T-SQL to Databricks Migration Auditor

(This is the scanner's real output on the bundled example examples/sample_proc.sql, plus the skill's rewrite. The full table is shortened here.)

# T-SQL -> Databricks scan
Files scanned: 1 | findings: 24 (high 9, medium 6, low 9)

| high   | :1  | Stored procedure       | Unity Catalog SQL procedure or notebook/job task |
| high   | :5  | TRY/CATCH              | SQL scripting handler or PySpark try/except |
| high   | :6  | Explicit transaction   | single MERGE or stage + swap |
| high   | :9  | CONVERT with style 120 | date_format(d,'yyyy-MM-dd') |
| high   | :11 | #temp table            | CREATE OR REPLACE TEMP VIEW / CTE |
| medium | :16 | UPDATE ... FROM join   | MERGE INTO |
| low    | :12 | NOLOCK hint            | remove |

Effort: 1 object, bucket = redesign (procedure + transaction + temp table).

Proposed Databricks SQL

CREATE OR REPLACE TEMP VIEW recent AS
SELECT o.OrderID,
       COALESCE(c.`Customer Name`, 'Unknown') AS CustomerName,
       date_format(o.OrderDate, 'yyyy-MM-dd') AS OrderDay,
       concat(c.FirstName, ' ', c.LastName) AS FullName,   -- VERIFY: NULL names give NULL, same as T-SQL '+'
       o.Amount
FROM main.sales.orders o
JOIN main.sales.customers c ON c.CustomerID = o.CustomerID  -- VERIFY: case-sensitive compare if keys are strings
WHERE o.OrderDate >= dateadd(DAY, -1, :run_date);
-- VERIFY: the original TOP 1000 had no ORDER BY, so it was non-deterministic. It's dropped here; confirm the intent.

MERGE INTO main.sales.fact_orders t
USING recent r ON r.OrderID = t.OrderID
WHEN MATCHED THEN UPDATE SET t.Amount = r.Amount;
-- A single MERGE is atomic on Delta, so the BEGIN TRAN/COMMIT wrapper isn't needed.

Then come row-count, sum(Amount) and hash-diff queries for fact_orders on both sides. (main.sales is a placeholder; the skill asks for your catalog mapping.)