Activator Authoring CLI

Update Check — ONCE PER SESSION (mandatory) The first time this skill is used in a session, run the check-updates skill before proceeding.

• GitHub Copilot CLI / VS Code: invoke the check-updates skill (e.g., /fabric-skills:check-updates).
• Claude Code / Cowork / Cursor / Windsurf / Codex: read the local package.json version, then compare it against the remote version via git fetch origin main --quiet && git show origin/main:package.json (or the GitHub API). If the remote version is newer, show the changelog and update instructions.
• Skip if the check was already performed earlier in this session.

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

activator-authoring-cli — Activator Item & Rule Authoring via CLI

Table of Contents

Tool Stack

⚠️ CRITICAL: Always use Python (not PowerShell) to build the ReflexEntities.json payload and the API request body.

Python Patterns

import json, base64, uuid

# Stringify template → JSON string for definition.instance
instance_string = json.dumps(template_dict, separators=(',', ':'))

# Encode entities and write updateDefinition request body
payload_b64 = base64.b64encode(json.dumps(entities).encode('utf-8')).decode('utf-8')
body = json.dumps({"definition": {"parts": [{"path": "ReflexEntities.json", "payload": payload_b64, "payloadType": "InlineBase64"}]}})
with open('update-body.json', 'w', encoding='utf-8') as f:
    f.write(body)
# Then: az rest --method POST --url "...updateDefinition" --resource "https://api.fabric.microsoft.com" --body @update-body.json

# Decode a getDefinition response
response = json.loads(api_output)
for part in response['definition']['parts']:
    if part['path'] == 'ReflexEntities.json':
        entities = json.loads(base64.b64decode(part['payload']).decode('utf-8'))

# Generate GUIDs for uniqueIdentifier and step id fields
entity_id = str(uuid.uuid4())

Connection

Use the shared authentication guidance in COMMON-CLI.md § Authentication Recipes. Resolve workspace and item IDs per COMMON-CLI.md § Finding Workspaces and Items in Fabric. Examples below assume WS_ID and REFLEX_ID are already resolved.

Item CRUD

Use the shared mechanics in COMMON-CLI.md § Item CRUD Operations. Activator uses the reflexes endpoint rather than the generic items endpoint:

Rule Management via Definitions

Rules are managed through getDefinition and updateDefinition. The payload is ReflexEntities.json, a Base64-encoded JSON array of entity objects. Workflow: Get → Decode → Modify → Re-encode → Update.

Get Definition

getDefinition is a POST (not GET), requires ReadWrite scopes, and may return 202 LRO. Use the fabric_lro helper from COMMON-CLI.md § Long-Running Operations (LRO) Pattern so 202 responses can be polled via the Location header before decoding.

DEFINITION=$(fabric_lro POST \
  "https://api.fabric.microsoft.com/v1/workspaces/${WS_ID}/reflexes/${REFLEX_ID}/getDefinition" \
  '{}')

echo "$DEFINITION" \
  | jq '.definition.parts[] | select(.path=="ReflexEntities.json") | .payload' -r \
  | base64 -d | jq .

Update Definition

MUST use Python to build update-body.json (see Python Patterns), then upload it using the COMMON-CLI updateDefinition pattern against /v1/workspaces/{workspaceId}/reflexes/{reflexId}/updateDefinition.

ReflexEntities.json — Assembly Procedure

Build a JSON array of entities in order. Each needs a fresh GUID for uniqueIdentifier. For the hand-authored pull-source flows in this skill, use templateVersion 1.2.4. For Eventstream sink-created flows, preserve the template version already present in the decoded Activator definition; those readbacks can use 1.1.

Step 1 — Container (exactly 1):

• Type: container-v1. Use the container payload type that matches the source graph: kqlQueries for KQL sources, rthSubscriptions for Real-Time Hub workspace subscriptions, or the service-created type already present in readback for Eventstream flows.
• All other entities reference this via parentContainer.targetUniqueIdentifier

Step 2 — Data Source (exactly 1, pick the right type):

• See eventstream-source.md, kql-source.md, dtb-source.md, or real-time-hub-source.md for the supported source workflows
• For hand-authored pull sources, set parentContainer.targetUniqueIdentifier → Container GUID
• For eventstreamSource-v1: do not start by hand-authoring the source. Create or update the Eventstream with an Activator destination first, then read the Activator definition and continue from the auto-created eventstreamSource-v1 + SourceEvent entities. In public readback, those sink-created entities can appear without explicit parentContainer.
• For kqlSource-v1: the KQL query should return ALL data (do NOT pre-filter conditions — let the rule handle that). Must include eventhouseItem, metadata, and queryParameters. For Fabric Eventhouse/KQL DB sources, use eventhouseItem: { itemId, workspaceId, itemType: "KustoDatabase" }. For external ADX/Kusto sources, use eventhouseItem: { clusterHostName, databaseName }. Before creating the Activator, run the KQL directly against the target source first and confirm the returned columns, timestamp field, and row shape are correct. Use eventTimeSettings plus DURATION_START/DURATION_END queryParameters whenever the query results have a reasonable timestamp column, and declare those parameters in the KQL with declare query_parameters(startTime:datetime, endTime:datetime);. Only use snapshot mode (queryParameters: [], no eventTimeSettings, no time filtering) when the underlying data has no reasonable timestamp column and each row represents current state. See kql-source.md.
• For digitalTwinBuilderSource-v1: use a DTB / Ontology connection item ref { itemId, workspaceId, itemType }, where itemType is either DigitalTwinBuilder or Ontology. query.queryString must be a JSON-string payload, not KQL. Before creating the Activator, run the DTB / Ontology query directly first and confirm the returned columns, key fields, and timestamp field are correct. Prefer eventTimeSettings plus DURATION_START/DURATION_END query parameters when the returned rows include a reasonable timestamp field; unlike KQL, those duration parameters are applied as DTB endpoint URL query params rather than referenced inside the query body. See dtb-source.md.

Step 3 — SourceEvent view (exactly 1):

• Type: timeSeriesView-v1, definition.type: "Event", instance: SourceEvent template referencing Source by entityId
• For hand-authored pull-source flows, set parentContainer → Container GUID
• For Eventstream sink-created flows, reuse the auto-created SourceEvent from readback instead of creating a second one

Step 4 — Choose the entity graph based on trigger type

• For AttributeTrigger rules (thresholds, ranges, text matches, boolean checks, aggregations):

  • Create an Object view
  • Optionally create SplitEvent if events must be mapped to object instances
  • Create IdentityPartAttribute and any required BasicEventAttribute entities
  • The rule then references those value attributes in ScalarSelectStep

• For EventTrigger rules (fire on every event, heartbeat, event field state/change):

  • Use the minimal graph: Container → Source → SourceEvent → Rule (+ optional fabricItemAction-v1)
  • Do NOT create Object, SplitEvent, IdentityPartAttribute, or BasicEventAttribute entities unless the scenario truly needs attribute-based modeling
  • EventTrigger reads raw event fields directly in FieldsDefaultsStep / EventDetectStep

Step 5 — Rule (1 per alert):

• Type: timeSeriesView-v1, definition.type: "Rule"
• Always add "description": "Created by: skills-for-fabric" for user clarity
• Instance: rule template (see rule-conditions.md)
  • AttributeTrigger (v1.2.4): ScalarSelectStep → ScalarDetectStep → (DimensionalFilterStep)* → ActStep
  • EventTrigger (v1.2.4): FieldsDefaultsStep → (EventDetectStep)+ → (DimensionalFilterStep)* → ActStep
• instance MUST be a JSON string (use json.dumps())
• Every template step inside instance.steps[] needs an id GUID. Missing step IDs can produce invalid expression graphs because backend translators use the step ID as the output node ID.
• For AttributeTrigger, set parentObject → Object and parentContainer → Container
• For EventTrigger, set parentContainer → Container and omit parentObject unless the design explicitly requires it
• Default to settings: { "shouldRun": true, "shouldApplyRuleOnUpdate": false } so newly created rules start in the started / running state
• Only set shouldRun: false when the user explicitly asks for a stopped rule or when a specific safe verification / eval workflow requires a disabled rule to avoid side effects
• For TeamsMessage actions with dynamic content, preserve the field-specific reference shapes from working readback: inline mixed-content fragments in headline / optionalMessage use AttributeReference with type: "complex", while structured additionalInformation entries use NameReferencePair + AttributeReference / EventFieldReference with type: "complexReference" and name: "reference"

Example rule entity:

{
    "uniqueIdentifier": "<rule-guid>",
    "payload": {
        "name": "My Rule Name",
        "description": "Created by: skills-for-fabric",  # Required for user clarity
        "parentObject": {"targetUniqueIdentifier": "<object-guid>"},
        "parentContainer": {"targetUniqueIdentifier": "<container-guid>"},
        "definition": {
            "type": "Rule",
            "instance": stringify_instance(rule_template),
            "settings": {"shouldRun": True, "shouldApplyRuleOnUpdate": False}
        }
    },
    "type": "timeSeriesView-v1"
}

Step 6 — Fabric Item Action (only for FabricItemInvocation):

• Type: fabricItemAction-v1 — use this standalone action entity whenever the rule invokes a Fabric item such as a Pipeline, Notebook, Spark job definition, Dataflow, or UDF / Function Set
• See action-types.md for schema
• In the rule's FabricItemBinding, set fabricJobConnectionDocumentId to the standalone fabricItemAction-v1.uniqueIdentifier; this is the expected linkage between the binding row and the action entity.
• For UDF / function-set actions, author the rule binding with itemType: "UserDataFunctions". On later getDefinition readback, the standalone fabricItemAction-v1 entity may surface payload.fabricItem.itemType: "FunctionSet" while the embedded FabricItemBinding still shows UserDataFunctions.
• For UDF / function-set actions, verify the target item actually exposes a non-empty function list and set subitemId to the discovered function name. Parameter names and parameterType values must match the discovered Fabric function metadata exactly; omit parameters that are not exposed by the target function. If the target item has no registered functions, the Activator linkage is incomplete and the action should not be treated as valid.

Entity Wiring Summary

Container ← everything references this via parentContainer
    │
    ├── Source ← parentContainer → Container
    │
    ├── SourceEvent ← parentContainer → Container
    │        │         instance references Source by entityId
    │        │
    │        ├── EventTrigger Rule ← parentContainer → Container
    │        │       minimal event-only path; reads raw event fields directly
    │        │
    │        └── Object ← parentContainer → Container
    │              │
    │              ├── (SplitEvent) ← OPTIONAL, parentObject → Object, parentContainer → Container
    │              │       instance references SourceEvent by entityId
    │              │       maps events to objects via FieldIdMapping
    │              │
    │              ├── Identity Attr ← parentObject → Object, parentContainer → Container
    │              │
    │              ├── Value Attr(s) ← parentObject → Object, parentContainer → Container
    │              │       instance references SourceEvent (or SplitEvent if used) by entityId
    │              │
    │              └── AttributeTrigger Rule ← parentObject → Object, parentContainer → Container
    │                      instance references Value Attr by entityId in ScalarSelectStep
    │
    └── (FabricItemAction) ← parentContainer → Container (for any FabricItemInvocation action: Pipeline, Notebook, Spark job, Dataflow, or UDF / Function Set)

Critical: definition.instance is a JSON String

instance inside timeSeriesView-v1 entity's definition is a JSON-encoded string, not a nested object. Always wrap rule templates in the full entity envelope.

❌ WRONG — raw template object (will fail):

{
  "templateId": "AttributeTrigger",
  "templateVersion": "1.2.4",
  "steps": [...]
}

✅ CORRECT — entity envelope with stringified instance:

{
  "uniqueIdentifier": "<new-guid>",
  "payload": {
    "name": "My Rule Name",
    "parentObject": { "targetUniqueIdentifier": "<object-guid>" },
      "parentContainer": { "targetUniqueIdentifier": "<container-guid>" },
      "definition": {
        "type": "Rule",
        "instance": "{\"templateId\":\"AttributeTrigger\",\"templateVersion\":\"1.2.4\",\"steps\":[...]}",
        "settings": { "shouldRun": true, "shouldApplyRuleOnUpdate": false }
      }
    },
    "type": "timeSeriesView-v1"
}

Use json.dumps() to stringify. Do NOT use PowerShell's ConvertTo-Json.

Two Rule Template Types

EventTrigger does NOT have ScalarSelectStep/ScalarDetectStep. Use when acting on events directly. Supports state, change, and heartbeat detection via EventDetectStep.

Must / Prefer / Avoid

MUST DO

• Always use --resource https://api.fabric.microsoft.com with az rest — without it, token audience is wrong
• Always send --body '{}' for getDefinition — it is a POST and omitting the body can cause 411 errors
• Always Base64-encode ReflexEntities.json payload when calling updateDefinition
• Always JSON.stringify the definition.instance field in timeSeriesView-v1 entities — it must be a string, not a nested object. Always wrap rule templates in the full entity envelope (see the ❌/✅ example above) — never output a raw template object without the entity wrapper
• Always use the correct template type — AttributeTrigger for value-based conditions (has ScalarSelectStep + ScalarDetectStep), EventTrigger for event-based firing (has FieldsDefaultsStep + EventDetectStep, no ScalarDetectStep)
• Always use new GUIDs for uniqueIdentifier when adding entities — duplicate GUIDs cause corruption
• Always update all cross-references when changing a uniqueIdentifier — other entities reference it via targetUniqueIdentifier
• Handle LRO responses — create, getDefinition, and updateDefinition may return 202; poll the Location header

PREFER

• Read-modify-write over full replacement — get the current definition, modify the entity array, and update
• Soft delete over hard delete unless permanent removal is intended
• Discover IDs dynamically via workspace listing + JMESPath rather than hardcoding GUIDs
• Transition-based alert conditions over steady-state conditions for most alerts — prefer detectors such as NumberBecomes, NumberEntersOrLeavesRange, LogicalBecomes, or explicit change conditions even when the user says casual state-like wording such as "is greater than", "is below", or "is outside the range". Treat ordinary alert wording as "notify me when it crosses into that state" to avoid repeated notifications while the condition remains true
• Steady-state conditions such as IsGreaterThan, IsLessThan, or IsOutsideRange only when the user explicitly asks for repeated firing while the value stays in the triggered state, for example "notify me every time it is greater than 30", "fire on every evaluation while it is above 30", or when a downstream occurrence / windowing pattern truly depends on that semantics

AVOID

• Hardcoded workspace or item IDs — always resolve dynamically
• Forgetting the .platform part — only include it with updateDefinition when using ?updateMetadata=true
• SELECT * without filtering on list endpoints — use pagination for large workspaces
• Modifying definitions of items with encrypted sensitivity labels — getDefinition is blocked
• Pre-filtering conditions in the KQL query — return all data from KQL and let the Activator rule steps handle thresholds, text conditions, and dimensional filters. KQL is the data source, not the rule engine
• Inline JSON in PowerShell az rest --body — PowerShell mangles quotes and special characters. Always write JSON to a temp file with [System.IO.File]::WriteAllText($path, $json, [System.Text.UTF8Encoding]::new($false)) and pass --body @$path
• Reusing display names after deletion — soft-deleted items hold their name for several minutes. Use a unique name or hard-delete first

Examples

Follow the Assembly Procedure to build definitions. See reference docs for complete entity schemas: source-types.md, rule-conditions.md, action-types.md.

Agent Integration Notes

• This skill uses the Fabric Items API (/reflexes) for CRUD and the Definition API for rule management
• No additional data-plane protocols are needed — all operations use az rest with the Fabric API audience
• For reading Activator items and rules without modifying them, use the activator-consumption-cli skill instead