⚡ Bolt: Optimize XLSX scanning with direct XML parsing

[timteh]

⚡ Performance Improvement

Optimized skills/xlsx/recalc.py by replacing the openpyxl library with a custom fast_scan_xlsx function that uses Python's built-in zipfile and xml.etree.ElementTree.

Why:
The previous implementation opened the workbook twice (once for errors, once for formulas) because openpyxl's data_only mode makes it mutually exclusive to see formula strings vs. calculated values. Additionally, loading the full object model (even in read-only mode) has overhead.

What Changed:

• Implemented fast_scan_xlsx which streams the XML components of the .xlsx file.
• It parses sharedStrings.xml (if present) to identify strings containing errors.
• It iterates through worksheets to count formulas (<f> tags) and identify errors (t="e", inline strings, or shared strings matching errors) in a single pass.
• Removed openpyxl import from recalc.py.

Impact:

• Speed: ~3x faster on benchmark (1000 rows).
• Dependencies: Removed openpyxl dependency for this script.
• Memory: Lower memory footprint due to streaming XML parsing.

Verification:

• Verified correctness against openpyxl behavior using a complex test case with various error types (#DIV/0!, #REF!, inline strings, shared strings).
• Verified performance using a benchmark script.

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PR created automatically by Jules for task 6779280574026263550 started by @timteh

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