AI SQL Tuner Studio User Guide

Table of Contents

1. Getting Started
   • System Requirements
   • First Launch
2. Connections
   • Adding a New Connection
   • Managing Connections
3. Tuning Goals
   • Model Selection
   • Reasoning Effort
   • Server Health Check
   • Fix Deadlocks
   • Code Review
   • Index Tuning
   • Query Tuner
   • Locking and Blocking Analysis
4. License Configuration
5. AI Configuration
   • Setting Up Azure AI Foundry
   • How the AI is Prompted
6. Running an Analysis
   • Reviewing a Run Before it Leaves Your Machine
7. Viewing Results
   • Tuning Setup Drawer
   • Console Drawer
   • HTML Report
8. Saving and Exporting
   • Save HTML Report
   • Open in Browser
   • Export SQL
9. Status Bar
10. Troubleshooting
    • Connection Failed
    • System Database Validation Error
    • Query Tuner Errors
    • Azure SQL Database Limitations
    • Rate Limit Errors
    • Request Too Large
    • Truncated Report
    • WebView2 Errors
    • Documentation Window
    • Release Notes Window
    • Windows Server 2022 Install Error
11. Menu Reference
    • File
    • View
    • Help
12. Keyboard Shortcuts
13. Data Privacy
14. Support

Getting Started

System Requirements

• Windows 10 version 1809 or later / Windows 11
• .NET 10.0 Runtime (included with the app)
• Internet connection (for Azure OpenAI calls)
• SQL Server 2016 or later (on-premises, Azure SQL Database, Azure SQL Managed Instance, or Microsoft Fabric SQL Database)

First Launch

1. Launch AI SQL Tuner Studio from the Start menu or desktop shortcut.
2. The main window displays:
   • Left panel: Configuration sections — Connections, Edition & Licensing, and AI Configuration
   • Right panel: Tuning Setup drawer (goal cards, options, model/reasoning/run controls — collapses automatically when a run starts), the HTML report preview, and the Console drawer
   • Footer status bar: Persistent bar at the bottom showing connection, license edition, primary model, run state, and session run count

The report area initially shows an illustrated empty state with the heading “No report yet” and hints about available tuning goals. Once you run your first analysis, the empty state is replaced with the generated report.

The app follows the active Windows light/dark theme. The left navigation panel, top header/menu, footer status bar, HTML output toolbar, console drawer, section headers, connection list, and action buttons automatically adjust their contrast for readability in dark mode. Left-panel section headers and saved connection names use stronger contrast to remain readable in dark theme environments, and dark mode uses deeper surfaces with clearer panel separation so cards, lists, and controls remain easy to distinguish. Manual theme changes via View → Theme apply instantly across the entire window, including the in-app HTML report preview.

You can override the system theme via View → Theme:

Option	Behaviour
Follow System	Matches the Windows dark/light setting (default)
Light	Forces the light (Paper/Teal) palette regardless of the OS setting
Dark	Forces the dark (Graphite/Mint) palette regardless of the OS setting

Your choice is remembered between sessions. The active option is shown with a ✓ check-mark.

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Connections

Before running an analysis, configure at least one SQL Server connection.

Adding a New Connection

1. In the Connections section, click New.
2. Fill in the connection details:
   • Connection Name: A friendly name for this connection (e.g., “Production Server”)
   • Server Name: The SQL Server hostname or IP address
   • Database Name: Target database name (optional; defaults to master)
3. Choose an authentication method:
   • Windows Authentication: Uses your current Windows credentials
   • SQL Server Authentication: Enter username and password
   • Microsoft Entra Interactive: For Azure SQL with multi-factor authentication
4. Optionally enable Trust Server Certificate for development environments.
5. Click Add to save the connection. The connection will be tested before saving.

Managing Connections

• Select a connection from the list before running an analysis.
• Click Edit to modify an existing connection.
• Connections are stored locally in %LOCALAPPDATA%\AISQLTuner\AISQLTunerStudio\connections.json.

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Tuning Goals

Select a tuning goal to determine what type of analysis to perform.

Model Selection

Use the MODEL dropdown (above the Run Analysis button) to choose the AI model for the analysis:

Option	Provider	Notes
GPT-5.4 (Azure OpenAI)	Azure OpenAI	Default; uses the Responses API
Claude Sonnet 4.6 (Anthropic)	Azure AI Foundry	Anthropic Messages API
Claude Opus 4.6 (Anthropic · Corporate)	Azure AI Foundry	Requires Corporate edition
Claude Opus 4.7 (Anthropic · Corporate)	Azure AI Foundry	Requires Corporate edition

All models use the same Azure AI Foundry endpoint and API key configured in the AI Configuration section.

The model you select is always the model that runs — selection is read directly from the dropdown at the moment you click Run Analysis, so switching models is effective immediately without needing to restart or re-save settings.

Reasoning Effort

Use the REASONING dropdown to control the depth of AI analysis:

• Low: Balanced speed and detail (default)
• Medium: More thorough analysis
• High: Most comprehensive, slower (best for complex issues)

GPT models: Low/Medium/High maps directly to native reasoning effort levels.

Claude models: Low/Medium/High maps to 32 K / 64 K / 128 K maximum output tokens (within the 400 K TPM limit).

This setting applies to all tuning goals and is saved automatically.

Server Health Check

Comprehensive analysis of your SQL Server instance including:

• Wait statistics (excluding benign wait types, showing waits > 1% of total)
• I/O latency by database file
• System configuration review
• sp_configure settings audit
• Plan cache analysis (top resource-consuming queries)
• High-impact missing indexes across all user databases
• Query Store status for all databases
• DBCC CHECKDB history for all databases
• Connection encryption status
• Sysadmin role membership audit
• Recent deadlock detection (past 7 days)
• Backup & recovery status (last full/diff/log backup times, recovery model, and risk flags for missing or delayed backups)

Database requirement: Optional (defaults to master)

Note: Scans all online user databases for comprehensive health assessment.

Fix Deadlocks

Analyzes recent deadlocks from the system_health extended events session and provides recommendations to prevent them.

Options:

• Deadlocks to analyze: Number of recent deadlocks to examine (1–20, default 5)

Database requirement: Optional (defaults to master)

Important: Not supported on Azure SQL Database or Microsoft Fabric SQL Database (system_health file target not accessible on these platforms).

Code Review

AI-powered review of your T-SQL stored procedures, functions, and triggers for performance issues, anti-patterns, and best practice violations.

Includes:

• Stored procedures, functions, triggers, and views (based on your object type selection)
• Top tables by row count (>1,000 rows)
• Largest index usage summary (key/included columns, seeks/scans/lookups/updates, size)

Options:

• Order: Newest or Oldest (by modification date)
• Objects: Number of objects to review (1–100, default 100)
• Object types: Stored procedures, functions, triggers, views (select at least one)
• Schema (optional): Limit the review to objects in a specific schema (e.g., dbo)
• Object (optional): Limit the review to a single object by name (e.g., usp_GetOrders). Requires Schema when specified.

Database requirement: Required – must specify a user database (cannot run against system databases: master, tempdb, model, msdb)

Index Tuning

Analyzes missing index recommendations, index usage statistics, query patterns from the plan cache, and constraints to provide specific index optimization recommendations.

Includes:

• Missing index analysis with impact scores
• Index usage statistics (seeks, scans, lookups, updates, key/included columns, size, compression)
• Constraint and foreign key relationships
• Column cardinality estimates for candidate and explicitly selected tables
• Large table identification (>1M rows, top 50)
• Index page density and fragmentation signals
• Plan cache query analysis (query text snippets)
• Database statistics configuration review
• Query Store workload insights, forced plan failures, and automatic tuning state

Options:

• Schema: Optional schema filter for narrowing analysis to a single table
• Table: Optional table filter; requires Schema when specified

Scope behavior:

• The schema/table filter applies to object-scoped sections such as missing indexes, index usage, constraints, column cardinality, large tables, and index page density.
• For Index Page Density, specifying both schema and table limits results to that table only; specifying only schema limits the candidate tables to missing-index and large-table candidates within that schema.
• Database-level sections such as plan cache, Query Store, forced plan failures, automatic tuning, and database statistics settings continue to analyze the selected database.

Database requirement: Required – must specify a user database (cannot run against system databases: master, tempdb, model, msdb)

Query Tuner

Focused tuning for a single SQL query. Query Tuner captures the estimated execution plan for the query, extracts referenced tables and operators, collects targeted metadata for those tables, and asks the AI model for query-level recommendations.

Includes:

• The query text you enter in the Query to analyze box
• Estimated execution plan XML captured with SET SHOWPLAN_XML ON (the query is not executed during plan capture)
• Execution plan summary including estimated total cost, referenced tables, operators, warnings, and missing index recommendations from the plan
• Targeted metadata for referenced tables only: index usage statistics, DMV missing indexes, table sizes, foreign keys, column cardinality, and statistics settings

Prompted AI output typically includes:

• Query rewrite suggestions with before/after T-SQL examples
• Index recommendations with full scripts
• For each index recommendation: estimatedStorageBytes, expectedReadBenefitPercent, expectedWriteOverheadPercent, and maintenanceNotes
• Statistics maintenance recommendations
• Parameter sniffing or plan guidance when applicable
• Evidence lines from SHOWPLAN XML or collected metadata for each major finding
• Confidence level estimates and prioritized recommendations

Options:

• Query to analyze: Required multiline text box for the SQL statement you want reviewed
• Reasoning effort: Low, Medium, or High

Database requirement: Required – must specify a user database (cannot run against system databases: master, tempdb, model, msdb)

Permissions commonly required:

• SHOWPLAN
• VIEW DATABASE STATE
• VIEW DEFINITION

Platform support: Supported for on-premises SQL Server, Azure SQL Database, Azure SQL Managed Instance, and Microsoft Fabric SQL Database.

Locking and Blocking Analysis

Captures a live concurrency snapshot for the selected user database and asks the AI to identify root causes of active blocking, lock amplification, deadlocks, and TempDB-related contention.

Includes:

• Active blocker → waiter chains with compact statement-level SQL and short batch context
• Summarized lock inventory for the selected database plus tempdb
• Long-running transactions
• Missing index and index usage evidence tied to blocking patterns
• Blocker query plans and deadlock history when available
• Query Store top-query evidence and database settings that influence blocking behavior
• TempDB contention signals including pagelatch waits, version store usage, and spilling queries

Prompted AI output typically includes:

• Blocking tree and root-cause classification
• Prioritized fixes with evidence references and confidence levels
• Query or code-change recommendations when the captured SQL suggests non-sargable predicates, broad transaction scope, scans, or oversized modifications
• Enablement guidance when Query Store or deadlock history is unavailable

Database requirement: Required – must specify a user database (cannot run against system databases: master, tempdb, model, msdb)

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License Configuration

Edition	Features
Free	Supports SQL Server Developer Edition
Standard	Adds support for SQL Server Standard Edition, Managed Instance General Purpose, Azure SQL and Fabric Database, limited to 2 instances
Pro	Adds support for all editions of SQL, limited to 2 instances
Corporate	Adds support for unlimited instances

1. Select your edition from the dropdown.
2. Click License… (or use Help → Manage license… / Ctrl+L) to open the license dialog.
3. In the dialog, paste your license key using the Paste button or type it in the revealed field.
4. Check Activate license to enable validation. This should only be checked the first time to activate the license. After the first run it should be unchecked.
5. Click Save to store the key. The sidebar will show a status dot and label reflecting the activation state.

Note: The license key is stored locally and is never displayed in the main sidebar. Use the Reveal / Hide toggle inside the license dialog to view or edit the key.

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AI Configuration

Setting Up Azure AI Foundry

Both Azure OpenAI (GPT) and Anthropic (Claude) models use the same Azure AI Foundry endpoint and API key.

1. Endpoint: Your Azure AI Foundry resource endpoint (e.g., https://your-resource.cognitiveservices.azure.com/)
2. API Key: Your Azure AI Foundry API key
3. Primary model: Deployment name for the main model (e.g., gpt-5.4, claude-sonnet-4-6)
4. Fallback model: Optional secondary deployment for rate limiting or large-request scenarios (e.g., gpt-5.3-codex, claude-sonnet-4-6)

The app selects deployments based on request size:

• Requests within the primary model’s character limit use the primary deployment.
• Larger requests automatically switch to the fallback deployment (if configured).
• Requests above the maximum supported size are blocked with a prompt to reduce the request size.

Tip: The app automatically detects the actual model used when deployments route to different model versions.

How the AI is Prompted

When running from the UI, the app asks the model to return a complete HTML document with:

• An Executive summary with top priorities
• Detailed prioritized recommendations
• A left-side table of contents
• A unique report title built from the report type plus one or more context anchors (such as server, database, query hash, scope, or date/identifier)
• Server name, server version, and database name when available
• Confidence level estimates
• A footer showing the AI SQL Tuner Studio version, model used, reasoning effort, and the UTC analysis timestamp

Each tuning goal has additional goal-specific instructions. For example:

• Code Review focuses on stored procedures, functions, triggers, and views plus table/index context
• Index Tuning emphasizes index benefit vs. write overhead, Query Store insights, and full scripts
• Query Tuner emphasizes execution plan evidence, query rewrites, targeted index design, and statistics guidance
• Locking and Blocking Analysis emphasizes blocker/waiter SQL, compact plan evidence, and query/code changes that reduce blocking scope

For HTML reports, the generated title is used consistently for the HTML <title>, the document <h1>, and the structured-data headline so each report is treated as a distinct document.

Check Save key to store your key locally, then click Save AI settings to persist your configuration.

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Running an Analysis

1. Select a connection from the Connections list in the left panel.
2. Choose a tuning goal by clicking one of the goal preset cards in the right panel.
3. Configure goal options if applicable (deadlock count, code review scope, index tuning filters, query text, etc.).
4. Verify database selection:
   • For Code Review, Index Tuning, or Query Tuner: Ensure a user database is specified (not master, tempdb, model, or msdb)
   • For Server Health Check or Fix Deadlocks: Database is optional (defaults to master)
5. Select a model from the MODEL dropdown.
6. Adjust reasoning effort if needed.
7. If using Query Tuner, paste the SQL statement into Query to analyze.
8. Click Run Analysis (or press Ctrl+R).

Reviewing a run before it leaves your machine

When you click Run Analysis, a Review run plan dialog appears showing exactly what will happen:

• Connection — server, database, authentication method, encryption state.
• AI call — provider, endpoint host, model, fallback model, reasoning level, output token budget, and whether the endpoint is cloud or on-premise.
• License — edition and activation status.
• Collectors — a table listing each data collector that will query your SQL Server, including the DMVs it touches, estimated row cap, and estimated payload size. Click any row to expand its description and SQL fingerprint. Each row corresponds to a distinct collection section executed at run time — goals such as Index Tuning, Query Tuner, Locking and Blocking, and Server Health each run multiple sections, all of which are shown.
• Payload estimate — total estimated bytes and input tokens (lower bound).
• Plan fingerprint — a stable hash (16 hex characters) identifying this specific configuration. Click the fingerprint pill to copy it.

From the dialog you can:

• Save plan… — Export the plan as a JSON file ({server}-{goal}-{utc}.runplan.json) suitable for attaching to change-control tickets or procurement reviews. The JSON never contains secrets (no API keys, no passwords, no license keys).
• Don’t show again until settings change — Suppress the dialog for repeated runs with the same configuration. The dialog automatically re-appears when you change the goal, model, reasoning level, server, or database.
• Send to AI — Proceed with the run.
• Cancel — Abort without starting the run.

The 8-line plan summary is always logged to the Console drawer regardless of dialog suppression, providing an audit trail for every run.

When you click Run Analysis, the Tuning Setup drawer automatically collapses to give the HTML report panel maximum space. The collapsed header shows a one-line summary of your run configuration (e.g. Code Review • Claude Opus 4.7 • High • MyServer/MyDB) and a live status badge (e.g. Running…, Completed, Failed). Click the header bar to re-expand the drawer and adjust settings for the next run.

If the request exceeds the maximum supported size, the app will display a dialog asking you to reduce the request size before retrying.

Progress and status messages appear in the Console drawer at the bottom of the right panel. Click the Console header bar (or press Ctrl+J) to expand or collapse it. The AI model in use is shown in the console and in the footer status bar.

The HTML report renders progressively as the AI response streams in — content appears in the report panel before the analysis is fully complete. You can scroll and read early sections while the rest of the report is still being generated.

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Viewing Results

Tuning Setup Drawer

The Tuning Setup drawer sits at the top of the right panel and contains the goal cards, goal-specific options, model/reasoning dropdowns, and the Run Analysis button. It starts expanded so you can configure your run.

• Toggle: Click the Tuning Setup header bar to expand or collapse the drawer at any time.
• Auto-collapse: The drawer collapses automatically when you click Run Analysis, maximising the space available for the HTML report.
• Dynamic resize: The drawer automatically resizes to fit the selected goal’s options — goals with more settings (e.g. Code Review, Query Tuner) expand the drawer taller; simpler goals keep it compact.
• Collapsed header: Shows a one-line summary of the run configuration — Goal • Model • Reasoning • Server/Database — plus a live status badge (Running…, Completed, Failed, Cancelled).
• Resize: Drag the handle at the bottom of the expanded drawer to adjust its height manually.

Console Drawer

The Console is a collapsible drawer at the bottom of the right panel. Click the Console header bar (or press Ctrl+J) to expand or collapse it. When collapsed, the latest log line is shown in the header for quick status at a glance. Use the Clear button (trash icon) to clear the console output.

The Console shows:

• Connection status and database information
• Data collection progress and per-section character counts
• AI model in use (shows actual model if routing occurs)
• Reasoning effort level
• Query Tuner execution-plan retrieval and metadata collection status when applicable
• Truncation warnings if the AI response was cut short due to output token limits
• Any warnings or errors

HTML Report

Interactive, professionally formatted report with:

• Executive summary with top priorities
• Detailed findings organized by severity
• Actionable recommendations with T-SQL scripts
• Table of contents for easy navigation
• Platform-specific guidance based on your SQL Server edition and version

Report features:

• Progressive rendering: The report appears in the panel as the AI streams its response — you can read and scroll through early sections while the analysis is still running. The full report is available once the status shows Completed.
• Color-coded severity indicators
• Code blocks with proper formatting
• Responsive design (adapts to light/dark mode — the in-app report preview automatically follows the active View → Theme setting; saved HTML files adapt to the browser’s system theme)
• Includes server name, version, and database information
• Footer includes the model name, reasoning effort, and analysis timestamp
• Truncation warning banner if the AI response was incomplete

For Query Tuner, the report may also include:

• Execution plan bottlenecks and warnings
• Query rewrite examples
• Query-specific index recommendations with benefit/overhead details
• Statistics recommendations tied to the referenced tables

Use the horizontal splitter to resize the Console and HTML Report panels.

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Saving and Exporting

Save HTML Report

1. Click Save HTML button or use File > Save Output menu (Ctrl+S).
2. Choose a destination folder.
3. Enter or confirm the filename (defaults to the report HTML title converted to kebab case, for example index-tuning-salesdb-2026-05-06.html). If the title is unavailable, the app falls back to a goal-based filename.
4. Click Save.

The report can be opened in any web browser and shared with your team.

Open in Browser

Click Open in Browser to view the current report in your default web browser. The file is temporarily saved to %TEMP%\AISQLTuner\preview\aisqltuner-preview.html.

Tip: Opening in a browser allows you to use browser features like print, zoom, and search.

Export SQL

Click Export SQL in the report toolbar to extract every executable T-SQL script from the report’s Scripts section into a single .sql file ready to run in SSMS or sqlcmd.

• What gets exported: only the SQL inside the report’s Scripts section (<section id="scripts">). Each script is preceded by a comment derived from its <h3> heading so the output is self-documenting. Illustrative SQL fragments elsewhere in the report (in inline <code> blocks) are intentionally excluded so the exported file contains only scripts the AI explicitly recommends running.
• Filename: defaults to the report’s HTML title converted to kebab case with a .sql extension — for example, index-tuning-report-rockypc-sqlstorm-dbo-votes-2026-05-12-03-04-35-utc.sql. This matches the Save HTML naming convention so paired .html and .sql files sort together.
• No Scripts section? Every report produced by the current prompt includes a Scripts section, even when there are no recommended actions (in which case the section explains why). If you load an older report that lacks one, Export SQL will tell you there is nothing to export.

Safety: Always review the exported SQL before running it. Scripts may include DROP, ALTER, or UPDATE STATISTICS operations. Test in a non-production environment first.

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Status Bar

A persistent footer bar at the bottom of the window shows at-a-glance information:

Segment	Description
Connection dot + name	Green = last test succeeded; amber = untested; grey = no connection selected. Hover for server, database, and auth details.
License pill	Shows the active edition (Free, Standard, Pro, Corporate). Hover for a hint to change it.
Model	Shows the primary model deployment name. Hover to see both primary and fallback model.
Run state	Shows Ready, Running…, Completed, Completed (truncated), or Cancelled. Hover to see the completion timestamp of the last run.
Run count	Number of analyses started since the app was launched. Resets on close.

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Troubleshooting

Connection Failed

• Verify server name and port (default SQL Server port is 1433).
• Check firewall rules on both client and server.
• For Azure SQL, ensure your client IP address is allowed in the firewall rules.
• For Azure SQL with Microsoft Entra Interactive, verify you have access permissions.
• Try enabling Trust Server Certificate for development/test environments.

System Database Validation Error

If you see an error about system databases when running Code Review, Index Tuning, or Query Tuner:

• Edit your connection and specify a user database instead of master, tempdb, model, or msdb.
• These goals require a user database to provide meaningful recommendations.

Query Tuner Errors

If Query Tuner fails before analysis starts:

• Ensure Query to analyze is not blank.
• Check the SQL for syntax errors.
• Verify the login has SHOWPLAN, VIEW DATABASE STATE, and VIEW DEFINITION on the target database.

If the plan is returned but no user tables are found:

• Metadata collection may be skipped.
• The AI can still analyze the estimated execution plan itself.

Azure SQL Database Limitations

• Fix Deadlocks goal is not available on Azure SQL Database or Microsoft Fabric SQL Database.
• Use Code Review, Index Tuning, or Query Tuner instead, or enable Query Store for deadlock analysis.

Rate Limit Errors

The app automatically switches to the secondary deployment if configured. If you continue to experience rate limits:

• Consider using a lower reasoning effort level.
• Configure a secondary model deployment in your Azure OpenAI resource.
• Check your Azure OpenAI quota and consider requesting an increase.

Request Too Large

If the app shows a Request too large dialog, reduce the request size and try again:

• Lower the number of objects in Code Review.
• Reduce the scope of the analysis by selecting a smaller database.
• For Query Tuner, simplify the query or reduce the amount of referenced object complexity.
• Try a lower reasoning effort level.

Truncated Report

If the console shows a truncation warning or the status shows “Completed (truncated)”, the AI response was cut short due to output token limits. The report may be incomplete. To resolve:

• Lower the Reasoning effort level.
• Reduce the number of objects or scope of the analysis.

WebView2 Errors

If the HTML report pane fails to load:

• Install Microsoft Edge WebView2 Runtime from: https://developer.microsoft.com/en-us/microsoft-edge/webview2/
• Restart the application after installation.

Documentation Window

The documentation opens in a separate, resizable window. If you don’t see it:

• Check if it opened behind the main window.
• Look for it in the taskbar.
• Close and reopen from Help > Documentation.

Release Notes Window

The release notes open in the same style of separate, resizable window when you click Release Notes in Help > About. If you don’t see them:

• Check if the window opened behind the main window.
• Look for a second app window in the taskbar.
• Reopen Help > About and click Release Notes again.

Windows Server 2022 install error: Windows App Runtime missing

If you install the app by double-clicking the AI SQL Tuner Studio_*.msixbundle on Windows Server 2022, you may see:

Microsoft.WindowsAppRuntime.1_8 framework cannot be found

This means the Windows App Runtime 1.8 framework is not installed on the server.

Option A (recommended): Install Windows App Runtime 1.8 using Microsoft’s installer

1. Open Microsoft’s official Windows App SDK downloads page: https://learn.microsoft.com/windows/apps/windows-app-sdk/downloads
2. In the Windows App Runtime section, download the Windows App Runtime 1.8 installer for x64.
3. Run the installer.
4. Retry installing the app by double-clicking the .msixbundle again.

Option B (offline / locked-down servers): Install the Windows App Runtime 1.8 MSIX packages

1. Download the Windows App Runtime 1.8 MSIX packages (x64) from: https://learn.microsoft.com/windows/apps/windows-app-sdk/downloads

2. Copy these files onto the server:

   • Microsoft.WindowsAppRuntime.Main.1.8.msix
   • Microsoft.WindowsAppRuntime.Singleton.1.8.msix
   • Microsoft.WindowsAppRuntime.DDLM.1.8.msix
   • Microsoft.WindowsAppRuntime.1.8.msix

3. Open PowerShell as Administrator, cd to the folder containing the files, then install in this order:

   • Add-AppxPackage -Path .\Microsoft.WindowsAppRuntime.Main.1.8.msix
   • Add-AppxPackage -Path .\Microsoft.WindowsAppRuntime.Singleton.1.8.msix
   • Add-AppxPackage -Path .\Microsoft.WindowsAppRuntime.DDLM.1.8.msix
   • Add-AppxPackage -Path .\Microsoft.WindowsAppRuntime.1.8.msix

4. Retry installing the app by double-clicking the .msixbundle.

Note: Your server may require enabling MSIX sideloading/trusted app installation per organization policy.

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Menu Reference

File

Item	Description
Save Output (Ctrl+S)	Save the current HTML report to a file
Exit (Ctrl+Q)	Close the application

View

Item	Description
Theme → Follow System (Ctrl+Shift+T)	Use the Windows dark/light setting
Theme → Light	Force the light (Paper/Teal) palette
Theme → Dark	Force the dark (Graphite/Mint) palette

Help

Item	Description
Manage license… (Ctrl+L)	Open the license dialog to enter or update your key
Check for Updates	Compares the installed version against the latest release and prompts to download if a newer version is available
Documentation	Opens this user guide in a separate window
About	Shows the installed version number, copyright information, and a Release Notes link that opens the packaged release notes in a separate window

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Keyboard Shortcuts

Shortcut	Action
Ctrl+S	Save HTML output
Ctrl+Q	Exit application
Ctrl+R	Run analysis
Ctrl+J	Toggle console drawer
Ctrl+L	Manage license
Ctrl+Shift+T	Switch theme to Follow System

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Data Privacy

• Connection credentials: Stored locally in %LOCALAPPDATA%\AISQLTuner\AISQLTunerStudio\connections.json (optional, encrypted for passwords).
• API keys: Stored locally only if “Save key” checkbox is enabled.
• SQL metadata: Query metadata and performance statistics are sent to Azure OpenAI for analysis.
• Query Tuner input: If you use Query Tuner, the query text you enter, the estimated execution plan XML, and targeted metadata for referenced tables are sent for analysis.
• No external storage: No data is stored on AI SQL Tuner servers.
• Azure OpenAI: Subject to Microsoft’s data privacy policies. Data is not used for model training.

What is sent to Azure OpenAI:

• Database schema information (table/column names, indexes)
• Query text from plan cache or stored procedures
• Query text entered manually for Query Tuner
• Estimated execution plan XML and plan warnings for Query Tuner
• Performance statistics (waits, I/O, execution counts)
• Configuration settings

What is NOT sent:

• Actual table data or query results
• Passwords or credentials
• Personal identifying information (unless present in object names)

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Support

• AISQLTuner: https://aisqltuner.com/contact/
• Email: support@aisqltuner.com

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