Skill UI

BGPT Paper Search queries the remote MCP server to retrieve structured experimental data from full-text studies, returning methods, results, sample sizes, quality scores, and conclusions for efficient literature reviews and evidence synthesis.

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.

This comprehensive tool manages the complete lifecycle of ML experiments, providing robust deployment capabilities across diverse environments. It supports running training jobs on local GPUs, dedicated remote servers, Vast.ai, and serverless platforms like Modal. The workflow handles environment detection, code synchronization (rsync/git), dependency pinning, and integrates advanced logging tools (e.g., W&B), ensuring reliable, scalable, and reproducible ML training runs.

A powerful skill covering geospatial science, including GIS, remote sensing, spatial statistics, and machine learning for Earth observation. It supports processing of various data types (raster, vector, point cloud) from sources like Sentinel and Landsat, and integrates modern cloud-native workflows (STAC, COG). Ideal for environmental monitoring, urban planning, and advanced spatial modeling tasks.

Zarr is a robust Python library designed for efficiently storing and managing large N-dimensional arrays. It provides features like chunking, compression, and parallel I/O, making it perfectly suited for cloud-native scientific computing pipelines. It ensures seamless integration with major scientific stacks including NumPy, Dask, and Xarray, while supporting remote storage backends like S3 and GCS.

KAPE (Kroll Artifact Parser and Extractor) is a specialized, rapid triage tool for incident response. It collects specific, volatile forensic artifacts (like registry hives, event logs, and browser data) from compromised Windows systems. It is designed for remote, at-scale artifact collection when full disk imaging is impractical, enabling analysts to quickly build a defensible, parseable dataset for initial investigation and containment.

A comprehensive guide outlining rigorous data analysis and reporting standards for geographic manuscripts. It covers spatial statistics, remote sensing accuracy, and qualitative interpretation, emphasizing spatial honesty, quantifying uncertainty, and ensuring results are robust across different scales and units.

A comprehensive guide for strengthening the methodological design of advanced geographical manuscripts. It covers various paradigms including spatial/quantitative GIScience, remote sensing, qualitative human geography, and mixed methods. Key advice areas include rigorously addressing spatial dependence (MAUP), validating measurements, justifying case selection, and ensuring holistic integration of diverse data sources.

This skill scans a specified local directory, extracts essential metadata from the files, and builds a comprehensive, searchable index. It then securely uploads this generated index to a configured remote search service via HTTP, making local files discoverable across remote platforms.