Skill UI

This tool generates sophisticated trading signals by leveraging an advanced anomaly detection engine. It scans financial assets for various market anomalies—such as spikes, drifts, and oscillations—and classifies them. It then integrates neural network prediction and searches historical pattern databases to output highly ranked, actionable trading signals, complete with confidence scores and target parameters.

Provides a structured workflow for systematically accessing and analyzing official intellectual property data from the USPTO. This skill covers patent search (PatentSearch API), trademark status checks (TSDR), ownership transfer tracking, and building reproducible IP landscape logs. It is designed for data collection and record verification, emphasizing the use of official APIs and rigorous logging practices. (Warning: Not for legal advice.)

This skill helps discover natural groupings within a large collection of semantic embeddings using the `ruvector` tool. It employs graph-based algorithms (Spectral/Louvain) to cluster code or data, revealing underlying themes, identifying outliers, and organizing vast vector sets. Ideal for analyzing codebases or large datasets to understand relationships between entries.

This skill utilizes hyperbolic space embedding (Poincare ball model) to represent complex data structures with inherent hierarchy, such as dependency trees, ontologies, or module taxonomies. Unlike standard Euclidean embeddings, hyperbolic space preserves hierarchical distances efficiently, allowing for accurate distance calculations (geodesic distance) that grow logarithmically with tree depth. It is ideal for advanced knowledge graph analysis and code architecture mapping.

This plugin provides advanced vector search capabilities using two distinct paths. The large-scale path supports millions of vectors via HNSW, ideal for general corpus search. The hot-path router handles small, critical pattern routing (≤11 patterns) with sub-ms latency. Key features include RaBitQ 1-bit quantization for memory efficiency (32× reduction), hyperbolic space search for hierarchical data, and unified cross-namespace search.

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.

A comprehensive set of programmatic interfaces for RuView's Wi-Fi sensing capabilities, including the CLI binary, REST API, and WebAssembly builds. This toolkit allows developers to integrate sophisticated disaster survivor detection and signal analysis into various environments, such as scripting, web browsers, and edge devices (ESP32-WASM3). Ideal for systems requiring cross-platform, scalable sensing data streams.

Generates comprehensive quality intelligence reports by analyzing historical evaluation scores. This tool tracks content performance over time, identifies improving or declining content types, detects significant quality regressions against baselines, and provides prioritized, actionable recommendations for improving brand quality across various content dimensions.

This tool performs deep, multi-touch attribution analysis to calculate comprehensive Return on Investment (ROI), Return on Ad Spend (ROAS), and Customer Acquisition Cost (CAC) across all marketing channels. It supports various attribution models (e.g., linear, time-decay) and projects long-term value using LTV, providing data for budget optimization, executive reporting, and identifying efficiency gaps.

Utilize Monte Carlo simulation to model complex marketing scenarios and predict revenue outcomes with quantified probability distributions. This tool is essential for assessing downside risk, understanding potential upside, and validating the probability of hitting specific revenue targets when testing budget shifts, channel mix changes, or new campaign launches.

This skill allows users to save structured marketing insights and learnings into a persistent intelligence graph. By capturing observations, context conditions (channel, audience, objective), and confidence levels, it builds compound intelligence. This process transforms one-off campaign findings into a consistent, queryable knowledge base that enhances all future marketing strategies and decision-making.

A comprehensive set of guidelines for generating maps, figures, and tables for academic journals. This guide emphasizes cartographic standards, statistical rigor, and maximizing the visual argument, ensuring that all exhibits are reproducible, legible in print, and adhere to strict word count limitations. It covers everything from projection choice and data normalization to model plot interpretation and handling spatial uncertainty.