Skill UI

This guide provides comprehensive best practices for creating optimized, secure, and efficient multi-stage Dockerfiles. Learn how to separate build environments (builder stage) from minimal runtime environments, significantly reducing image size and attack surface. Topics covered include layer caching optimization, security hardening (non-root users), and using minimal base images for reproducible builds.

Provides systematic Power BI performance troubleshooting guidance covering model optimization, DAX design, report layout, and capacity diagnostics, plus tool-driven measurement tips for faster page loads, interactions, and query execution.

This skill aggregates and summarizes the latest news from multiple authoritative Chinese sources across various categories, including Politics, Finance, Society, World, Tech, Sports, and Entertainment. It utilizes web browsing tools to open specified URLs, take content snapshots, and extract key headlines and detailed summaries, providing the user with a concise, structured report.

This skill provides a comprehensive audit of user interfaces, evaluating screens against Nielsen's 10 Usability Heuristics and modern mobile UX best practices. It systematically checks for critical usability flaws, design inconsistencies, accessibility gaps, and potential dark patterns, ensuring the resulting product delivers a superior and intuitive user experience across all platforms.

Automates YouTube workflows through the Rube MCP/Composio toolkit, covering uploads, playlist management, content search, analytics, subscriptions, and comments while respecting tool schemas and quota-aware practices.

This guide details advanced techniques for searching cricket matches by leveraging precise numerical scoring data. Instead of broad terms, users should utilize specific details—such as team totals (e.g., 168/9), runs off balls, wickets taken, or over details—combined with the match type and year to create highly targeted search queries. This method significantly improves search accuracy and efficiency when researching sports statistics.

OpenSearch is a distributed search and analytics engine integrated into the KubeSphere WizTelemetry Observability Platform. It is crucial for storing, searching, and analyzing various types of observability data, including application logs, system events, audit records, and notification history. This guide covers installation, configuration, and operational best practices for managing the OpenSearch cluster within KubeSphere.

This advanced research technique is designed for deep dives into football topics. Instead of relying solely on the original query, it mandates tracking every discovered entity—such as player names, club names, or coaches—from search results. By treating these entities as new leads, the user must formulate follow-up searches using the discovered names and remaining constraints, ensuring nothing relevant is overlooked and building a comprehensive knowledge chain.

A comprehensive, adaptive mathematics tutor covering K-12 topics from arithmetic through calculus. This skill utilizes proven pedagogical strategies—such as Socratic questioning, CPA approach, and error analysis—to ensure students build deep mathematical understanding rather than just procedural fluency. It adapts to multiple global curricula (SAT, A-Level, Gaokao) and tracks progress to target weak spots.

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.

AnnData is a specialized Python package designed for managing and analyzing annotated matrices, particularly crucial in single-cell genomics and bioinformatics. It efficiently stores experimental measurements (X) alongside comprehensive metadata (obs, var, obsm, etc.). This skill allows users to read, write, subset, and concatenate large, complex datasets in formats like .h5ad and .zarr, making it essential for scRNA-seq analysis workflows and integration with the scverse ecosystem.

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.