Object Explorer is the main browsing and inspection surface for SQL Server objects in the currently selected database. It is built for read-oriented investigation so you can locate an object, inspect its definition, review lightweight statistics, trace dependencies, and launch AI Tune from one workflow.
- Browse user objects by database and object type.
- Search by object name with multi-term matching.
- Inspect source code or generated table definitions.
- Review cached execution or table-level metadata.
- Trace dependencies and launch AI-assisted analysis.
- Stored Procedures
- Views
- Functions
- Triggers
- Tables
The left side is the navigation and filtering area for database objects.
- Database selector
- Object Type filter
- Search box
- Object list in schema.object_name format
The right side shows detail tabs for the currently selected object.
- Source Code
- Statistics
- Relations
- AI Tune
Selecting an object triggers the module to load source, statistics, and relations immediately, and it also prepares the object context for AI Tune.
- Loads accessible online databases and excludes system-only cases like tempdb and model.
- Attempts to preselect the active database from the current connection.
- Changing the selection refreshes the object list for that database.
Narrow the list to All Objects, Stored Procedures, Views, Triggers, Functions, or Tables.
The current implementation maps these options to SQL Server object type codes such as P, V, FN, TR, and U.
- Filters the currently loaded list client-side.
- Splits the search text into lowercase terms.
- Keeps only items that match all entered terms.
- Displays objects in schema.object_name format with type icons.
- Stores schema, name, and SQL Server type metadata for downstream tabs.
- Acts as the main entry point for inspection and analysis.
- Loads programmable object definitions from SQL module metadata.
- Generates a best-effort CREATE TABLE script for tables.
- Falls back to a read-only message when source is not available.
- Shows cached execution metrics for procedures, views, functions, and triggers.
- Shows row count, size, columns, indexes, and recent read/write metadata for tables.
- Cached-plan metrics are useful for quick triage but are not full historical totals.
- Shows both Depends On and Used By lists.
- Supports double-click navigation into related objects.
- Dependency results are best-effort and may miss dynamic SQL references.
- Builds context from source, metadata, execution stats, relations, and plan signals.
- Supports Standard Analysis, Deep Analysis, and optional force refresh behavior.
- Provides progress, logs, confidence indicators, and export actions after analysis.
- Select an object from the left list.
- Open the AI Tune tab.
- Review the selected object label and collection status.
- Start analysis after the module prepares the object context.
- Review progress logs, status, and the confidence badge.
- Re-run or deepen the analysis when evidence is incomplete.
- Export reports as HTML, Markdown, or Text.
- Save the LLM request payload for audit or debugging when needed.
- Select the target database.
- Filter by object type and use search to find the object.
- Inspect definition or generated table script in Source Code.
- Review cached execution data or table metadata in Statistics.
- Check dependencies in Relations.
- Open AI Tune for deeper analysis and save the result if needed.
- No source definition does not always mean the object is unsupported; tables use generated scripts instead.
- No execution data in Statistics does not automatically mean the object is unused.
- Relations can be incomplete when dependency metadata cannot resolve dynamic SQL.
- AI Tune produces recommendations only and does not apply automatic changes.
- The module is read-only and intended for inspection, analysis, and evidence collection.