
eventhouse-authoring-cli
Execute KQL management commands (table management, ingestion, policies, functions, materialized views) against Fabric Eventhouse and KQL Databases via CLI. Use when the user wants to: 1. Create or alter KQL tables, columns, or functions 2. Ingest data into an Eventhouse (inline, from storage, streaming) 3. Configure retention, caching, or partitioning policies 4. Create or manage materialized views and update policies 5. Manage data mappings for ingestion pipelines 6. Deploy KQL schema via scripts Triggers: "create kql table", "kql ingestion", "ingest into eventhouse", "kql function", "materialized view", "kql retention policy", "eventhouse schema", "kql authoring", "create eventhouse table", "kql mapping"
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/microsoft/skills-for-fabric --skill eventhouse-authoring-cli- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads eventhouse-authoring-cli automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
eventhouse-authoring-cli — Eventhouse Authoring and Management via CLI
Table of Contents
| Task | Reference | Notes |
|---|---|---|
| Finding Workspaces and Items in Fabric | COMMON-CLI.md § Finding Workspaces and Items in Fabric | Mandatory — READ link first [needed for workspace/item ID resolution] |
| Fabric Topology & Key Concepts | COMMON-CORE.md § Fabric Topology & Key Concepts | Hierarchy, Finding Things in Fabric |
| Environment URLs | COMMON-CORE.md § Environment URLs | KQL Cluster URI, KQL Ingestion URI |
| Authentication & Token Acquisition | COMMON-CORE.md § Authentication & Token Acquisition | Wrong audience = 401; KQL audience: kusto.kusto.windows.net |
| Core Control-Plane REST APIs | COMMON-CORE.md § Core Control-Plane REST APIs | List Workspaces, List Items, Item Creation |
| Pagination | COMMON-CORE.md § Pagination | |
| Long-Running Operations (LRO) | COMMON-CORE.md § Long-Running Operations (LRO) | |
| Rate Limiting & Throttling | COMMON-CORE.md § Rate Limiting & Throttling | |
| OneLake Data Access | COMMON-CORE.md § OneLake Data Access | Requires storage.azure.com token, not Fabric token |
| Job Execution | COMMON-CORE.md § Job Execution | |
| Capacity Management | COMMON-CORE.md § Capacity Management | |
| Gotchas & Troubleshooting | COMMON-CORE.md § Gotchas & Troubleshooting | |
| Best Practices | COMMON-CORE.md § Best Practices | |
| 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 https://api.fabric.microsoft.com or az rest fails |
| Pagination Pattern | COMMON-CLI.md § Pagination Pattern | |
| Long-Running Operations (LRO) Pattern | COMMON-CLI.md § Long-Running Operations (LRO) Pattern | |
OneLake Data Access via curl | COMMON-CLI.md § OneLake Data Access via curl | Use curl not az rest (different token audience) |
| SQL / TDS Data-Plane Access | COMMON-CLI.md § SQL / TDS Data-Plane Access | sqlcmd (Go) — not for KQL, but useful for cross-workload |
| Job Execution (CLI) | COMMON-CLI.md § Job Execution | |
| OneLake Shortcuts | COMMON-CLI.md § OneLake Shortcuts | |
| Capacity Management (CLI) | COMMON-CLI.md § Capacity Management | |
| Composite Recipes | COMMON-CLI.md § Composite Recipes | |
| Gotchas & Troubleshooting (CLI-Specific) | COMMON-CLI.md § Gotchas & Troubleshooting (CLI-Specific) | az rest audience, shell escaping, token expiry |
Quick Reference: az rest Template | COMMON-CLI.md § Quick Reference: az rest Template | |
| Quick Reference: Token Audience / CLI Tool Matrix | COMMON-CLI.md § Quick Reference: Token Audience ↔ CLI Tool Matrix | Which --resource + tool for each service |
| Authoring Capability Matrix | EVENTHOUSE-AUTHORING-CORE.md § Authoring Capability Matrix | Read first — KQL Database vs Shortcut (read-only); connection requires Admin/Ingestor role |
| Table Management and Schema Evolution | EVENTHOUSE-AUTHORING-CORE.md § Table Management and Schema Evolution | Create Table, Create-Merge (idempotent), Alter / Rename / Drop, Schema Evolution (Rename, Swap/Blue-Green) |
| Ingestion and Data Mappings | EVENTHOUSE-AUTHORING-CORE.md § Ingestion and Data Mappings | Inline, Set-or-Append/Replace, From Storage, Streaming, Data Mappings (CSV, JSON) |
| Policies | EVENTHOUSE-AUTHORING-CORE.md § Policies | Retention, Caching, Partitioning, Merge |
| Materialized Views | EVENTHOUSE-AUTHORING-CORE.md § Materialized Views | Create, Alter, Lifecycle, Supported aggregations |
| Stored Functions and Update Policies | EVENTHOUSE-AUTHORING-CORE.md § Stored Functions and Update Policies | Stored Functions, Update Policies (auto-transform on ingestion) |
| External Tables | EVENTHOUSE-AUTHORING-CORE.md § External Tables | OneLake / ADLS External Table, Query External Table |
| Permission Model | EVENTHOUSE-AUTHORING-CORE.md § Permission Model | Database Roles, Grant Permissions |
| Authoring Gotchas and Troubleshooting | EVENTHOUSE-AUTHORING-CORE.md § Authoring Gotchas and Troubleshooting Reference | 10 numbered issues with cause + fix |
| Bash Templates | authoring-script-templates.md § Bash Templates | Create Table + Ingest, Schema Deployment, Export Schema, Set Retention/Caching |
| PowerShell Templates | authoring-script-templates.md § PowerShell Templates | Create Table + Ingest, Schema Deployment |
| Tool Stack | SKILL.md § Tool Stack | |
| Connection | SKILL.md § Connection | |
| Authoring Scope | SKILL.md § Authoring Scope | |
| Execute KQL Command | SKILL.md § Execute KQL Command | az rest pattern — write JSON body, then execute |
| Table Management via CLI | SKILL.md § Table Management via CLI | Create Table, Add Column, Drop Table |
| Data Ingestion via CLI | SKILL.md § Data Ingestion via CLI | Inline, From Storage, From OneLake, Set-or-Append |
| Policies via CLI | SKILL.md § Policies via CLI | Retention, Caching, Streaming Ingestion |
| Materialized Views via CLI | SKILL.md § Materialized Views via CLI | |
| Functions and Update Policies via CLI | SKILL.md § Functions and Update Policies via CLI | Create Function, Create Update Policy |
| Schema Evolution via CLI | SKILL.md § Schema Evolution via CLI | Safe Schema Deployment Script, Export Current Schema |
| Monitoring Authoring Operations | SKILL.md § Monitoring Authoring Operations | |
| Must / Prefer / Avoid / Troubleshooting | SKILL.md § Must / Prefer / Avoid / Troubleshooting | MUST DO / AVOID / PREFER checklists |
| Agentic Workflows | SKILL.md § Agentic Workflows | Exploration Before Authoring, Script Generation Workflow |
| Examples | SKILL.md § Examples | |
| Agent Integration Notes | SKILL.md § Agent Integration Notes |
Tool Stack
| Tool | Purpose | Install |
|---|---|---|
| az cli | KQL management commands via Kusto REST API; Fabric control-plane discovery | winget install Microsoft.AzureCLI |
| jq | JSON processing and output formatting | winget install jqlang.jq |
Connection
Same as eventhouse-consumption-cli. Authoring requires elevated roles:
# Discover KQL Database query URI
WS_ID="<workspace-id>"
az rest --method GET \
--url "https://api.fabric.microsoft.com/v1/workspaces/${WS_ID}/kqlDatabases" \
--resource "https://api.fabric.microsoft.com" \
| jq '.value[] | {name: .displayName, queryUri: .properties.queryServiceUri}'
# Set connection variables
CLUSTER_URI="https://<cluster>.kusto.fabric.microsoft.com"
DB_NAME="MyDatabase"
# Verify admin access
cat > /tmp/kql_body.json << EOF
{"db":"${DB_NAME}","csl":".show database ${DB_NAME} principals | where Role == 'Admin'"}
EOF
az rest --method POST \
--url "${CLUSTER_URI}/v1/rest/mgmt" \
--resource "https://kusto.kusto.windows.net" \
--headers "Content-Type=application/json" \
--body @/tmp/kql_body.json \
| jq '.Tables[0].Rows'
Authoring Scope
| Operation | Command Pattern |
|---|---|
| Create table | .create-merge table T (cols) |
| Add column | .alter-merge table T (NewCol: type) |
| Drop table | .drop table T ifexists |
| Ingest data | .ingest into table T (...) |
| Set retention | .alter table T policy retention ... |
| Set caching | .alter table T policy caching hot = Nd |
| Create function | .create-or-alter function F() { ... } |
| Create materialized view | .create materialized-view MV on table T { ... } |
| Create update policy | .alter table T policy update ... |
| Create data mapping | .create table T ingestion csv mapping ... |
Execute KQL Command
All KQL management commands in this skill follow the same az rest pattern. After setting CLUSTER_URI and DB, write the JSON body to /tmp/kql_body.json and execute:
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":"<KQL management command>"}
EOF
az rest --method POST \
--url "${CLUSTER_URI}/v1/rest/mgmt" \
--resource "https://kusto.kusto.windows.net" \
--headers "Content-Type=application/json" \
--body @/tmp/kql_body.json \
| jq '.Tables[0].Rows'
Nested JSON — For commands whose KQL contains embedded JSON (policies, mappings), use
<< 'EOF'(single-quoted) to prevent shell expansion of backslash-escaped quotes, and replace${DB}with the literal database name.
PowerShell equivalent —
@{db=$Database;csl=$Command} | ConvertTo-Json -Compress | Out-File $env:TEMP\kql_body.json -Encoding utf8NoBOMthen--body "@$env:TEMP\kql_body.json". See PowerShell Templates.
Table Management via CLI
Create Table (Idempotent)
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".create-merge table Events (Timestamp: datetime, EventType: string, UserId: string, Properties: dynamic, Duration: real)"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Add Column
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".alter-merge table Events (Region: string)"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Drop Table
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".drop table Events ifexists"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Data Ingestion via CLI
Inline Ingestion (Testing)
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".ingest inline into table Events <| 2025-01-15T10:00:00Z,Login,user1,{},0.5\n2025-01-15T10:01:00Z,Click,user2,{},0.2"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Ingest from Storage
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".ingest into table Events (h'https://mystorage.blob.core.windows.net/data/events.csv.gz;impersonate') with (format='csv', ingestionMappingReference='EventsCsvMapping', ignoreFirstRecord=true)"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Ingest from OneLake
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".ingest into table Events (h'abfss://workspace@onelake.dfs.fabric.microsoft.com/lakehouse.Lakehouse/Files/events.parquet;impersonate') with (format='parquet')"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Set-or-Append from Query
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".set-or-append CleanEvents <| RawEvents | where IsValid == true | project Timestamp, EventType, UserId"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Policies via CLI
Retention
# Set 365-day retention
cat > /tmp/kql_body.json << 'EOF'
{"db":"MyDB","csl":".alter table Events policy retention '{\"SoftDeletePeriod\":\"365.00:00:00\",\"Recoverability\":\"Enabled\"}'"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Caching (Hot Cache)
# Keep last 30 days in hot cache
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".alter table Events policy caching hot = 30d"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Streaming Ingestion
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".alter table Events policy streamingingestion enable"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Materialized Views via CLI
# Create materialized view with backfill
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".create materialized-view with (backfill=true) HourlyEventCounts on table Events { Events | summarize Count = count(), LastSeen = max(Timestamp) by EventType, bin(Timestamp, 1h) }"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
# Check health
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".show materialized-view HourlyEventCounts statistics"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Functions and Update Policies via CLI
Create Function
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".create-or-alter function with (docstring='Parse raw events', folder='ETL') ParseRawEvents() { RawEvents | extend Parsed = parse_json(RawData) | project Timestamp = todatetime(Parsed.timestamp), EventType = tostring(Parsed.eventType), UserId = tostring(Parsed.userId) }"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Create Update Policy
cat > /tmp/kql_body.json << 'EOF'
{"db":"MyDB","csl":".alter table ParsedEvents policy update @'[{\"IsEnabled\":true,\"Source\":\"RawEvents\",\"Query\":\"ParseRawEvents()\",\"IsTransactional\":true}]'"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Schema Evolution via CLI
Safe Schema Deployment Script
Save management commands in a .kql file (one per line), then execute each command via az rest:
# deploy_schema.kql contains one command per line:
# .create-merge table Events (Timestamp: datetime, EventType: string, UserId: string, Properties: dynamic)
# .create-merge table ParsedEvents (Timestamp: datetime, EventType: string, UserId: string, PageName: string)
# .alter table Events policy retention '{\"SoftDeletePeriod\":\"365.00:00:00\",\"Recoverability\":\"Enabled\"}'
# .alter table Events policy caching hot = 30d
# Execute each command from the file (see "Execute KQL Command" section)
while IFS= read -r cmd; do
[[ "$cmd" =~ ^// ]] && continue # skip comment lines
[[ -z "$cmd" ]] && continue # skip blank lines
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":"${cmd}"}
EOF
az rest --method POST \
--url "${CLUSTER_URI}/v1/rest/mgmt" \
--resource "https://kusto.kusto.windows.net" \
--headers "Content-Type=application/json" \
--body @/tmp/kql_body.json \
| jq '.Tables[0].Rows'
done < deploy_schema.kql
Export Current Schema
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".show database ${DB} schema as csl script"}
EOF
az rest --method POST \
--url "${CLUSTER_URI}/v1/rest/mgmt" \
--resource "https://kusto.kusto.windows.net" \
--headers "Content-Type=application/json" \
--body @/tmp/kql_body.json \
| jq -r '.Tables[0].Rows[][0]' > current_schema.kql
Monitoring Authoring Operations
// Recent management commands
.show commands
| where StartedOn > ago(1h)
| project StartedOn, CommandType, Text = substring(Text, 0, 100), State, Duration
| order by StartedOn desc
// Ingestion failures
.show ingestion failures
| where FailedOn > ago(24h)
| summarize FailureCount = count() by ErrorCode, Table
| order by FailureCount desc
// Materialized view health
.show materialized-views
| project Name, IsEnabled, IsHealthy, MaterializedTo
Must / Prefer / Avoid / Troubleshooting
Must
- Clarify before acting on ambiguous prompts — if the request does not specify a target table, operation type, or schema (e.g. "set up my Eventhouse", "configure my database"), ask the user what they want to do. Never infer intent and apply management commands autonomously. Irreversible side-effects (policy changes, schema mutations, data ingestion) require explicit user intent.
- Use idempotent commands —
.create-merge table,.create-or-alter function,.create table ifnotexists. - Verify permissions before authoring — must have
AdminorIngestorrole. - Test update policies by running the function independently before attaching.
- Include
impersonatein storage URIs when ingesting from OneLake or Blob Storage.
Prefer
az restwith loop for deploying multi-command schema files.- Fabric KQL MCP server for agent-integrated ingestion and management workflows.
.create-merge tableover.create tablefor safe schema evolution.- Materialized views over repeated expensive aggregation queries.
- Script-based CI/CD — export schema with
.show database DB schema as csl script, store in git.
Avoid
.drop tablewithoutifexists— fails on missing tables..alter tableto add columns — use.alter-merge tableinstead (additive only).- Ingestion without mappings for CSV/JSON — column order or field names may not match.
- Hardcoded storage URIs — parameterise in scripts.
- Disabling materialized views without understanding the re-backfill cost.
Troubleshooting
| Symptom | Fix |
|---|---|
.create table fails "already exists" | Use .create-merge table or .create table ifnotexists |
| Ingestion succeeds but table empty | Check data mappings: .show table T ingestion csv mappings |
| Update policy not firing | Verify function runs standalone; check .show table T policy update |
Forbidden (403) on management commands | Request admin or ingestor database role |
| Materialized view stuck | Check .show materialized-view MV statistics; may need .disable/.enable |
| OneLake ingest auth error | Add ;impersonate to abfss:// URI |
Agentic Workflows
Exploration Before Authoring
Always check for explicit intent before doing anything:
Step 0 → Is the request specific? Does it name a table, operation, and/or schema?
→ NO → Ask: "What would you like to set up? Options: create tables,
configure policies, set up ingestion mappings, create materialized views."
STOP — do not proceed until user specifies.
→ YES → Continue to Step 1.
Step 1 → .show tables details // what exists?
Step 2 → .show table <TABLE> schema as json // current columns
Step 3 → .show table <TABLE> policy retention // current policies
Step 4 → Plan changes (create-merge, alter, etc.)
Step 5 → Execute changes
Step 6 → Verify: .show table <TABLE> schema as json // confirm changes
Script Generation Workflow
Step 1 → Understand requirements from user
Step 2 → Generate KQL management commands
Step 3 → Save to .kql file
Step 4 → Deploy via az rest (one command at a time)
Step 5 → Verify deployed state matches intent
Examples
Example 1: Create Table with Policies and Mapping
# Create table
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".create-merge table SensorData (Timestamp: datetime, DeviceId: string, Temperature: real, Humidity: real, Location: dynamic)"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
# Set retention
cat > /tmp/kql_body.json << 'EOF'
{"db":"MyDB","csl":".alter table SensorData policy retention '{\"SoftDeletePeriod\":\"90.00:00:00\",\"Recoverability\":\"Enabled\"}'"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
# Set caching
cat > /tmp/kql_body.json << EOF
{"db":"${DB}","csl":".alter table SensorData policy caching hot = 7d"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
# Create JSON mapping
cat > /tmp/kql_body.json << 'EOF'
{"db":"MyDB","csl":".create table SensorData ingestion json mapping 'SensorJsonMapping' '[{\"column\":\"Timestamp\",\"path\":\"$.ts\",\"datatype\":\"datetime\"},{\"column\":\"DeviceId\",\"path\":\"$.deviceId\",\"datatype\":\"string\"},{\"column\":\"Temperature\",\"path\":\"$.temp\",\"datatype\":\"real\"},{\"column\":\"Humidity\",\"path\":\"$.humidity\",\"datatype\":\"real\"},{\"column\":\"Location\",\"path\":\"$.location\",\"datatype\":\"dynamic\"}]'"}
EOF
Execute
/tmp/kql_body.json— see Execute KQL Command
Example 2: ETL with Update Policy
// 1. Target table
.create-merge table ParsedLogs (Timestamp: datetime, Level: string, Message: string, Source: string)
// 2. Transform function
.create-or-alter function ParseRawLogs() {
RawLogs
| extend J = parse_json(RawMessage)
| project
Timestamp = todatetime(J.timestamp),
Level = tostring(J.level),
Message = tostring(J.message),
Source = tostring(J.source)
}
// 3. Attach update policy
.alter table ParsedLogs policy update
@'[{"IsEnabled":true,"Source":"RawLogs","Query":"ParseRawLogs()","IsTransactional":true}]'
Agent Integration Notes
- This skill covers authoring operations — creating/altering database objects and ingesting data.
- For read-only queries and data exploration, delegate to eventhouse-consumption-cli.
- For cross-workload orchestration, delegate to the FabricDataEngineer agent.
- All management commands require elevated database roles (
AdminorIngestor).
FAQ
What does the eventhouse-authoring-cli skill do?
Execute KQL management commands (table management, ingestion, policies, functions, materialized views) against Fabric Eventhouse and KQL Databases via CLI. Use when the user wants to: 1. Create or alter KQL tables, columns, or functions 2. Ingest data into an Eventhouse (inline, from storage, streaming) 3. Configure retention, caching, or partitioning policies 4. Create or manage materialized views and update policies 5. Manage data mappings for ingestion pipelines 6. Deploy KQL schema via scripts Triggers: "create kql table", "kql ingestion", "ingest into eventhouse", "kql function", "materialized view", "kql retention policy", "eventhouse schema", "kql authoring", "create eventhouse table", "kql mapping"
How do I install eventhouse-authoring-cli?
Run npx skills add https://github.com/microsoft/skills-for-fabric --skill eventhouse-authoring-cli in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/eventhouse-authoring-cli/ (personal) or .claude/skills/eventhouse-authoring-cli/ (project).
Which AI agents can use eventhouse-authoring-cli?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is eventhouse-authoring-cli safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains eventhouse-authoring-cli?
It is published by microsoft in microsoft/skills-for-fabric, and it is an official skill from the maker of the technology it covers. It has 124 recorded installs.
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azure-deploy
microsoft/azure-skills
Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.
azure-validate
microsoft/azure-skills
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.