Skill UI

deepTools is a Python command-line suite for NGS workflows, converting BAM files into normalized coverage, running QC (fingerprint, correlation, PCA), comparing samples, and rendering heatmaps or profiles for ChIP-seq, RNA-seq, and ATAC-seq analyses.

High-performance Rust toolkit with Python bindings for genomic interval analysis, covering overlap detection, coverage track generation, ML tokenization, reference sequence handling, fragment processing, and scoring workflows for sequencing datasets.

Pysam offers Python bindings to htslib for reading and writing SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences, enabling coverage stats, pileup analysis, variant queries, and seamless integration into NGS pipelines.

This skill provides a comprehensive method for querying advanced threat intelligence using ATT&CK data. It maps the Tactics, Techniques, and Procedures (TTPs) of specific APT groups into MITRE ATT&CK Navigator layers. Users can build multi-layer heatmaps to identify detection gaps, compare threat coverage, and create structured threat-intel reports for defense engineering.

This skill provides a systematic method to map observed Indicators of Compromise (IOCs) and threat actor TTPs to the global MITRE ATT&CK framework. It guides users in building technique coverage heatmaps using the ATT&CK Navigator, identifying critical detection gaps, and generating actionable threat intelligence reports across Enterprise, Mobile, and ICS domains. Ideal for SOC analysts, threat hunters, and security researchers seeking structured threat analysis.

Gtars offers local genomic interval models, set algebra, overlap/count operations, consensus and coverage, tokenization, fragment processing, and refget/BEDbase planning across Python, Rust, and CLI.

High-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames. Supports overlap, nearest, merge, coverage, complement and subtract for BED/VCF/BAM/GFF files, with streaming and cloud-native access as a faster bioframe alternative.

A Python library for reading, querying, filtering, and writing genomic file formats including SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, and tabix data. Supports pileup, coverage analysis, indexing, and CRAM reference operations with HTSlib integration. Ideal for bioinformatics workflows requiring low-level streaming access to genomic data.

A comprehensive workflow designed to build deep revenue analytics dashboards using exported Clari data. It calculates key metrics such as forecast accuracy, pipeline coverage ratios, and tracks representative performance changes. Ideal for financial analysts and sales managers needing to assess revenue health and forecast reliability.

A unified CLI tool that queries multiple web and academic search engines (Crossref, Brave, Tavily, DuckDuckGo) in parallel. It aggregates results, extracting structured metadata like DOI, publication year, and authors. Ideal for deep research, cross-checking claims, or comparing scholarly coverage against general web results.

This skill integrates with Monte Carlo's observability platform to provide a comprehensive health report for data assets. It checks critical metrics including data freshness, active alerts, monitoring coverage, asset importance, and the health of upstream dependencies. Activates when users inquire about the status, reliability, or quality of a data table.

This framework provides a rigorous methodology for conducting systematic literature reviews and comprehensive academic syntheses. It guides researchers through building transparent coverage, designing robust coding matrices, and choosing the correct integration method (narrative, systematic, or bibliometric) to move beyond simple summarization and create an auditable intellectual map of a field.