Skill UI

This skill demonstrates how to use Trivy, an open-source security scanner, to perform comprehensive container security assessments. It scans container images, Kubernetes manifests, and Infrastructure as Code (IaC) files for vulnerabilities, misconfigurations, exposed secrets, and license compliance issues. Key features include generating Software Bill of Materials (SBOM) for supply chain transparency and integrating scanning gates into CI/CD pipelines, supporting robust DevSecOps practices.

This comprehensive guide details a multi-step workflow for detecting and extracting covert data hidden within images, audio, and video files. It covers initial metadata analysis, running advanced steganalysis tools (like zsteg, binwalk, stegoveritas), and performing low-level analysis such as Least Significant Bit (LSB) analysis to uncover hidden communication channels used in digital forensics and cybersecurity investigations.

Grype is an open-source vulnerability scanner from Anchore. It inspects container images, filesystems, and SBOMs for known CVEs. It leverages Syft-generated SBOMs to match packages against multiple vulnerability databases (NVD, GitHub Advisories). Use it for security assessments, auditing, and integrating into CI/CD pipelines to enforce vulnerability standards and manage supply chain risks.

Use Trivy to automate comprehensive vulnerability detection (CVEs, misconfigurations) in Docker container images within CI/CD pipelines. This skill guides users on establishing robust quality gates—such as integrating into GitHub Actions or GitLab CI—to ensure that only secure images are pushed to production registries, covering OS packages, dependencies, and Dockerfile best practices.

Accelerates CPU-bound Python workflows by translating NumPy, pandas, ML, graph, image, simulation, and IO code into NVIDIA GPU kernels using CuPy, Numba CUDA, Warp, cuDF/cuML/cuGraph, KvikIO, cuSpatial, and RAFT for dramatic speedups.

This skill guides developers on integrating Firebase AI (Gemini) into Flutter applications. It covers essential topics including initial setup and configuration, generating text and managing multi-turn chat responses, implementing real-time streaming output, handling multimodal prompts (text and images), and ensuring robust error handling, security, and adherence to data privacy best practices.

This skill provides comprehensive functionality for reading, creating, editing, and downloading content from Lark Feishu Docs (Docx/Wiki). Whether accessing via URL or token, it supports structured content manipulation using both XML and Markdown formats (v2 API). Use it for fetching document details, updating specific blocks, and managing embedded media and resources like whiteboards and images. Note that it requires prerequisite knowledge for advanced operations.

This guide details the functionalities for interacting with Lark Instant Messaging (IM). It covers core concepts like message types, threads, reactions, and flags, and provides methods for managing chat history, creating/managing groups, and handling various message resources (images, files, videos). It is essential for applications needing robust chat communication capabilities.

A powerful tool for managing whiteboard content embedded in Lark cloud documents. It allows users to query the board, exporting content as a preview image, retrieving raw node structures, or updating the board using various formats (Mermaid, PlantUML). Ideal for generating, viewing, or modifying complex diagrams like architecture diagrams and flowcharts.

A powerful tool that converts complex Unified Modeling Language (UML) diagrams—such as Sequence, Class, Activity, and State diagrams—into plain text ASCII art. This is crucial for documentation in environments that do not support image embedding, such as terminal sessions, README files, or Git commit messages. Supports both standard ASCII and enhanced Unicode ASCII formats for better visual fidelity.

Process and resize images using ImageMagick across Windows, Linux, and macOS, including metadata inspection, format conversion, thumbnail creation, and batch workflows for wallpapers or mass photo adjustments.

Guides adding GraalVM native image support to Java apps by detecting Maven or Gradle frameworks, injecting native build plugins, configuring reflection/resource/JNI/proxy files, iterating builds per Oracle best practices, and validating the native executable.