Skill UI

This tool generates a detailed, local 'receipt' or impact report of all Claude Code activity recorded in local session transcripts. It cross-references this data with your local Git history to provide a quantifiable measure of effort and project contribution. Ideal for performance reviews, budget justifications, or self-auditing usage.

This skill acts as an advanced orchestration protocol for reviewing GitHub pull requests. It is stack-agnostic, meaning it does not enforce its own rules. Instead, it dynamically discovers the project's existing standards—such as the test runner, architectural conventions, and requirement specifications—before running six specialized subagents in parallel. It provides a comprehensive, context-aware review and summary directly on GitHub.

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.

This skill summarizes user-provided input into one concise paragraph. It is specifically designed to enhance E2E (End-to-End) coverage testing within development environments, such as Agent Builders. The generated summary ensures comprehensive content representation and must include the E2E_SUMMARY_SKILL_PASS marker for validation.

A comprehensive suite for running advanced sensing applications using RuView hardware. It supports multi-modal data fusion from CSI, Wi-Fi, and mmWave sensors to perform critical tasks such as occupancy detection, vital sign monitoring (heart rate, breathing), pose estimation, environment mapping, and mass casualty assessment. Ideal for prototyping sophisticated IoT and smart building solutions.

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.

A comprehensive guide for bringing RuView CSI sensing nodes (ESP32-S3/C6) online. This skill covers the full lifecycle: building the embedded firmware, flashing the device, provisioning WiFi credentials, and confirming the Continuous Sensing Image (CSI) data stream. Essential for physical hardware deployment and debugging of complex sensing systems.

This tool provides the framework for setting up and running mmWave/FMCW radar (60 GHz, 24 GHz) alongside WiFi CSI. It performs advanced sensor fusion, reconciling radar-derived vitals (heart rate, breathing rate) with CSI data to generate unified 48-byte fused vital records. It is suitable for developing high-precision health monitoring systems and volumetric spatial models.

This guide provides a comprehensive onboarding process for RuView (WiFi-DensePose). It details three deployment tiers: Docker simulation for quick testing and UI exploration, source code build verification (Rust/Python), and live sensing setup utilizing ESP32 hardware. Ideal for new users or rapid prototyping.

This comprehensive tool provides a multi-stage verification pipeline for the RuView system. It executes full Rust workspace tests, runs a deterministic Python proof (Trust Kill Switch) to detect behavioral drift, and generates a detailed ADR-028 witness bundle. Use this before merging pull requests or when creating an official attestation package for recipients.

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.

This skilled searches GitHub Issues and Discussions to find prior reports, error matches, and compatibility clues for software debugging. It extracts details on exact errors, package versions, OS environments, and recommended workarounds. Use this workflow for diagnosis and discovery, not for academic citation. It guides structured queries to provide actionable debugging steps and compatibility summaries.