ag-pq-auditor

You can audit Power Query M code by running deterministic rule-based checks on Excel workbooks or loose .m files to identify query folding breaks, hardcoded file paths, and missing error handling with severity-rated findings.

Slow Power Query refresh times are often caused by performance bottlenecks like mid-query Table.Buffer calls, unfiltered wide sources, or broken query folding. Auditing the M code can identify these specific issues and provide recommendations to fix them in minutes.

To check Excel data pipelines for security vulnerabilities, you can scan the extracted M code for embedded credentials and hardcoded file paths. The audit returns severity-rated security compliance findings with clear remediation guidance to secure your analytics workflow.

Yes, you can audit loose .m files directly instead of extracting Power Query code from Excel workbooks. The skill supports multiple input formats, including Windows COM automation for workbooks, loose .m files, and a built-in demo mode for testing without live data.

Yes, extracting Power Query M code from Excel workbooks requires the pywin32 dependency for Windows COM automation. However, you can still audit loose .m files or use the built-in demo mode if you do not need to extract queries directly from workbook files.

A rule-based audit for Power Query data quality is limited to deterministic checks for known patterns like coding standards violations and circular dependencies. It does not use dynamic runtime analysis, so it identifies architecture flaws and security risks statically without executing the actual queries.