arguments":[...]} — do not convert those inline parts to complexReference

  • For attribute-trigger rules, reference attributes by entity ID; for event-trigger rules, reference event fields by field name

  • The additionalInformation field can include structured dynamic data via NameReferencePair

  • Structured additionalInformation uses nested AttributeReference / EventFieldReference entries with type: "complexReference" and name: "reference"

Working inline mixed-content example:

{
  "name": "optionalMessage",
  "type": "array",
  "values": [
    { "name": "string", "type": "string", "value": "The humidity of this package has crossed above or below the allowed range." },
    {
      "kind": "AttributeReference",
      "type": "complex",
      "arguments": [{ "name": "entityId", "type": "string", "value": "<attr-id>" }]
    },
    { "name": "string", "type": "string", "value": " " }
  ]
}

Working event field message part:

{
  "kind": "EventFieldReference",
  "type": "complex",
  "arguments": [
    { "name": "fieldName", "type": "string", "value": "Status" }
  ]
}

Working additionalInformation example:

{
  "kind": "NameReferencePair",
  "type": "complex",
  "arguments": [
    { "name": "name", "type": "string", "value": "Temperature" },
    {
      "name": "reference",
      "kind": "AttributeReference",
      "type": "complexReference",
      "arguments": [
        { "name": "entityId", "type": "string", "value": "<temperature-attribute-guid>" }
      ]
    }
  ]
}

EmailMessage

Sends an email alert with configurable recipients (To, CC, BCC), subject, and body.

⚠️ Authoring guidance

In current backend behavior, authoring should use array-shaped content fields for subject, headline, optionalMessage, and additionalInformation, matching working readback and successful eval output.

{
  "name": "EmailBinding",
  "kind": "EmailMessage",
  "arguments": [
    { "name": "messageLocale", "type": "string", "value": "en-us" },
    { "name": "sentTo", "type": "array", "values": [
        { "type": "string", "value": "[email protected]" }
    ]},
    { "name": "copyTo", "type": "array", "values": [
        { "type": "string", "value": "[email protected]" }
    ]},
    { "name": "bCCTo", "type": "array", "values": [] },
    { "name": "subject", "type": "array", "values": [
        { "type": "string", "value": "Alert: Sales threshold exceeded" }
    ]},
    { "name": "headline", "type": "array", "values": [
        { "type": "string", "value": "Main alert content displayed prominently" }
    ]},
    { "name": "optionalMessage", "type": "array", "values": [
        { "type": "string", "value": "Additional context and recommended actions" }
    ]},
    { "name": "additionalInformation", "type": "array", "values": [] }
  ]
}
ArgumentTypeRequiredDescription
messageLocalestringnoe.g. en-us
sentToarray of stringsyesPrimary recipients (To)
copyToarray of stringsnoCC recipients
bCCToarray of stringsnoBCC recipients
subjectarray of content partsyesEmail subject line
headlinearray of content partsyesMain content displayed prominently
optionalMessagearray of content partsnoAdditional body text
additionalInformationarraynoExtra context
EmailMessage vs TeamsMessage Differences
FieldTeamsMessageEmailMessage
Recipientsrecipients (array)sentTo + copyTo + bCCTo
SubjectN/Asubject (array)
Headlinearray of content partsarray of content parts
Messagearray of content partsarray of content parts

Fabric Item Action (fabricItemAction-v1)

A standalone entity that defines a Fabric item (Pipeline, Notebook, Spark job, Dataflow, or Function/UDF) to execute when a rule fires. Rules reference this entity by uniqueIdentifier.

{
  "uniqueIdentifier": "<fabric-item-action-guid>",
  "payload": {
    "name": "Run alert pipeline",
    "fabricItem": {
      "itemId": "<pipeline-item-guid>",
      "workspaceId": "<workspace-guid>",
      "itemType": "Pipeline"
    },
    "jobType": "Pipeline",
    "parentContainer": {
      "targetUniqueIdentifier": "<container-guid>"
    }
  },
  "type": "fabricItemAction-v1"
}
PropertyTypeRequiredDescription
namestringyesDisplay name
fabricItem.itemIdGUIDyesFabric item ID
fabricItem.workspaceIdGUIDyesWorkspace containing the item
fabricItem.itemTypestringyesPipeline, SynapseNotebook, SparkJobDefinition, DataflowFabric, UserDataFunctions, or FunctionSet
jobTypestringyesJob type (for example Pipeline, RunNotebook, sparkjob, or Execute)
parentContainer.targetUniqueIdentifierGUIDyesContainer ref
Supported Fabric Item Types
itemTypejobTypeDescription
PipelinePipelineRun a Data Factory pipeline
SynapseNotebookRunNotebookRun a Fabric notebook
SparkJobDefinitionsparkjobRun a Spark job definition
DataflowFabricExecuteRun a Dataflow
UserDataFunctionsExecuteRun a user data function
FunctionSetExecuteAlias of UserDataFunctions; run a function from a function set

⚠️ Notebooks use itemType: "SynapseNotebook" with jobType: "RunNotebook" (not "Notebook" or "SparkJob").

⚠️ FunctionSet is handled as an alias of UserDataFunctions in backend execution.

⚠️ The public Fabric items API exposes the underlying item type as UserDataFunction (singular), but Activator action payloads still use itemType: "UserDataFunctions" (plural).

⚠️ Readback nuance for UDF / function-set actions: on write/import, authoring commonly uses UserDataFunctions. On a later getDefinition readback, the standalone fabricItemAction-v1 entity may normalize payload.fabricItem.itemType to FunctionSet, while the rule's embedded FabricItemBinding.arguments.itemType still remains UserDataFunctions.

⚠️ UDF prerequisite: before wiring a UDF action, verify the target UserDataFunction item exposes the function you plan to call. If the item has no registered functions, fix the UDF definition first; do not treat the Activator action as valid.

Target-Specific fabricItemAction-v1 Examples
Notebook
{
  "uniqueIdentifier": "<notebook-action-guid>",
  "payload": {
    "name": "Run alert notebook",
    "fabricItem": {
      "itemId": "<notebook-item-guid>",
      "workspaceId": "<workspace-guid>",
      "itemType": "SynapseNotebook"
    },
    "jobType": "RunNotebook",
    "parentContainer": {
      "targetUniqueIdentifier": "<container-guid>"
    }
  },
  "type": "fabricItemAction-v1"
}
Spark Job Definition
{
  "uniqueIdentifier": "<spark-job-action-guid>",
  "payload": {
    "name": "Run alert spark job",
    "fabricItem": {
      "itemId": "<spark-job-item-guid>",
      "workspaceId": "<workspace-guid>",
      "itemType": "SparkJobDefinition"
    },
    "jobType": "sparkjob",
    "parentContainer": {
      "targetUniqueIdentifier": "<container-guid>"
    }
  },
  "type": "fabricItemAction-v1"
}
Dataflow
{
  "uniqueIdentifier": "<dataflow-action-guid>",
  "payload": {
    "name": "Run alert dataflow",
    "fabricItem": {
      "itemId": "<dataflow-item-guid>",
      "workspaceId": "<workspace-guid>",
      "itemType": "DataflowFabric"
    },
    "jobType": "Execute",
    "parentContainer": {
      "targetUniqueIdentifier": "<container-guid>"
    }
  },
  "type": "fabricItemAction-v1"
}
User Data Function / Function Set
{
  "uniqueIdentifier": "<udf-action-guid>",
  "payload": {
    "name": "Run alert function",
    "fabricItem": {
      "itemId": "<udf-item-guid>",
      "workspaceId": "<workspace-guid>",
      "itemType": "UserDataFunctions"
    },
    "jobType": "Execute",
    "parentContainer": {
      "targetUniqueIdentifier": "<container-guid>"
    }
  },
  "type": "fabricItemAction-v1"
}
How Rules Reference Fabric Item Actions

The ActStep uses a FabricItemBinding row with kind FabricItemInvocation. This is the same structure in both AttributeTrigger and EventTrigger — the ActStep grammar is identical across all trigger types.

All 7 base arguments are required (including empty arrays). Some item types add more arguments; for example UDF / Function Set bindings add subitemId.

Use a template version that supports every argument in the binding. Parameters require at least 1.2, and flexible item types / UDF subitemId require at least 1.2.3; the default rule template version 1.2.4 covers these known requirements.

Set fabricJobConnectionDocumentId to the uniqueIdentifier of the standalone fabricItemAction-v1 entity. The backend treats that value as the reference from the rule binding row to the action document; do not replace it with the Fabric item ID.

For Spark Job Definition ActStep bindings, use itemType: "SparkJobDefinition". The exact jobType value is backend-passed-through; prefer a known-good payload/readback for the target environment instead of guessing.

{
  "name": "FabricItemBinding",
  "kind": "FabricItemInvocation",
  "arguments": [
    { "name": "workspaceId", "type": "string", "value": "<workspace-guid>" },
    { "name": "itemId", "type": "string", "value": "<pipeline-or-notebook-guid>" },
    { "name": "itemType", "type": "string", "value": "Pipeline" },
    { "name": "jobType", "type": "string", "value": "Pipeline" },
    { "name": "fabricJobConnectionDocumentId", "type": "string", "value": "<fabric-item-action-guid>" },
    { "name": "additionalInformation", "type": "array", "values": [] },
    { "name": "parameters", "type": "array", "values": [] }
  ]
}

⚠️ Common mistakes that cause RowCountMismatch:

  1. Missing arguments — all 7 base arguments are required, including additionalInformation and parameters as empty arrays

  2. Wrong row name — must be "FabricItemBinding" (not "FabricItemInvocation" — that's the kind)

  3. Multiple rows in ActStep — ActStep allows exactly ONE action binding row

For UserDataFunctions and FunctionSet, include a subitemId string argument in the binding to name the specific function to execute. Match the binding's parameterName values to the names exposed by the Fabric function metadata, and use Activator's canonical parameterType values — String, Number, or Boolean — for each parameter. The Fabric function metadata may surface Python type names such as str, float, or int; do not pass those through as parameterType on the binding — the rule validator rejects them. Map them to the canonical Activator types instead:

Fabric function metadata dataTypeActivator binding parameterType
strString
int, floatNumber
boolBoolean

Recommended authoring pattern: keep the binding itemType as UserDataFunctions even if a later readback shows the standalone action entity as FunctionSet.

Linkage prerequisite: subitemId must match a real function exposed by the target User Data Function item. If the item exists but exposes no functions, fix the UDF definition first; the Activator linkage is not valid until a function is registered.

For dynamic parameter values inside FabricItemParameter.parameterValue, use reference-valued parts with type: "complexReference". This differs from inline Teams headline / optionalMessage fragments, where type: "complex" is correct.

{
  "name": "FabricItemBinding",
  "kind": "FabricItemInvocation",
  "arguments": [
    { "name": "workspaceId", "type": "string", "value": "<workspace-guid>" },
    { "name": "itemId", "type": "string", "value": "<function-set-guid>" },
    { "name": "itemType", "type": "string", "value": "UserDataFunctions" },
    { "name": "jobType", "type": "string", "value": "Execute" },
    { "name": "fabricJobConnectionDocumentId", "type": "string", "value": "<udf-action-guid>" },
    { "name": "additionalInformation", "type": "array", "values": [] },
    { "name": "parameters", "type": "array", "values": [
        {
          "kind": "FabricItemParameter",
          "type": "complex",
          "arguments": [
            { "name": "parameterName", "type": "string", "value": "name" },
            { "name": "parameterType", "type": "string", "value": "String" },
            { "name": "parameterValue", "type": "complexArray", "values": [
                { "type": "string", "value": "world" }
            ]}
          ]
        },
        {
          "kind": "FabricItemParameter",
          "type": "complex",
          "arguments": [
            { "name": "parameterName", "type": "string", "value": "temperature" },
            { "name": "parameterType", "type": "string", "value": "Number" },
            { "name": "parameterValue", "type": "complexArray", "values": [
                {
                  "kind": "AttributeReference",
                  "type": "complexReference",
                  "arguments": [
                    { "name": "entityId", "type": "string", "value": "<temperature-attribute-guid>" }
                  ]
                }
            ]}
          ]
        }
    ]},
    { "name": "subitemId", "type": "string", "value": "<published-function-name>" }
  ]
}
Additional gotchas for dynamic FabricItemParameter values

The worked UDF binding example above covers the canonical static + dynamic pattern. A few additional gotchas are worth calling out explicitly because they each produced a 400 with a misleading error pointed at the leaf rule rather than the offending field:

Envelope contrast — same AttributeReference, two shapes

AttributeReference appears in several places inside the rule graph, and the envelope differs by location. Reuse the wrong shape and you get a 400. The two shapes you will see in the same definition:

Where it appearsEnvelope
Inside ScalarSelectStep / DimensionalFilterStep rows{ "kind": "AttributeReference", "type": "complex", "name": "attribute", "arguments": [...] }
Inside FabricItemParameter.parameterValue.values{ "kind": "AttributeReference", "type": "complexReference", "arguments": [...] } (no name field)

For the structured additionalInformation form used by Teams / Email actions, see the TeamsMessage guidance further up — that one uses type: "complexReference" with name: "reference", which is yet a different envelope.

AttributeReference.entityId must point at a BasicEventAttribute

Inside FabricItemParameter.parameterValue, the AttributeReference.entityId must resolve to a BasicEventAttribute entity in the same definition. Pointing at an IdentityPartAttribute returns 400 Invalid TimeSeriesView payload. with no hint about the template type. If you want to pass an identity field dynamically, declare a parallel BasicEventAttribute over the same source field and reference that.

Backend Execution Payload Shapes

The runtime request body sent to the Fabric jobs endpoint depends on itemType:

Notebook (SynapseNotebook)
{
  "ExecutionData": {
    "Parameters": {
      "name": { "value": 345.13, "type": "float" },
      "isName": { "value": true, "type": "bool" },
      "NotebookName": { "value": "MyNotebook", "type": "string" }
    }
  }
}
Spark Job Definition (SparkJobDefinition)
{
  "ExecutionData": {
    "mainClass": "com.microsoft.spark.example.OnePlusOneApp",
    "executableFile": "abfss://[email protected]/lakehouse.Lakehouse/Files/job.jar",
    "commandLineArguments": "--input bronze --output silver"
  }
}

Spark job definitions are schema-supported, but current backend parameter discovery returns no user-defined parameters. Use explicit parameter names like mainClass, executableFile, and commandLineArguments.

Dataflow (DataflowFabric)
{
  "ExecutionData": {
    "ExecuteOption": "ApplyChangesIfNeeded",
    "Parameters": [
      { "parameterName": "Threshold", "type": "Automatic", "value": 25 },
      { "parameterName": "Mode", "type": "Automatic", "value": "Incremental" }
    ]
  }
}
User Data Function / Function Set (UserDataFunctions / FunctionSet)
{
  "ExecutionData": {
    "FunctionName": "hello_fabric",
    "Parameters": {
      "name": "world"
    },
    "RunKind": "Activator",
    "RelatedArtifacts": "<activator-artifact-guid>"
  }
}
Fabric Item Action Design Guidance
  • The target Fabric item must already exist in the target workspace

  • Resolve itemId and workspaceId dynamically via the Fabric Items API — do not hardcode

  • The Activator's managed identity must have permissions to execute the target item

  • Pipeline, notebook, dataflow, Spark job, and function actions can all pass parameters from the triggering event, but the runtime payload shape differs by item type

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

What our scanner noticed· Low risk

  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/skills-for-fabric · skills/activator-cli · commit f8fac11
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced
Also distributed in
microsoft/skills-for-fabric

AutoGineer is not affiliated with or endorsed by Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download activator-cli.zip