Skill UI

Centralizes proven red team methodologies into an automated reconnaissance and vulnerability discovery workflow that sequences asset discovery, live host validation, fingerprinting, content hunting, and exploit surface analysis for bug bounty and defensive assessments.

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.

Query the JASPAR REST API and Python helpers to retrieve TF binding profiles, convert PFMs to PWMs, and scan DNA sequences for high-confidence motifs, enabling regulatory variant interpretation, ChIP/ATAC analysis, and TF network construction.

A comprehensive toolkit for reconstructing and analyzing the evolutionary history of biological sequences (genes, proteins, genomes). The standard workflow includes multiple sequence alignment using MAFFT, robust maximum likelihood tree inference with IQ-TREE 2 and FastTree, and advanced visualization/manipulation using ETE3. This skill is essential for studies in viral phylodynamics, microbial genomics, protein family evolution, and molecular clock dating.

This guide details how to write advanced correlation searches using Splunk's Search Processing Language (SPL). It covers techniques like threshold-based detection, sequence analysis, and anomaly detection to identify sophisticated security threats (e.g., brute force, data exfiltration, lateral movement) in a Security Operations Center (SOC) environment. Mastery of SPL is essential for closing SIEM detection gaps and ensuring compliance.

This technique audits user interaction flows (like button clicks) to detect subtle bugs that static analysis often misses. It specifically tracks the full sequence of state changes, identifying instances where later actions unintentionally cancel, contradict, or leave the UI in an inconsistent state due to state store side effects or race conditions. Ideal for debugging complex state management architectures (Redux, Zustand).

This skill provides integration with the Adaptyv Bio Foundry API, enabling the automated design, submission, and analysis of protein experiments. Users can submit amino acid sequences for various high-throughput assays, including binding kinetics (BLI/SPR), thermostability, and expression yield. It guides the entire research workflow, from sequence input to final results retrieval, accelerating biopharma discovery.

Biopython is a robust, comprehensive toolkit for computational molecular biology written in Python. It enables users to manipulate biological sequences (DNA, RNA, protein), parse standard formats (FASTA, GenBank, PDB, etc.), and programmatically access major bioinformatics databases like NCBI via Entrez. This skill is ideal for developing complex bioinformatics pipelines, including sequence alignment, structural analysis, and phylogenetic tree construction.

A comprehensive Python package providing a unified interface to over 40 major bioinformatics web services and databases. Use it for complex biological workflows, including cross-database querying (e.g., UniProt, KEGG, ChEMBL), identifier mapping, protein sequence retrieval, pathway analysis, and running sequence similarity searches like BLAST. It streamlines data integration from multiple life science resources into consistent Python code.

The ESM skill provides comprehensive tools for computational biology, leveraging ESM3 and ESM-C models. It enables sophisticated protein sequence generation, structure prediction (sequence to 3D structure), inverse folding (structure to sequence design), and generating function-conditioned proteins. Use it for de novo protein design, feature embedding, and advanced structural analysis in bioinformatics workflows.

gget is a comprehensive command-line tool and Python package offering unified access to over 20 genomic databases. It facilitates quick lookups for gene information, sequence analysis (BLAST), protein structures, and expression data, supporting both interactive CLI use and advanced programmatic Python workflows for biological research.