Skill UI

Configure automated Continuous Integration and Continuous Deployment (CI/CD) pipelines for Juicebox AI data analysis integrations. This setup utilizes GitHub Actions to run comprehensive unit tests (with mocked datasets) and integration tests (connecting to live APIs) on every PR and merge to main. It ensures that data upload logic, analysis execution, and result parsing workflows are robust and reliable before deployment.

This skill aggregates public sentiment and discussion about any given topic from the last 30 days. It pulls comprehensive data and engagement metrics from major sources including Reddit, X, YouTube, TikTok, Hacker News, and general web sources. It is invaluable for market research, competitive analysis, or understanding rapidly changing cultural and technological trends.

A toolkit for phylogenetic tree manipulation, event detection, NCBI taxonomy integration, and publication-quality visualization, streamlining phylogenomics workflows and gene family analysis.

NeuroKit2 is a Python biosignal processing toolkit for ECG, EEG, EDA, RSP, EMG, and EOG data that automates cleaning, feature extraction, and HRV/complexity analysis for psychophysiology, clinical, and HCI studies.

End-to-end Neuropixels recording analysis covering SpikeGLX/OpenEphys/NWB loading, preprocessing, motion correction, Kilosort4 sorting, quality metrics, Allen/IBL curation, and AI-assisted visualization for extracellular electrophysiology.

Query the Reactome Content and Analysis Services (or the reactome2py client) to fetch pathway hierarchies, map genes, run overrepresentation/expression analyses, and explore disease interactions for systems biology research.

Query the STRING REST API to retrieve protein-protein interaction networks, map identifiers, visualize evidence-weighted edges, and run GO/KEGG/Pfam enrichment for systems biology analysis.

GeoMaster is a comprehensive geospatial science skill that guides remote sensing, GIS, spatial analysis, and machine learning workflows for Earth observation and planetary data projects, covering satellite imagery, vector/raster math, point clouds, terrain, hydrology, and cloud-native data stacks.

Run OpenMM-powered molecular dynamics simulations and MDAnalysis trajectory workflows to build protein or small-molecule systems, minimize energy, equilibrate conditions, and characterize RMSD/RMSF, contacts, and free-energy surfaces for structural biology or drug studies.

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 tool parses API Gateway access logs from various providers (AWS, Kong, Nginx). It performs statistical analysis using pandas to detect critical security threats such as Broken Object Level Authorization (BOLA/IDOR), credential stuffing, rate limit bypass attempts, and injection vulnerabilities. Ideal for SOC analysts or security engineers investigating API abuse and building advanced threat detection rules.

This skill provides a systematic framework for analyzing cyber campaign attribution. It involves collecting, weighting, and correlating diverse indicators—such as infrastructure overlaps, TTP consistency, malware code similarities, and operational patterns—to determine the responsible threat actor. Utilizing structured methodologies like Analysis of Competing Hypotheses (ACH) and the Diamond Model, users can build confidence-weighted assessments to enhance threat intelligence accuracy.