Linear magnetic holes (LMHs) are localised depressions in the magnetic field magnitude in which the field direction remains nearly unchanged across the structure. Despite their prevalence in in-situ measurements near 1 AU, large-scale statistical investigations remain challenging because of the lack of reproducible and operational automated detection frameworks applicable to extended magnetic-field datasets. In this work, we present an automated and configurable detection framework for identifying LMHs using magnetic field data from the Magnetic Field Investigation (MFI) instrument onboard the WIND spacecraft. The pipeline applies a rolling-minimum search to the total magnetic-field magnitude, |B|, to identify candidate depressions across the entire time series. The continuous dataset processing enables accurate ambient-field estimation while reducing edge effects associated with segmented analysis. Each candidate event is subsequently filtered using three criteria: (i) a depth criterion requiring the minimum field magnitude to fall below 50% of the ambient field computed from surrounding regions, (ii) a directionality criterion that rejects events whose upstream-to-downstream field rotation exceeds 15°, thereby separating linear from rotational structures, and (iii) a data-quality criterion that discards intervals containing more than 40% missing measurements. Satisfying events are automatically cataloged and exported as comma-separated-value (CSV) files together with multi-page PDF reports containing event visualizations and statistical diagnostics. Validation against the Stevens & Kasper (2007) Wind/MFI catalogue, at the default depth (rd<0.5) and field-rotation (Θ<15°) thresholds, demonstrates a recovery (true-positive) rate of 95% and an estimated false-negative rate of ∼5%, with detected event durations, depth ratios, and occurrence rates in quantitative agreement with previously reported LMH observations at 1 AU. The pipeline provides a transparent, configurable, and extensible foundation for future large-sample investigations of solar-wind magnetic depressions.