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    Run your first query

    Open a collection, run a find, read the result six different ways, and find out whether it used an index.

    Checked against v1.11.0 Updated
    The autocomplete list open on a nested field path, each entry showing its type
    Fig 01 Query editor · Typing "shipping." offers only the child fields, with types

    Open a collection

    Double-click a collection in the sidebar. That opens a query tab bound to that connection and database, with a find already written for you.

    Ctrl+K (Cmd+K on macOS) opens the command palette, which searches every connection, database, and collection at once, and > reaches the commands. It is usually faster than the tree once you know what you are looking for.

    Write the query

    The editor is Monaco, running against the MongoDB Node driver, so the syntax is the syntax you already know:

    db.orders.find({ status: { $ne: 'cancelled' } }).sort({ placedAt: -1 })

    Completions come from your actual collection schemas, not from a static list of operators. Type a field name and you get its real BSON type; type address. and you get the child fields under it.

    The part worth knowing about is what happens inside a pipeline. The editor folds the pipeline stage by stage: $project, $group, $count, $facet, $bucket and $unset reshape the result, and $addFields, $set and $lookup add to it. A field introduced by an earlier stage is still offered to you eight stages later. Where a stage’s output cannot be derived, the whole document is kept rather than guessed at, so valid code is never reported as an error. Schema-aware autocomplete has the full behaviour.

    Run it with Ctrl+Enter. Queries and Markdown notes autosave, so a tab you closed by accident comes back with its text.

    Read the result

    The result pane has six views, and the one you want depends on the question:

    View Use it for
    Table Scanning many documents with the same shape
    Tree One document at a time, with the BSON type of every value
    JSON Copying the raw Extended JSON out
    Result A write outcome, or a single value
    Explain Whether the query used an index, and how efficiently
    Chart Seeing the shape of the numbers (Pro)

    Switch with the buttons above the result. Ctrl+I opens a preview drawer that follows the focused row.

    Check that it used an index

    This is the habit worth forming early. Auto-explain collects plan statistics while a read runs, so the result reports its scan type without you running a second query. Hovering that badge details the plan: scan type, index name, documents scanned, and documents returned.

    If it scanned the collection, open the Explain view. It grades the plan as collection scan, indexed, optimal, or ungraded, shows the execution plan as a tree, and suggests the index that would remove the scan, with a button that creates it.

    You can also paste an explain plan from anywhere else into the explain visualizer, which runs in the browser with nothing installed.

    Next

    The explain view grading a query that runs a collection scan, with an index suggestion
    Fig 02 Explain · A COLLSCAN graded, with the index that would fix it