Skill UI

A comprehensive guide providing best practices for Git workflows, covering adaptation strategies for major Chinese platforms (Gitee, Coding.net, etc.), branch naming conventions, standardized commit messaging (Chinese Conventional Commits), and CI/CD integration across various domestic environments. Helps streamline development processes for Chinese teams.

This skill guides the management of CI/CD pipelines within KubeSphere DevOps. It utilizes Kubernetes Custom Resources (CRs) to define, trigger, and monitor complex build workflows, seamlessly integrating with Jenkins concepts in a cloud-native manner. Use it for automating build, test, and deployment processes for applications running on Kubernetes.

Expert technique for narrowing down Asian drama candidates by leveraging streaming platform and broadcast channel information. Use this when the query mentions services like Netflix, Viki, or Amazon Prime, combined with genre and year details. This method significantly increases search precision, especially when combining platform data with temporal or thematic keywords.

KubeSphere Core acts as the central operating system for cloud-native application management built on Kubernetes. It provides essential functions, including API aggregation, multi-cluster routing, and multi-tenant separation. It manages core resources and simplifies complex cloud-native deployment and operation tasks.

This comprehensive skill guides users through the entire lifecycle management of KubeSphere extensions. It covers extension discovery, dependency resolution, version verification, and executing controlled installations, upgrades, or uninstalls using the InstallPlan mechanism. It is essential for maintaining a stable and complex multi-component Kubernetes cluster environment.

This service provides a centralized, common API server backend for the entire KubeSphere WizTelemetry Observability Platform. It unifies backend functionalities for core observability components including Logging, Auditing, Events, Tracing, and Notifications, enabling global monitoring and streamlined platform management within Kubernetes environments. Use it when installing or configuring the core telemetry platform.

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.

Arboreto is a powerful Python library designed to infer Gene Regulatory Networks (GRNs) from various gene expression datasets, including bulk and single-cell RNA-seq. It employs scalable algorithms like GRNBoost2 and GENIE3 to identify critical transcription factor-target gene relationships. Featuring support for Dask distributed computing, Arboreto is optimized for large-scale, high-throughput transcriptomic analysis.

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.

DeepChem is a comprehensive Python library designed for applying machine learning to complex fields like chemistry, materials science, and biology. It enables users to perform molecular property prediction (e.g., ADMET, toxicity), train models using specialized graph neural networks (GNNs), and process diverse molecular formats (SMILES, SDF, FASTA). It provides extensive featurization options, making it foundational for drug discovery and computational chemistry research.

This skill provides programmatic access to the Cancer Dependency Map (DepMap), a comprehensive resource characterizing genetic dependencies in cancer cell lines. Use it to identify genes essential for specific cancer types, discover synthetic lethal interactions, and validate potential oncology drug targets using CRISPR and RNAi data.

ETE is a comprehensive toolkit for phylogenomic research, designed to handle and analyze hierarchical tree structures. It supports various tree formats (Newick, NHX) and provides advanced functionalities such as detecting evolutionary events (duplication/speciation), identifying orthologs/paralogs, integrating with NCBI taxonomy for lineage tracking, and generating publication-quality visualizations in PDF/SVG.