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azure-kusto-irql

Compose IRQL (Incident Response Query Language) queries for Kusto cybersecurity investigations. Translates natural language hunting questions into composable IRQL pipelines using Get_*, Extract_*, and Enrich_* functions. WHEN: IRQL query, security hunt, threat hunting KQL, incide

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Install

skills CLI npx skills add https://github.com/microsoft/skills/tree/main/.github/plugins/azure-kusto-graph-skills/skills/azure-kusto-irql
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install microsoft-skills@llmmart
Git git clone https://github.com/microsoft/skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole microsoft/skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

IRQL -- Incident Response Query Language

Compose IRQL function pipelines from selector, extractor, and enricher building blocks. IRQL wraps raw KQL security tables behind intent-revealing, composable functions so analysts (and LLMs) can express hunts without memorizing schemas, cluster locations, or join keys.

Activation Triggers

Use this skill when the user:

  • Explicitly mentions IRQL, Get_*, Extract_*, or Enrich_* functions
  • Says "use IRQL" or "write an IRQL query"
  • Requests a composable hunting pipeline using known IRQL selectors

Do not activate for generic security queries (e.g. "find failed logins") unless the user explicitly asks for IRQL. Route those to azure-kusto instead.

Not a natural-language-to-IRQL converter. This skill composes IRQL function pipelines and may handle basic natural-language requests that map directly to known selectors and simple filters. For general NL-to-KQL or NL-to-IRQL conversion, use a dedicated query-generation skill (available separately).

IRQL Function Preflight

Before generating a pipeline, verify IRQL is available on the target database:

.show functions
| where Name startswith "Get_" or Name startswith "Extract_" or Name startswith "Enrich_"
| project Name

If no IRQL functions are found, inform the user that IRQL is not deployed on the target database and suggest using azure-kusto for raw KQL queries instead. IRQL functions are a prerequisite -- this skill does not deploy base IRQL selectors.

What IRQL Is

IRQL is a function-based dialect on top of KQL. It provides:

  1. Unified schema -- disparate security tables project into consistent column names regardless of the underlying data source
  2. Composability -- small functions chain via | invoke to build complex hunts from simple steps
  3. Portability -- the same IRQL pipeline works across different clusters/databases; only the Get_* primitives need re-pointing

IRQL is not a separate language. It's KQL functions you invoke. Any valid KQL works alongside IRQL functions.

Deploying IRQL

IRQL functions are stored KQL functions (.create-or-alter function). They must already be deployed to the target database before this skill can generate pipelines.

Public example cluster (functions pre-deployed):

  • Cluster: https://kc7001.eastus.kusto.windows.net
  • Databases: ValdyTimes, JoJosHospital

To port IRQL to a new cluster/database, create Get_* selectors that project your source tables into the unified schema (column names below), then deploy extractors and enrichers. The extractors and enrichers work unchanged as long as the input schema matches.

Function Catalog

1. Selectors -- Get_*

Return projected, schema-unified views of source tables. Use the minimal form by default; use _All when extra columns are needed.

Function Columns
Get_Event_Authentication EnvTime, Hostname, ClientIp, Username, Result
Get_Event_Authentication_All + Description, UserAgent, PasswordHash
Get_Email EnvTime, EmailSender, EmailRecipient, Subject, Url
Get_Email_All + ReplyTo, Verdict
Get_Employees Name, ClientIp, Email, Username, Hostname, Role
Get_Employees_All + HireDate, UserAgent, Domain
Get_Event_FileCreation EnvTime, Hostname, Filename, Path
Get_Event_FileCreation_All + Username, Sha256, ProcessName
Get_Event_NetworkInbound EnvTime, ClientIp, Url
Get_Event_NetworkInbound_All + Method, UserAgent, StatusCode
Get_Event_NetworkOutbound EnvTime, ClientIp, Url
Get_Event_NetworkOutbound_All + Method, UserAgent
Get_Dns_All EnvTime, Domain, ClientIp
Get_Event_Process EnvTime, ProcessCommandLine, ProcessName, Hostname, Username
Get_Event_Process_All + ParentProcessName, ParentProcessHash, ProcessHash
Get_SecurityAlerts_All EnvTime, AlertType, Severity, Description, Indicators
Get_Network_Connection_All EnvTime, SourceIp, SourcePort, DestinationIp, DestinationPort, Protocol, Bytes

2. Extractors -- Extract_*

Derive a new column from an existing one. Invoke after a selector.

Function Input Column Adds
Extract_Email_Sender_Domain(T) EmailSender Domain
Extract_Employee_Firstname(T) Name Firstname
Extract_Event_Network_Domain(T) Url DomainName

3. Enrichers -- Enrich_*

Left-join helpers that attach context from a related table.

Function Key Column Enriches With
Enrich_Event_Authentication_Username(T) Username Auth events for user
Enrich_Ip_Employee(T) ClientIp Employee identity from IP
Enrich_Username_Employee(T) Username Employee identity from username
Enrich_Ip_Domain(T) ClientIp DNS domains resolved to IP
Enrich_Ip_Event_NetworkOutbound(T) ClientIp Outbound network from IP
Enrich_Ip_Network_Connection(T) ClientIp Network flows from IP

4. External Enrichment

Function Source Requirement
Enrich_Sha256_VirusTotal(T) VirusTotal file report API key + callout policy
Get_CISA_KEV() / Enrich_CISA_KEV(T) CISA KEV catalog Callout policy

Composition Rules

Selector -> Extract -> Filter -> Enrich -> Summarize/Project
  1. Start with a Selector: Get_Event_Authentication, Get_Email, etc.
  2. Extract derived fields: | invoke Extract_Email_Sender_Domain()
  3. Filter to the signal: | where Result == "Failed Login"
  4. Enrich with context: | invoke Enrich_Username_Employee()
  5. Summarize / project the answer

Always pipe (|) between steps. Extractors and Enrichers use | invoke FunctionName().

Query Generation Guidelines

  • Use the minimal selector unless extra columns are needed -> then _All
  • Chain extractors before enrichers (extractors add columns enrichers may key on)
  • Place where filters as early as possible
  • Use summarize for aggregations, project for final column selection
  • End with order by + take to limit output

Examples

For additional prompts and worked examples, see references/EXAMPLES.md.

Brute-force detection

Get_Event_Authentication
| where Result == "Failed Login"
| summarize FailedCount = count() by Username
| where FailedCount > 19
| invoke Enrich_Username_Employee()
| project Username, Name, Role, Email, FailedCount
| order by FailedCount desc

Phishing triage by recipient seniority

Get_Email
| invoke Extract_Email_Sender_Domain()
| project EnvTime, EmailSender, Domain, Username = EmailRecipient, Subject, Url
| invoke Enrich_Username_Employee()
| extend Seniority = case(
    Role has_any ("CEO", "Chief", "Director", "VP", "President"), 3,
    Role has_any ("Manager", "Lead", "Senior"), 2,
    1)
| summarize
    TotalEmails = count(),
    SeniorityScore = sum(Seniority),
    Recipients = make_set(Name, 50),
    DistinctRecipients = dcount(Username)
  by Domain
| where DistinctRecipients >= 2
| order by SeniorityScore desc
| take 20

Post-exploitation pivot from an indicator

let victims =
    Get_Event_FileCreation_All
    | where Filename has "<INDICATOR>"
    | distinct Hostname;
Get_Event_Process
| where Hostname in (victims)
| where ProcessCommandLine has_any ("rundll32", "regsvr32", "powershell", "systeminfo")
| project EnvTime, Hostname, Username, ProcessName, ProcessCommandLine
| order by EnvTime asc

Suspicious outbound traffic enriched with identity

Get_Event_NetworkOutbound
| invoke Extract_Event_Network_Domain()
| where DomainName has_any ("<SUSPICIOUS_DOMAIN_1>", "<SUSPICIOUS_DOMAIN_2>")
| invoke Enrich_Ip_Employee()
| project EnvTime, Name, Role, DomainName, Url, ClientIp
| order by EnvTime desc

External IP authentication anomaly

Get_Event_Authentication_All
| where not(ClientIp startswith "10.") and not(ClientIp startswith "192.168.")
| summarize
    Attempts = count(),
    Failures = countif(Result == "Failed Login"),
    Users = make_set(Username)
  by ClientIp
| order by Failures desc
| take 20

MCP Tools Used

Tool Purpose
kusto_query Execute IRQL pipelines against a Kusto database
kusto_table_schema_get Discover available tables and columns
kusto_cluster_list List available ADX clusters
kusto_database_list List databases in a cluster

Opening Queries in Kusto Explorer (Windows Only)

Optional convenience feature. The default workflow is to output the KQL in chat and let the user copy it into Kusto Explorer or the VS Code Kusto extension manually. Auto-launch is opt-in only.

Always output the complete KQL query in the chat response with Step 1 (connect) and Step 2 (query) clearly labeled:

// Step 1: Connect to your cluster (skip if already connected)
// Example: uncomment to connect to the KC7 training cluster
// #connect cluster('kc7001.eastus.kusto.windows.net').database('ValdyTimes')
// Or replace with your own cluster:
// #connect cluster('<YOUR_CLUSTER>').database('<YOUR_DATABASE>')

// Step 2: Run the query below
<KQL_QUERY>

If the user asks to save or open in Kusto Explorer, follow the procedure in references/KUSTO_EXPLORER_LAUNCH.md. Key rules:

  • Use ask_user to confirm before writing files or launching executables
  • Display file contents in chat so the user can review before opening
  • Never use shell interpolation or here-strings — write files via Set-Content/Add-Content
  • Never encode queries into browser URLs
  • On macOS/Linux, save the .kql file and suggest the VS Code Kusto extension or ADX Web Explorer
  • For graph visualization from IRQL data, see azure-kusto-graph and azure-kusto-irql-graph
Files (skills)
  • references
    • EXAMPLES.md 2.2 KB 
      # Try It Out -- azure-kusto-irql

Paste any of these into **Copilot Chat** to see the skill in action.
Cluster: `https://kc7001.eastus.kusto.windows.net`

---

## ValdyTimes (IRQL functions: `Get_*`, `Extract_*`, `Enrich_*`)

| # | Ask This | What It Does |
|---|----------|--------------|
| 1 | "Find all failed logins in ValdyTimes" | Basic `Get_Event_Authentication` with filter |
| 2 | "Which sender domains are emailing executives?" | `Get_Email` -> `Extract_Email_Sender_Domain` -> `Enrich_Username_Employee` |
| 3 | "Show me users with more than 20 failed logins and their job roles" | `Get_Event_Authentication` -> `summarize` -> `Enrich_Username_Employee` |
| 4 | "Find powershell or rundll32 execution on any host" | `Get_Event_Process` with command-line filter |
| 5 | "What domains are being accessed by IPs with failed logins?" | Auth -> distinct IPs -> `Enrich_Ip_Domain` |
| 6 | "Find authentication from external IPs" | `Get_Event_Authentication_All` with RFC1918 exclusion |
| 7 | "A file called Raisin_Kane appeared on some hosts. What processes ran on those hosts?" | `Get_Event_FileCreation_All` -> victim hosts -> `Get_Event_Process` |
| 8 | "Which users are logging in from the most distinct IPs?" | `Get_Event_Authentication_All` -> `summarize dcount(ClientIp) by Username` |

## AzureCrest (raw KQL — no IRQL)

AzureCrest has no IRQL functions. In this environment, route to the `azure-kusto` skill to author raw KQL equivalents (do not use `azure-kusto-irql`).

| # | Ask This | What It Does |
|---|----------|--------------|
| 1 | "Find all failed logins in AzureCrest" | Raw `AuthenticationEvents` with `result` filter |
| 2 | "Which sender domains are emailing executives in AzureCrest?" | `Email` -> extract domain -> join `Employees` |
| 3 | "Show users with more than 20 failed logins and their roles in AzureCrest" | `AuthenticationEvents` -> `summarize` -> join `Employees` |
| 4 | "Find powershell execution across all hosts in AzureCrest" | `ProcessEvents` with `process_commandline` filter |
| 5 | "What domains are accessed by IPs with failed logins in AzureCrest?" | `AuthenticationEvents` -> distinct `src_ip` -> join `PassiveDns` |
| 6 | "Find authentication from external IPs in AzureCrest" | `AuthenticationEvents` with RFC1918 exclusion |
    • KUSTO_EXPLORER_LAUNCH.md 2.6 KB 
      # Kusto Explorer Launch Procedure

## Prerequisites

- Windows only — Kusto Explorer is not available on macOS/Linux
- User must explicitly consent before file creation or launch

## Step 1: Confirm with user

Use `ask_user`: "Save this query as a .kql file and open in Kusto Explorer? (Yes / Save only / No)"

- **No** → output KQL in chat only (default)
- **Save only** → proceed to Step 2, skip Step 4
- **Yes** → proceed through all steps

## Step 2: Build the .kql file content

The file needs two sections because Kusto Explorer processes `#connect` as a connection-creation command that must run before the query.

```
// Step 1 — Select this line and run it first to connect
#connect cluster('<CLUSTER>').database('<DATABASE>')

// Step 2 — Select the query below and run it after Step 1 completes
<KQL_QUERY>
```

Replace `<CLUSTER>` with the target cluster (e.g. `kc7001.eastus.kusto.windows.net`), `<DATABASE>` with the database name (e.g. `ValdyTimes`), and `<KQL_QUERY>` with the generated query.

## Step 3: Write the file

Write to the current workspace directory using the filesystem API. Use a descriptive name with a random suffix to avoid collisions.

```powershell
$cluster = "<CLUSTER>"
$database = "<DATABASE>"
$tmp = Join-Path $PWD "kusto_query_$(New-Guid).kql"
$lines = @(
    "// Step 1 - Select this line and run it first",
    "#connect cluster('$cluster').database('$database')",
    "",
    "// Step 2 - Select the query below and run it after Step 1 completes"
)
Set-Content -Path $tmp -Value ($lines -join "`n") -Encoding utf8 -NoNewline
Add-Content -Path $tmp -Value "`n<KQL_QUERY>" -Encoding utf8
```

> **Security:** Use `Set-Content`/`Add-Content` only. Never embed query text in PowerShell here-strings (`@"..."@`) — a crafted query can escape the delimiter and inject commands.

Display the saved file path and its full contents in chat so the user can review.

## Step 4: Launch Kusto Explorer (only if user chose "Yes")

Locate and launch the Kusto Explorer executable:

```powershell
$exe = (Get-ChildItem "$env:LOCALAPPDATA\Apps\2.0" -Recurse -Filter "Kusto.Explorer.exe" -ErrorAction SilentlyContinue | Sort-Object LastWriteTime -Descending | Select-Object -First 1).FullName
if ($exe) {
    Start-Process $exe -ArgumentList "`"$tmp`""
} else {
    Write-Warning "Kusto Explorer not found. Open the saved file manually: $tmp"
}
```

Tell the user: run the `#connect` line (Step 1) first, then select and run the query (Step 2).

## macOS/Linux fallback

Save the `.kql` file as in Step 3 and suggest:
- Open in the VS Code Kusto extension
- Paste into [ADX Web Explorer](https://dataexplorer.azure.com)
  • SKILL.md 10.2 KB 
    ---
name: azure-kusto-irql
description: "Compose IRQL (Incident Response Query Language) queries for Kusto cybersecurity investigations. Translates natural language hunting questions into composable IRQL pipelines using Get_*, Extract_*, and Enrich_* functions. WHEN: IRQL query, security hunt, threat hunting KQL, incident response query, compose hunting pipeline, failed logins, phishing investigation, lateral movement, process execution, file creation events."
license: MIT
metadata:
  author: Microsoft
  version: "1.2.1"
---

# IRQL -- Incident Response Query Language

Compose IRQL function pipelines from selector, extractor, and enricher building blocks. IRQL wraps raw KQL security tables behind intent-revealing, composable functions so analysts (and LLMs) can express hunts without memorizing schemas, cluster locations, or join keys.

## Activation Triggers

Use this skill when the user:
- Explicitly mentions IRQL, `Get_*`, `Extract_*`, or `Enrich_*` functions
- Says "use IRQL" or "write an IRQL query"
- Requests a composable hunting pipeline using known IRQL selectors

Do **not** activate for generic security queries (e.g. "find failed logins") unless the user explicitly asks for IRQL. Route those to `azure-kusto` instead.

**Not a natural-language-to-IRQL converter.** This skill composes IRQL function pipelines and may handle basic natural-language requests that map directly to known selectors and simple filters. For general NL-to-KQL or NL-to-IRQL conversion, use a dedicated query-generation skill (available separately).

## IRQL Function Preflight

Before generating a pipeline, verify IRQL is available on the target database:

```kql
.show functions
| where Name startswith "Get_" or Name startswith "Extract_" or Name startswith "Enrich_"
| project Name
```

If no IRQL functions are found, inform the user that IRQL is not deployed on the target database and suggest using `azure-kusto` for raw KQL queries instead. IRQL functions are a prerequisite -- this skill does not deploy base IRQL selectors.

## What IRQL Is

IRQL is a **function-based dialect on top of KQL**. It provides:

1. **Unified schema** -- disparate security tables project into consistent column names regardless of the underlying data source
2. **Composability** -- small functions chain via `| invoke` to build complex hunts from simple steps
3. **Portability** -- the same IRQL pipeline works across different clusters/databases; only the `Get_*` primitives need re-pointing

IRQL is not a separate language. It's KQL functions you invoke. Any valid KQL works alongside IRQL functions.

## Deploying IRQL

IRQL functions are stored KQL functions (`.create-or-alter function`). They must already be deployed to the target database before this skill can generate pipelines.

**Public example cluster** (functions pre-deployed):
- Cluster: `https://kc7001.eastus.kusto.windows.net`
- Databases: `ValdyTimes`, `JoJosHospital`

To port IRQL to a new cluster/database, create `Get_*` selectors that project your source tables into the unified schema (column names below), then deploy extractors and enrichers. The extractors and enrichers work unchanged as long as the input schema matches.

## Function Catalog

### 1. Selectors -- `Get_*`

Return projected, schema-unified views of source tables. Use the minimal form by default; use `_All` when extra columns are needed.

| Function | Columns |
|---|---|
| `Get_Event_Authentication` | `EnvTime`, `Hostname`, `ClientIp`, `Username`, `Result` |
| `Get_Event_Authentication_All` | + `Description`, `UserAgent`, `PasswordHash` |
| `Get_Email` | `EnvTime`, `EmailSender`, `EmailRecipient`, `Subject`, `Url` |
| `Get_Email_All` | + `ReplyTo`, `Verdict` |
| `Get_Employees` | `Name`, `ClientIp`, `Email`, `Username`, `Hostname`, `Role` |
| `Get_Employees_All` | + `HireDate`, `UserAgent`, `Domain` |
| `Get_Event_FileCreation` | `EnvTime`, `Hostname`, `Filename`, `Path` |
| `Get_Event_FileCreation_All` | + `Username`, `Sha256`, `ProcessName` |
| `Get_Event_NetworkInbound` | `EnvTime`, `ClientIp`, `Url` |
| `Get_Event_NetworkInbound_All` | + `Method`, `UserAgent`, `StatusCode` |
| `Get_Event_NetworkOutbound` | `EnvTime`, `ClientIp`, `Url` |
| `Get_Event_NetworkOutbound_All` | + `Method`, `UserAgent` |
| `Get_Dns_All` | `EnvTime`, `Domain`, `ClientIp` |
| `Get_Event_Process` | `EnvTime`, `ProcessCommandLine`, `ProcessName`, `Hostname`, `Username` |
| `Get_Event_Process_All` | + `ParentProcessName`, `ParentProcessHash`, `ProcessHash` |
| `Get_SecurityAlerts_All` | `EnvTime`, `AlertType`, `Severity`, `Description`, `Indicators` |
| `Get_Network_Connection_All` | `EnvTime`, `SourceIp`, `SourcePort`, `DestinationIp`, `DestinationPort`, `Protocol`, `Bytes` |

### 2. Extractors -- `Extract_*`

Derive a new column from an existing one. Invoke after a selector.

| Function | Input Column | Adds |
|---|---|---|
| `Extract_Email_Sender_Domain(T)` | `EmailSender` | `Domain` |
| `Extract_Employee_Firstname(T)` | `Name` | `Firstname` |
| `Extract_Event_Network_Domain(T)` | `Url` | `DomainName` |

### 3. Enrichers -- `Enrich_*`

Left-join helpers that attach context from a related table.

| Function | Key Column | Enriches With |
|---|---|---|
| `Enrich_Event_Authentication_Username(T)` | `Username` | Auth events for user |
| `Enrich_Ip_Employee(T)` | `ClientIp` | Employee identity from IP |
| `Enrich_Username_Employee(T)` | `Username` | Employee identity from username |
| `Enrich_Ip_Domain(T)` | `ClientIp` | DNS domains resolved to IP |
| `Enrich_Ip_Event_NetworkOutbound(T)` | `ClientIp` | Outbound network from IP |
| `Enrich_Ip_Network_Connection(T)` | `ClientIp` | Network flows from IP |

### 4. External Enrichment

| Function | Source | Requirement |
|---|---|---|
| `Enrich_Sha256_VirusTotal(T)` | VirusTotal file report | API key + callout policy |
| `Get_CISA_KEV()` / `Enrich_CISA_KEV(T)` | CISA KEV catalog | Callout policy |

## Composition Rules

```
Selector -> Extract -> Filter -> Enrich -> Summarize/Project
```

1. **Start with a Selector**: `Get_Event_Authentication`, `Get_Email`, etc.
2. **Extract** derived fields: `| invoke Extract_Email_Sender_Domain()`
3. **Filter** to the signal: `| where Result == "Failed Login"`
4. **Enrich** with context: `| invoke Enrich_Username_Employee()`
5. **Summarize / project** the answer

Always pipe (`|`) between steps. Extractors and Enrichers use `| invoke FunctionName()`.

## Query Generation Guidelines

- Use the **minimal selector** unless extra columns are needed -> then `_All`
- Chain extractors before enrichers (extractors add columns enrichers may key on)
- Place `where` filters as early as possible
- Use `summarize` for aggregations, `project` for final column selection
- End with `order by` + `take` to limit output

## Examples

For additional prompts and worked examples, see [references/EXAMPLES.md](references/EXAMPLES.md).

### Brute-force detection
```kql
Get_Event_Authentication
| where Result == "Failed Login"
| summarize FailedCount = count() by Username
| where FailedCount > 19
| invoke Enrich_Username_Employee()
| project Username, Name, Role, Email, FailedCount
| order by FailedCount desc
```

### Phishing triage by recipient seniority
```kql
Get_Email
| invoke Extract_Email_Sender_Domain()
| project EnvTime, EmailSender, Domain, Username = EmailRecipient, Subject, Url
| invoke Enrich_Username_Employee()
| extend Seniority = case(
    Role has_any ("CEO", "Chief", "Director", "VP", "President"), 3,
    Role has_any ("Manager", "Lead", "Senior"), 2,
    1)
| summarize
    TotalEmails = count(),
    SeniorityScore = sum(Seniority),
    Recipients = make_set(Name, 50),
    DistinctRecipients = dcount(Username)
  by Domain
| where DistinctRecipients >= 2
| order by SeniorityScore desc
| take 20
```

### Post-exploitation pivot from an indicator
```kql
let victims =
    Get_Event_FileCreation_All
    | where Filename has "<INDICATOR>"
    | distinct Hostname;
Get_Event_Process
| where Hostname in (victims)
| where ProcessCommandLine has_any ("rundll32", "regsvr32", "powershell", "systeminfo")
| project EnvTime, Hostname, Username, ProcessName, ProcessCommandLine
| order by EnvTime asc
```

### Suspicious outbound traffic enriched with identity
```kql
Get_Event_NetworkOutbound
| invoke Extract_Event_Network_Domain()
| where DomainName has_any ("<SUSPICIOUS_DOMAIN_1>", "<SUSPICIOUS_DOMAIN_2>")
| invoke Enrich_Ip_Employee()
| project EnvTime, Name, Role, DomainName, Url, ClientIp
| order by EnvTime desc
```

### External IP authentication anomaly
```kql
Get_Event_Authentication_All
| where not(ClientIp startswith "10.") and not(ClientIp startswith "192.168.")
| summarize
    Attempts = count(),
    Failures = countif(Result == "Failed Login"),
    Users = make_set(Username)
  by ClientIp
| order by Failures desc
| take 20
```

## MCP Tools Used

| Tool | Purpose |
|------|---------|
| `kusto_query` | Execute IRQL pipelines against a Kusto database |
| `kusto_table_schema_get` | Discover available tables and columns |
| `kusto_cluster_list` | List available ADX clusters |
| `kusto_database_list` | List databases in a cluster |

## Opening Queries in Kusto Explorer (Windows Only)

> **Optional convenience feature.** The default workflow is to output the KQL in chat and let the user copy it into Kusto Explorer or the VS Code Kusto extension manually. Auto-launch is opt-in only.

Always output the complete KQL query in the chat response with Step 1 (connect) and Step 2 (query) clearly labeled:

```
// Step 1: Connect to your cluster (skip if already connected)
// Example: uncomment to connect to the KC7 training cluster
// #connect cluster('kc7001.eastus.kusto.windows.net').database('ValdyTimes')
// Or replace with your own cluster:
// #connect cluster('<YOUR_CLUSTER>').database('<YOUR_DATABASE>')

// Step 2: Run the query below
<KQL_QUERY>
```

If the user asks to save or open in Kusto Explorer, follow the procedure in [references/KUSTO_EXPLORER_LAUNCH.md](references/KUSTO_EXPLORER_LAUNCH.md). Key rules:

- Use `ask_user` to confirm before writing files or launching executables
- Display file contents in chat so the user can review before opening
- Never use shell interpolation or here-strings — write files via `Set-Content`/`Add-Content`
- Never encode queries into browser URLs
- On macOS/Linux, save the `.kql` file and suggest the VS Code Kusto extension or ADX Web Explorer
- For graph visualization from IRQL data, see `azure-kusto-graph` and `azure-kusto-irql-graph`

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