Skill UI

Comprehensive guidance on using Shodan’s web UI, CLI, and API for reconnaissance, exposed-service discovery, screenshot capture, and exporting JSON/CSV data during penetration tests.

Access the ClinicalTrials.gov API v2 to search trials by condition, drug, location, sponsor or status, fetch details via NCT ID, and export JSON/CSV data for research analysis, patient matching, and trial monitoring.

FlowIO reads and writes Flow Cytometry Standard (FCS) files, exposing metadata, channels, and NumPy event arrays while allowing CSV/DataFrame conversion, making it ideal for cytometry pipelines and backend preprocessing services.

Scanpy is a scalable Python toolkit for single-cell RNA-seq analyses, covering QC, normalization, dimensionality reduction, clustering, marker discovery, annotation, and publication-ready visualization across h5ad/10X/CSV datasets.

Vaex is a high-performance Python library for lazy out-of-core DataFrames that process billions of rows without RAM. Use it to analyze massive CSV/HDF5/Arrow/Parquet tables, compute fast statistics, visualize big data, and build scikit-learn pipelines.

Helps craft precise ir.model.access.csv lines and ir.rule record rules for Odoo, debug access denials, and enforce scoped or multi-company visibility for modules.

This skill integrates multiple digital health sources (such as Apple Health, Fitbit, Oura, and CSV/JSON files) into a unified system. It processes, standardizes, and validates diverse health data formats, and connects this data to a dedicated knowledge base (WellAlly.tech). It provides intelligent recommendations and article retrieval based on the user's current health context and needs.

Aggregates official auctioneer information from all 27 Brazilian Commercial Boards into a SQLite store, exposes a FastAPI REST interface, and enables CSV/JSON exports plus customizable scraping per state.

Intelligent multi-strategy web scraper that selects between static WebFetch, browser automation, curl/bash, and WebSearch paths to extract structured tables, lists, pricing, and other data, with pagination handling, validation confidence, transforms, and CSV/JSON output for monitoring workflows.

This tool analyzes ML experiment results from various paths (JSON/CSV). It computes comprehensive statistics, builds detailed comparison tables based on model types and hyperparameters, and generates actionable insights. Use it when you need to interpret raw experimental data, compare different model runs, or determine the next steps for research.

Timesketch is a collaborative, open-source platform for security teams to analyze and reconstruct complex forensic timelines. It ingests and normalizes multi-source security data (logs, artifacts) using methods like Plaso, CSV, and JSONL. Users can visualize event chronology, track attack chains, and utilize advanced built-in analyzers (e.g., Sigma, Chain of Events) for comprehensive incident investigation and documentation.

This guide details how to build automated threat intelligence enrichment pipelines within Splunk Enterprise Security. By leveraging the Threat Intelligence Framework, users can ingest, normalize, and correlate Indicators of Compromise (IOCs) from diverse external sources (such as TAXII, CSV, and custom APIs). The process uses KV Store collections and lookup searches to enrich raw security events with critical threat context, significantly reducing triage time for SOC teams.