Introduction: Accurate and rapid taxonomic classification of microbial genomes is fundamental for microbiology, epidemiology, and biodiversity monitoring. Existing bioinformatic pipelines often require large computational resources and multiple manual steps. Objective: We developed GenoScanner, a shell-based, high-speed, and hypothesis-driven pipeline to classify microbial genomes within minutes, integrating genomic analysis, phylogenetic inference, and molecular speciation testing under the Phylophenetic Species Concept. Methods: The pipeline compares the investigated genome against a curated genomic database (nomenclaturally valid genomes) to identify the closest phylogenetic neighbors. Subsequent Average Nucleotide Identity (ANI) estimation and robust phylogenetic reconstruction was carried out with JolyTree; Poisson Tree Processes Models (bPTP default or mPTP optional) were used to provide the basis for Bayesian species delimitation testing. This software relies on well-established bioinformatic tools such as NCBI Entrez Direct, BLAST+, and Biopython, among others. The rationale of GenoScanner explicitly evaluates three hypotheses to achieve better taxonomic resolution: 1. Genomic Coherence—via mutational distances and nucleotide identity; 2. Phylogenetic Monophyly—through rapid full-genome tree estimation; 3. Molecular Speciation—under probabilistic PTP models. Results & Advantages: The proposed framework enables rapid genome classification within minutes, significantly accelerating taxonomic workflows. By integrating genome-based phenetic data like ANI and Mash distance, phylogenomic analysis, and speciation-level evidence, it enhances the resolution and reliability of species assignments. Species delimitation is performed with robust accuracy using the PTP models, and full reproducibility is ensured through a standardized genomic databases. The approach is particularly effective for classifying bacteria, fungi, algae, and protists that are well represented in genomic repositories. These features collectively support diverse applications in molecular systematics, epidemiological monitoring, and biodiversity assessment. Conclusion: GenoScanner provides an efficient, reproducible, and conceptually robust framework for genome-based microbial taxonomy. By combining speed, accuracy, and formal species delimitation testing, it serves as a practical tool for both research and surveillance applications. Availability: https://github.com/ayixon/genomescanner.