Skill UI

This toolset allows users to save and restore complete agent sessions, ensuring context continuity across multiple conversations. It captures the agent's entire state, including memory, configuration, task progress, and learning metrics. Use it when pausing work and needing to resume later with full context, or for checkpointing long-running tasks.

A comprehensive guide to architectural patterns for building scalable, production-ready backend services using Java and Spring Boot. Covers essential topics including RESTful API design, layered architecture (Controller, Service, Repository), data persistence (JPA), caching, asynchronous processing, robust error handling, and middleware filtering.

This skill provides the creative direction layer for video production, focusing on *what* the content should feel like, not just *how* to render frames. It distills complex visual aesthetics (such as angelcore, cloud-trance, or hyperpop) into actionable mood, color palettes, and rhythmic editing grammars. Use it when building music videos, stylistic reels, or guiding AI b-roll generation that must maintain a unified, intentional visual narrative.

This skill executes comprehensive historical backtesting using the high-performance neural-trader engine. It supports features like walk-forward validation and captures key financial metrics (Sharpe, Drawdown). Critically, it signs the resulting artifact using Ed25519 cryptography, providing non-repudiable tamper evidence required for promoting research models to live trading systems.

This tool automates the process of optimizing investment portfolio allocations using a mean-variance engine. It integrates neural prediction models and risk constraints to determine optimal asset weights. Users can set specific risk targets, assess comprehensive risk metrics (variance, correlation), and generate actionable, step-by-step rebalancing plans for professional portfolio management.

Assess and manage investment risk using the neural-trader risk engine. This tool calculates critical metrics such as Value at Risk (VaR), Conditional VaR (CVaR), and Sharpe ratio for both single positions and entire portfolios. It also optimizes position sizing using methods like Kelly criterion and checks for market circuit breaker triggers (e.g., high correlation spikes or volatility regime shifts) to ensure robust trading decisions and minimize exposure.

This skill automates the comprehensive setup and bootstrapping of the ruvector framework. It ensures all necessary optional add-ons—including ONNX, Brain, and LLM components—are installed. Furthermore, it registers the required MCP server and runs a full battery of diagnostics to verify the entire toolchain is functional and ready for immediate use.

This skill executes a rigorous, deterministic integrity forensic audit using an external, pinned Anti-Autoresearch framework. It sweeps the submitted paper to detect potential inconsistencies, rule violations, and structural anomalies. The resulting verdict is converted into a typed policy gate (BLOCK/WARN/NO_NEW_BLOCKER) and an append-only obligations ledger, providing a final layer of assurance before submission or publication.

This tool provides a comprehensive overview of your project's memory usage across all associated memory systems. It reports metrics such as line counts, topic file counts, capacity limits, stale entries, and actionable recommendations to help maintain memory integrity and optimize performance.

This skill connects to the public, read-only AI HOT API to retrieve the latest Chinese AI news, curated selections, hot topics, and daily reports. It is essential for users needing up-to-date information on large language models, industry breakthroughs, or major AI events, ensuring results are based on real-time data rather than pre-trained knowledge.

A comprehensive framework for advanced sensing utilizing WiFi signals. It implements multistatic radar sensing, cross-viewpoint data fusion, RF tomography for volumetric imaging, and persistent field modeling. Features include pre-movement intention detection, biomechanics drift tracking, and robust mesh security hardening for research-grade deployments.

This guide outlines the essential CLI commands for managing the full task lifecycle within the LobeHub task system. It covers viewing task details, creating and managing subtasks with dependencies, handling task-related documents (workspace), and tracking conversational topics. Use `lh task` to ensure structured workflow execution and progress reporting.