Skill UI

Provides comprehensive configuration management for local LLM inference using RuVLLM. Users can select models, perform task-specific fine-tuning with MicroLoRA adapters, or implement continuous, real-time adaptation using SONA. This tool guides the entire advanced LLM workflow, covering status checks, configuration generation, and advanced adaptation loops.

This tool manages the lifecycle of learned intelligence patterns, implementing the crucial DISTILL and CONSOLIDATE phases of the 4-step intelligence pipeline. It enables the capture of successful task knowledge, supports multi-domain adaptation via SONA or MicroLoRA, and consolidates learned patterns into long-term storage to prevent catastrophic forgetting.

A comprehensive tool for aggregating and displaying system metrics (counters, gauges, histograms) from the observability namespace. It computes baselines and flags anomalies by detecting deviations exceeding standard deviations, providing a clear snapshot of system health, error rates, and performance degradation trends.

A comprehensive guide to writing robust, efficient, and maintainable Python applications. Covers core principles like readability, explicit coding, and EAFP (Easier to Ask Forgiveness than Permission), advanced features like modern type hinting, context managers, and sophisticated exception handling techniques.

A comprehensive guide detailing advanced performance optimization patterns for React 18/19 and Next.js. Adapted from Vercel Engineering's best practices, this skill organizes 70+ critical rules across eight categories—including eliminating waterfalls, optimizing bundle size, improving server-side rendering, and managing client-side re-renders. Use this when developing, reviewing, or refactoring high-performance React applications.

This tool manages RVF (Ruflo Vector Format) files, providing comprehensive functions for handling, transferring, and backing up agent memories. It supports listing, exporting, importing, migrating, and generating statistics for complex vector embeddings and associated metadata, ensuring knowledge portability across different projects and platforms.

This helper tool is designed to assist with a wide variety of tasks and needs. It encourages users to use their own judgment and judgment to handle diverse prompts, making it a flexible and adaptable resource for general problem-solving scenarios. Ideal for brainstorming, general queries, and initial exploration.

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.

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 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.

Provides advanced strategies for optimizing content and brand presence for generative AI search platforms (AEO/GEO). Covers AI Visibility, Citation Tracking, Entity Consistency, and Knowledge Graph optimization across tools like ChatGPT, Gemini, and Google AI Overviews. Essential for brands adapting to modern AI search experiences.

Tool to embed C2PA (Content Provenance) manifests into AI-generated multimedia assets (image, video, audio, PDF). This mechanism adds a machine-readable provenance trail detailing the generator, prompt, and review history. Essential for complying with global regulations like the EU AI Act Article 50, ensuring verifiable digital authenticity, and building brand trust.