skills/eventstream-authoring-cli/SKILL.md
Create, wire, and publish Fabric Eventstream real-time streaming topologies via the Items REST API. Build definitions with 25 source types (Event Hubs, IoT Hub, CDC, Kafka, SampleData), 8 operators (Filter, Aggregate, GroupBy, Join, ManageFields, Union, Expand, SQL), 4 destinations (Lakehouse, Eventhouse, Activator, Custom Endpoint), DefaultStream/DerivedStream routing. **Invoke this skill** to: (1) author Eventstream topology, (2) add Event Hub source, (3) add filter operator, (4) add CDC source with Debezium flattening, (5) wire destinations, (6) modify/delete Eventstream definitions. Invoke before making topology changes. Triggers: "create eventstream", "deploy eventstream", "eventstream topology", "add source to eventstream", "add event hub source", "add filter operator", "eventstream filter", "eventstream destination", "CDC source", "eventstream operator", "eventstream definition", "update eventstream", "wire eventstream", "real-time ingestion pipeline", "eventstream topology deployment".
npx skillsauth add microsoft/skills-for-fabric eventstream-authoring-cliInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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-updatesskill.- Claude Code / Cowork / Cursor / Windsurf / Codex: compare local vs remote package.json version.
- Skip if the check was already performed earlier in this session.
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
- Eventstream ≠ Eventhouse. Eventstream is a real-time event ingestion and routing pipeline. For KQL database operations, use
eventhouse-authoring-clioreventhouse-consumption-cli.
| Task | Reference | Notes |
|---|---|---|
| Finding Workspaces and Items in Fabric | COMMON-CLI.md § Finding Workspaces and Items in Fabric | Mandatory — READ link first [needed for finding workspace id by its name or item id by its name, item type, and workspace id] |
| Fabric Topology & Key Concepts | COMMON-CORE.md § Fabric Topology & Key Concepts | |
| Environment URLs | COMMON-CORE.md § Environment URLs | |
| Authentication & Token Acquisition | COMMON-CORE.md § Authentication & Token Acquisition | Wrong audience = 401; read before any auth issue |
| Core Control-Plane REST APIs | COMMON-CORE.md § Core Control-Plane REST APIs | Includes pagination, LRO polling, and rate-limiting patterns |
| Gotchas, Best Practices & Troubleshooting | COMMON-CORE.md § Gotchas, Best Practices & Troubleshooting | |
| Tool Selection Rationale | COMMON-CLI.md § Tool Selection Rationale | |
| Authentication Recipes | COMMON-CLI.md § Authentication Recipes | az login flows and token acquisition |
| Fabric Control-Plane API via az rest | COMMON-CLI.md § Fabric Control-Plane API via az rest | Always pass --resource; includes pagination and LRO helpers |
| Gotchas & Troubleshooting (CLI-Specific) | COMMON-CLI.md § Gotchas & Troubleshooting (CLI-Specific) | az rest audience, shell escaping, token expiry |
| Quick Reference | COMMON-CLI.md § Quick Reference | az rest template + token audience/tool matrix |
| Eventstream Resource Model | EVENTSTREAM-AUTHORING-CORE.md § Eventstream Resource Model | Read first — graph-based topology with sources, operators, streams, destinations |
| Source Configuration | EVENTSTREAM-AUTHORING-CORE.md § Source Configuration | 25 API-supported source types with per-source properties |
| Transformation Operators | EVENTSTREAM-AUTHORING-CORE.md § Transformation Operators | 8 operator types: Filter, Aggregate, GroupBy, Join, ManageFields, Union, Expand, SQL |
| Destination Configuration | EVENTSTREAM-AUTHORING-CORE.md § Destination Configuration | 4 API-supported destination types with node schema |
| Stream Types | EVENTSTREAM-AUTHORING-CORE.md § Stream Types | DefaultStream (auto) and DerivedStream (from operators) |
| Eventstream Lifecycle (REST API) | EVENTSTREAM-AUTHORING-CORE.md § Eventstream Lifecycle (REST API) | CRUD + Definition endpoints |
| Item Definitions and Deployment | EVENTSTREAM-AUTHORING-CORE.md § Item Definitions and Deployment | Base64 encoding pattern for eventstream.json |
| Gotchas and Limitations | EVENTSTREAM-AUTHORING-CORE.md § Gotchas and Limitations | Max 11 custom endpoints, base64 encoding, naming constraints |
| Create an Eventstream | SKILL.md § Create an Eventstream | |
| Deploy Full Topology | SKILL.md § Deploy Full Topology | End-to-end: build topology JSON → base64 encode → submit definition |
| Update Eventstream Topology | SKILL.md § Update Eventstream Topology | |
| Delete an Eventstream | SKILL.md § Delete an Eventstream | |
| Gotchas, Rules, Troubleshooting | SKILL.md § Gotchas, Rules, Troubleshooting | MUST DO / AVOID / PREFER checklists |
Create an empty Eventstream item, then configure it with sources, destinations, and operators via the definition API.
az rest --method POST \
--url "https://api.fabric.microsoft.com/v1/workspaces/${WORKSPACE_ID}/eventstreams" \
--resource "https://api.fabric.microsoft.com" \
--headers "Content-Type=application/json" \
--body '{"displayName": "my-eventstream", "description": "IoT sensor pipeline"}'
Save the returned id as EVENTSTREAM_ID.
Construct the eventstream.json topology with sources, streams, operators, and destinations. Each node references its upstream via inputNodes.
Prefer building the JSON programmatically to avoid serialization errors. Key rules:
inputNodesinputNodes[].nameinputSerialization in propertiesBase64-encode the topology JSON and submit via the definition API. See Item Definitions and Deployment for the full payload structure.
For deploying a complete Eventstream with topology in a single API call, use the Create Item with Definition endpoint:
# 1. Build eventstream.json content (topology)
TOPOLOGY_JSON='{"compatibilityLevel":"1.1","sources":[...],"streams":[...],"operators":[...],"destinations":[...]}'
# 2. Build eventstreamProperties.json (optional — controls retention and throughput)
PROPERTIES_JSON='{"retentionTimeInDays":1,"eventThroughputLevel":"Low"}'
# 3. Base64-encode both (no line wraps)
TOPOLOGY_B64=$(echo -n "$TOPOLOGY_JSON" | base64 -w 0)
PROPERTIES_B64=$(echo -n "$PROPERTIES_JSON" | base64 -w 0)
# 4. Submit via Items API
az rest --method POST \
--url "https://api.fabric.microsoft.com/v1/workspaces/${WORKSPACE_ID}/items" \
--resource "https://api.fabric.microsoft.com" \
--headers "Content-Type=application/json" \
--body "{
\"displayName\": \"my-eventstream\",
\"type\": \"Eventstream\",
\"definition\": {
\"parts\": [
{
\"path\": \"eventstream.json\",
\"payload\": \"${TOPOLOGY_B64}\",
\"payloadType\": \"InlineBase64\"
},
{
\"path\": \"eventstreamProperties.json\",
\"payload\": \"${PROPERTIES_B64}\",
\"payloadType\": \"InlineBase64\"
}
]
}
}"
Note: If
eventstreamProperties.jsonis omitted, the API applies defaults:retentionTimeInDays: 1,eventThroughputLevel: "Low". Include it explicitly to control retention (1–90 days) and throughput.
On Windows (PowerShell), use
[Convert]::ToBase64String([Text.Encoding]::UTF8.GetBytes($json))for base64 encoding.
POST /v1/workspaces/{wsId}/eventstreams/{esId}/getDefinitioneventstream.json payload from base64POST /v1/workspaces/{wsId}/eventstreams/{esId}/updateDefinitionAPI Note: The Eventstream Definition APIs use
POSTwith action verbs (getDefinition,updateDefinition), notGET/PUTon a/definitionresource. This follows the Fabric Items Definition pattern. See official docs.
The Update Definition API returns 202 Accepted for long-running operations. Poll the Location header URL until completion.
⚠️ CRITICAL: Filter operator conditions use nested objects for
columnandvalue— NOT bare strings. Using"column": "temperature"instead of the object form below will cause a silent API rejection.
{
"name": "FilterHighTemp",
"type": "Filter",
"inputNodes": [{"name": "my-stream"}],
"properties": {
"conditions": [{
"column": {
"node": null,
"columnName": "temperature",
"columnPath": null,
"expressionType": "ColumnReference"
},
"operatorType": "GreaterThan",
"value": {
"dataType": "Float",
"value": "30.0",
"expressionType": "Literal"
}
}]
}
}
Required structure for ALL operator condition fields:
column → object with {node, columnName, columnPath, expressionType: "ColumnReference"}value → object with {dataType, value, expressionType: "Literal"}operatorType → string: Equals, NotEquals, GreaterThan, GreaterThanOrEquals, LessThan, LessThanOrEquals, Contains, DoesNotContain, StartsWith, DoesNotStartWith, EndsWith, DoesNotEndWith, IsEmpty, IsNull, IsNotNull, IsNotNullOrEmptydataType → BigInt, Float, Nvarchar(max), DateTime, BitThis same nested-object pattern applies to all operators that reference columns (Filter, Aggregate, GroupBy, Join, ManageFields).
az rest --method DELETE \
--url "https://api.fabric.microsoft.com/v1/workspaces/${WORKSPACE_ID}/eventstreams/${EVENTSTREAM_ID}" \
--resource "https://api.fabric.microsoft.com"
Returns 200 OK on success.
eventstream.json payload before submitting definitions--resource https://api.fabric.microsoft.com with az rest calls"column": {"columnName": "x", "expressionType": "ColumnReference", ...}, never "column": "x" (API rejects bare strings silently)202 Accepted with a Location headerSampleData source type for testing and prototypingretentionTimeInDays explicitly rather than relying on defaultsFilterTemperature not filter-temperature or filter_temperature). Exception: DefaultStream names are auto-generated by the platform as {eventstreamName}-stream and may contain hyphens — do not rename themPlatform note — examples use PowerShell. Always write the JSON body to a temp file via
[IO.File]::WriteAllText()(no BOM) and pass--body "@$file"toaz rest, rather than inline--body "..."whichcmd.execan mangle. Use-CompresswithConvertTo-Jsonto avoid newline issues. The one safe inline exception is--body '{}'for empty bodies.
Prompt: "Create an Eventstream called SensorIngestion in my dev workspace with a sample data source."
# 1. Discover workspace ID
$wsId = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/workspaces" `
--resource "https://api.fabric.microsoft.com" `
--query "value[?displayName=='dev'] | [0].id" -o tsv)
if (-not $wsId) { throw "Workspace 'dev' not found" }
# 2. Create empty Eventstream
$esBody = @{ displayName = "SensorIngestion"; description = "IoT sensor pipeline" } | ConvertTo-Json -Compress
$bodyFile = Join-Path ([IO.Path]::GetTempPath()) "es_create.json"
[IO.File]::WriteAllText($bodyFile, $esBody, [System.Text.UTF8Encoding]::new($false))
$created = az rest --method post `
--url "https://api.fabric.microsoft.com/v1/workspaces/$wsId/eventstreams" `
--resource "https://api.fabric.microsoft.com" `
--headers "Content-Type=application/json" `
--body "@$bodyFile" | ConvertFrom-Json
# 3. Get the created Eventstream ID from response
$esId = $created.id
if (-not $esId) { throw "Eventstream creation did not return an ID" }
# 4. Build topology — DefaultStream uses inputNodes (not parentName)
$topology = @{
compatibilityLevel = "1.0"
sources = @(@{
name = "SampleSource"
type = "SampleData"
properties = @{ type = "Bicycles" }
})
streams = @(@{
name = "SensorIngestion-stream"
type = "DefaultStream"
properties = @{}
inputNodes = @(@{ name = "SampleSource" })
})
operators = @()
destinations = @()
}
$topologyJson = $topology | ConvertTo-Json -Depth 10 -Compress
$topologyB64 = [Convert]::ToBase64String([Text.Encoding]::UTF8.GetBytes($topologyJson))
# 5. Deploy definition
$defBody = @{
definition = @{
parts = @(@{
path = "eventstream.json"
payload = $topologyB64
payloadType = "InlineBase64"
})
}
} | ConvertTo-Json -Depth 5 -Compress
$defFile = Join-Path ([IO.Path]::GetTempPath()) "es_def.json"
[IO.File]::WriteAllText($defFile, $defBody, [System.Text.UTF8Encoding]::new($false))
# Note: updateDefinition returns 202 Accepted (LRO). Poll until completion.
$updateJson = az rest --method post `
--url "https://api.fabric.microsoft.com/v1/workspaces/$wsId/eventstreams/$esId/updateDefinition" `
--resource "https://api.fabric.microsoft.com" `
--headers "Content-Type=application/json" `
--body "@$defFile"
if ($LASTEXITCODE -ne 0) { throw "updateDefinition request failed" }
$updateResp = $updateJson | ConvertFrom-Json -ErrorAction SilentlyContinue
if ($updateResp.operationId) {
for ($i = 0; $i -lt 12; $i++) {
Start-Sleep -Seconds 5
$status = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/operations/$($updateResp.operationId)" `
--resource "https://api.fabric.microsoft.com" | ConvertFrom-Json)
if ($status.status -eq 'Succeeded') { Write-Host "Update succeeded"; break }
elseif ($status.status -in @('Failed', 'Cancelled')) {
throw "updateDefinition LRO $($status.status): $($status.error.message)"
}
}
}
Prompt: "Add a filter to my SensorIngestion Eventstream that keeps only events where No_Bikes > 5 and expose the filtered output as a DerivedStream."
Important: Adding a Filter operator node alone does not redirect the DefaultStream. To make the filtered output consumable, wire a DerivedStream (or destination) to the filter's output via
inputNodes.
# 1. Discover workspace + Eventstream IDs
$wsId = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/workspaces" `
--resource "https://api.fabric.microsoft.com" `
--query "value[?displayName=='dev'] | [0].id" -o tsv)
if (-not $wsId) { throw "Workspace 'dev' not found" }
$esId = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/workspaces/$wsId/eventstreams" `
--resource "https://api.fabric.microsoft.com" `
--query "value[?displayName=='SensorIngestion'] | [0].id" -o tsv)
if (-not $esId) { throw "Eventstream 'SensorIngestion' not found" }
# 2. Get current definition (handles LRO if API returns 202)
$respJson = az rest --method post `
--url "https://api.fabric.microsoft.com/v1/workspaces/$wsId/eventstreams/$esId/getDefinition" `
--resource "https://api.fabric.microsoft.com" `
--headers "Content-Type=application/json" `
--body '{}'
if ($LASTEXITCODE -ne 0 -or -not $respJson) { throw "getDefinition request failed" }
$resp = $respJson | ConvertFrom-Json
if ($resp.definition) {
$def = $resp # Synchronous — got definition immediately
} elseif ($resp.operationId) {
# Asynchronous (LRO) — poll operation status
$def = $null
for ($i = 0; $i -lt 12; $i++) {
Start-Sleep -Seconds 5
$status = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/operations/$($resp.operationId)" `
--resource "https://api.fabric.microsoft.com" | ConvertFrom-Json)
if ($status.status -eq 'Succeeded') {
$def = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/operations/$($resp.operationId)/result" `
--resource "https://api.fabric.microsoft.com" | ConvertFrom-Json)
break
} elseif ($status.status -in @('Failed', 'Cancelled')) {
throw "getDefinition LRO $($status.status): $($status.error.message)"
}
}
if (-not $def.definition) { throw "getDefinition LRO timed out (last status: $($status.status))" }
} else {
throw "getDefinition returned neither a definition nor an operationId"
}
# 3. Decode existing topology
$esPart = $def.definition.parts | Where-Object { $_.path -eq 'eventstream.json' } | Select-Object -First 1
if (-not $esPart) { throw "eventstream.json part not found in definition" }
$topology = [Text.Encoding]::UTF8.GetString(
[Convert]::FromBase64String($esPart.payload)) | ConvertFrom-Json
# 4. Add Filter operator (PascalCase name — no underscores or hyphens)
# Column: expressionType + columnName; Value: expressionType + dataType + value
$filter = @{
name = "FilterLowBikes"
type = "Filter"
inputNodes = @(@{ name = "SensorIngestion-stream" })
properties = @{
conditions = @(@{
operatorType = "GreaterThan"
column = @{
expressionType = "ColumnReference"
node = $null
columnName = "No_Bikes"
columnPath = $null
}
value = @{
expressionType = "Literal"
dataType = "BigInt"
value = "5"
}
})
}
}
$existingOps = @($topology.operators | Where-Object { $_ -ne $null })
$topology.operators = $existingOps + @($filter)
# 5. Add DerivedStream wired to filter output (makes filtered data available)
$derivedStream = @{
name = "FilteredOutput"
type = "DerivedStream"
properties = @{
inputSerialization = @{ type = "Json"; properties = @{ encoding = "UTF8" } }
}
inputNodes = @(@{ name = "FilterLowBikes" })
}
$existingStreams = @($topology.streams | Where-Object { $_ -ne $null })
$topology.streams = $existingStreams + @($derivedStream)
# 6. Re-encode and update
$topologyJson = $topology | ConvertTo-Json -Depth 10 -Compress
$topologyB64 = [Convert]::ToBase64String([Text.Encoding]::UTF8.GetBytes($topologyJson))
$esPart.payload = $topologyB64
$defBody = @{ definition = @{ parts = $def.definition.parts } } | ConvertTo-Json -Depth 5 -Compress
$defFile = Join-Path ([IO.Path]::GetTempPath()) "es_def.json"
[IO.File]::WriteAllText($defFile, $defBody, [System.Text.UTF8Encoding]::new($false))
# Note: updateDefinition returns 202 Accepted (LRO). Poll until completion.
$updateJson = az rest --method post `
--url "https://api.fabric.microsoft.com/v1/workspaces/$wsId/eventstreams/$esId/updateDefinition" `
--resource "https://api.fabric.microsoft.com" `
--headers "Content-Type=application/json" `
--body "@$defFile"
if ($LASTEXITCODE -ne 0) { throw "updateDefinition request failed" }
$updateResp = $updateJson | ConvertFrom-Json -ErrorAction SilentlyContinue
if ($updateResp.operationId) {
for ($i = 0; $i -lt 12; $i++) {
Start-Sleep -Seconds 5
$status = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/operations/$($updateResp.operationId)" `
--resource "https://api.fabric.microsoft.com" | ConvertFrom-Json)
if ($status.status -eq 'Succeeded') { Write-Host "Update succeeded"; break }
elseif ($status.status -in @('Failed', 'Cancelled')) {
throw "updateDefinition LRO $($status.status): $($status.error.message)"
}
}
}
Prompt: "Create a complete Eventstream called EventPipeline with a Custom Endpoint source, a filter for high-value events, and a DerivedStream for the filtered output."
Note: This uses the Fabric Items API (
POST /items) to create the Eventstream with its definition in a single call, rather than create-then-update.
# 1. Discover workspace ID
$wsId = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/workspaces" `
--resource "https://api.fabric.microsoft.com" `
--query "value[?displayName=='dev'] | [0].id" -o tsv)
if (-not $wsId) { throw "Workspace 'dev' not found" }
# 2. Build complete topology with filter + DerivedStream
$topology = @{
compatibilityLevel = "1.0"
sources = @(@{
name = "CustomSource"
type = "CustomEndpoint"
properties = @{}
})
streams = @(
@{
name = "EventPipeline-stream"
type = "DefaultStream"
properties = @{}
inputNodes = @(@{ name = "CustomSource" })
}
@{
name = "FilteredEvents"
type = "DerivedStream"
properties = @{
inputSerialization = @{ type = "Json"; properties = @{ encoding = "UTF8" } }
}
inputNodes = @(@{ name = "FilterPremium" })
}
)
operators = @(@{
name = "FilterPremium"
type = "Filter"
inputNodes = @(@{ name = "EventPipeline-stream" })
properties = @{
conditions = @(@{
operatorType = "GreaterThan"
column = @{
expressionType = "ColumnReference"
node = $null
columnName = "Amount"
columnPath = $null
}
value = @{
expressionType = "Literal"
dataType = "BigInt"
value = "100"
}
})
}
})
destinations = @()
}
# 3. Create with inline definition (single API call)
$topologyJson = $topology | ConvertTo-Json -Depth 10 -Compress
$topologyB64 = [Convert]::ToBase64String([Text.Encoding]::UTF8.GetBytes($topologyJson))
$body = @{
displayName = "EventPipeline"
type = "Eventstream"
definition = @{
parts = @(@{
path = "eventstream.json"
payload = $topologyB64
payloadType = "InlineBase64"
})
}
} | ConvertTo-Json -Depth 5 -Compress
$bodyFile = Join-Path ([IO.Path]::GetTempPath()) "es_create_full.json"
[IO.File]::WriteAllText($bodyFile, $body, [System.Text.UTF8Encoding]::new($false))
# Create-with-definition returns 202 Accepted (LRO). Poll until completion.
$createJson = az rest --method post `
--url "https://api.fabric.microsoft.com/v1/workspaces/$wsId/items" `
--resource "https://api.fabric.microsoft.com" `
--headers "Content-Type=application/json" `
--body "@$bodyFile"
if ($LASTEXITCODE -ne 0) { throw "Create Eventstream request failed" }
$createResp = $createJson | ConvertFrom-Json -ErrorAction SilentlyContinue
if ($createResp.operationId) {
for ($i = 0; $i -lt 12; $i++) {
Start-Sleep -Seconds 5
$status = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/operations/$($createResp.operationId)" `
--resource "https://api.fabric.microsoft.com" | ConvertFrom-Json)
if ($status.status -eq 'Succeeded') { Write-Host "Create succeeded"; break }
elseif ($status.status -in @('Failed', 'Cancelled')) {
throw "Create LRO $($status.status): $($status.error.message)"
}
}
}
Prompt: "Delete the SensorIngestion Eventstream from my dev workspace."
# 1. Discover workspace + Eventstream IDs
$wsId = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/workspaces" `
--resource "https://api.fabric.microsoft.com" `
--query "value[?displayName=='dev'] | [0].id" -o tsv)
if (-not $wsId) { throw "Workspace 'dev' not found" }
$esId = (az rest --method get `
--url "https://api.fabric.microsoft.com/v1/workspaces/$wsId/eventstreams" `
--resource "https://api.fabric.microsoft.com" `
--query "value[?displayName=='SensorIngestion'] | [0].id" -o tsv)
if (-not $esId) { throw "Eventstream 'SensorIngestion' not found" }
# 2. Delete
az rest --method delete `
--url "https://api.fabric.microsoft.com/v1/workspaces/$wsId/eventstreams/$esId" `
--resource "https://api.fabric.microsoft.com"
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Onboard Log Analytics, Application Insights, and Azure Monitor telemetry into Microsoft Fabric as a Mirrored Catalog, then turn it into business-impact insights by correlating telemetry with business data via Eventhouse shortcuts, verified schemas, and ready-to-use Operations Agent instructions. Triggers: onboard Log Analytics telemetry, connect Application Insights to a Mirrored Catalog, correlate App Insights telemetry with business data, build an Operations Agent for business-impact alerting, determine if availability or latency impacted bookings orders or revenue.
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Onboard Log Analytics, Application Insights, and Azure Monitor telemetry into Microsoft Fabric as a Mirrored Catalog, then turn it into business-impact insights by correlating telemetry with business data via Eventhouse shortcuts, verified schemas, and ready-to-use Operations Agent instructions. Triggers: onboard Log Analytics telemetry, connect Application Insights to a Mirrored Catalog, correlate App Insights telemetry with business data, build an Operations Agent for business-impact alerting, determine if availability or latency impacted bookings orders or revenue.
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Manage refresh schedules and job execution for an EXISTING Microsoft Fabric Materialized Lake View (MLV) via REST APIs: create, update, and delete refresh schedules (interval-based: hourly, daily, weekly), trigger on-demand refreshes, monitor job status, and cancel running jobs. Uses human-in-the-loop confirmations for safety. This skill does NOT author or create the MLV definition: writing the CREATE MATERIALIZED LAKE VIEW / CREATE OR REPLACE SQL is `spark-authoring-cli`, not this skill. Note: MLV discovery (list MLVs, lineage, data quality) requires UI as REST APIs are not yet available. Triggers: "schedule MLV refresh", "manage MLV refresh", "MLV refresh schedule", "schedule materialized lake view refresh", "automate MLV refresh", "trigger MLV refresh", "monitor MLV refresh", "MLV job status", "cancel MLV refresh", "refresh schedule", "MLV automation", "refresh my materialized views"