Skill UI

This comprehensive guide outlines an opinionated set of conventions for building robust Ruby on Rails applications. It covers core architectural principles, including rich models, state-as-records, minimal dependencies, and best practices for CRUD operations and testing. It is mandatory to consult these guidelines whenever designing, writing, reviewing, or refactoring any Rails code.

A comprehensive skill implementing the GTD weekly review process. It guides users through three deterministic phases (Get Clear, Get Current, Get Creative) to audit open loops, check project commitments, and ensure the personal system remains trustworthy. It helps users close open loops, audit stalled projects, and maintain a reliable organizational workflow.

This skill provides a robust framework for self-certifying task delivery. It guides developers through discovering a formal "verify plan" and capturing concrete evidence—such as screenshots, DOM snapshots, or CLI output—across defined surfaces (Web, CLI, Electron). The process ensures that task delivery is judged on demonstrable, reproducible proof, eliminating reliance on mere textual claims.

A comprehensive guide for configuring and deploying the RuView wireless sensing system. It covers firmware build-time settings (sdkconfig), runtime parameters (NVS provisioning), multi-node mesh setup, and integrating advanced edge intelligence modules (ADR-041). Essential for tuning system behavior and capabilities without modifying core code.

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.

A comprehensive guide detailing the entire model lifecycle for RuView. It supports multiple advanced tracking methods including camera-free pose estimation (WiFlow), camera-supervised methods using MediaPipe, robust contrastive embeddings (RuVector), and domain generalization (MERIDIAN). Covers training, evaluation, and deployment across local GPU and cloud platforms.

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 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.