Skill UI

This comprehensive tool automates the process of translating non-English official documents (images) for visa applications. It handles image preprocessing (conversion and rotation), performs robust OCR using multiple frameworks, translates the extracted text into professional English while maintaining document structure, and generates a certified bilingual PDF containing both the original image and the formatted translation.

PathML is a Python toolkit for computational pathology workflows, loading 160+ slide formats, preprocessing H&E images, constructing spatial graphs, training HoVer-Net/HACTNet models, and analyzing multiplex imaging for ML-ready pathology data.

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.

Perform comprehensive digital forensic analysis on raw (dd), E01, or AFF disk images using industry-standard tools like Autopsy and The Sleuth Kit. This process allows investigators to recover deleted files, examine file system metadata, search for specific keywords, and build detailed investigation timelines. It is essential for generating structured reports from digital evidence in legal and cybersecurity investigations.

A comprehensive toolset for digital forensics, designed to detect, extract, and analyze covert data hidden within images, audio, and video files. It utilizes advanced steganalysis techniques (LSB, DCT, frequency domain analysis) and specialized tools (StegDetect, zsteg, binwalk) to uncover hidden communications channels, making it crucial for investigations involving data exfiltration or insider threats.

A comprehensive guide and workflow for recovering deleted files (documents, images, videos, etc.) from damaged storage media, forensic disk images, or corrupted file systems. It utilizes PhotoRec's file signature-based carving engine, allowing data recovery regardless of file system damage. The process includes advanced steps for file validation, hashing, and organizing evidence for forensic analysis.

This skill provides a comprehensive workflow to transform raw data into professional visual charts. It intelligently analyzes data features (e.g., trends, comparisons, flows) to select the optimal chart type (line, bar, pie, etc.). Users provide data and specifications, and the skill generates a high-quality, detailed chart image using a structured JavaScript process.

This skill provides bounded, local exploratory data analysis for diverse scientific data files, including CSV, JSON, HDF5, and image metadata. It rigorously audits data structure, detects missing values, and identifies outliers in a secure, sandboxed environment. It is designed exclusively for pre-modeling data integrity checks and must not be used to infer scientific meaning or make causal claims.

Histolab is a specialized Python library for digital pathology designed to process Whole Slide Images (WSI). It automates critical steps including sophisticated tissue detection, customizable tile extraction (random, grid, score-based), and stain normalization. It is essential for preparing high-quality, structured datasets for deep learning model training and comprehensive quantitative whole slide analysis.

This skill functions as an expert GPU optimization engineer, transforming CPU-bound Python code into highly accelerated GPU kernels. It provides expertise across scientific computing, deep learning, and data analytics, covering core libraries like NumPy, pandas, and scikit-learn. Use cases include massive data parallelism, geospatial analysis, physics simulations, image processing, and advanced vector search on NVIDIA hardware.

PathML is a robust computational platform engineered for local, research-only workflows in computational pathology. It facilitates comprehensive analysis pipelines, including whole slide image (WSI) loading and tiling, preprocessing, quality control (QC), quantification of multiplex images, and the construction of spatial graphs. Designed with strict adherence to data privacy and research reproducibility, it supports advanced biological data analysis.

Utilizes the idc-index package to query and download large-scale, public cancer imaging datasets from the NCI Imaging Data Commons. This skill allows users to select image subsets based on diverse metadata (e.g., cancer type, modality, anatomical site) and download raw DICOM files for advanced AI training, medical research, and visualization. No authentication is required for data access.