Skill UI

An interactive tool designed to discover, select, and assemble specialized teams of AI agents. It supports structured agent collections across different domains (e.g., Engineering, Marketing). Users select multiple roles for a specific task, and the skill launches them in parallel, synthesizing their independent findings into a unified report, including consensus and conflict analysis.

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.

A utility designed to generate high-dimensional vector embeddings (384-dim) from various sources including text, code, or documents. This process converts raw data into numerical representations optimized for semantic search, similarity comparison, and clustering, utilizing ONNX and HNSW indexing for efficient retrieval.

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.

A sophisticated, multi-agent workflow designed for comprehensive code reviews of GitHub Pull Requests. It performs deep analysis by simulating multiple specialized perspectives, checking PR eligibility (handling draft/merged status and follow-ups), and managing large or complex diffs. The skill synthesizes high-signal, actionable feedback by integrating parallel reviewers' findings with historical PR discussions, ensuring robust code quality before merging.

This skill enforces rigorous meeting discipline through a four-stage workflow: Cost Gating, Timeboxed Agenda Building, Running the Meeting, and Action Item Extraction. It calculates meeting costs, ensures every agenda topic has a desired outcome, and converts raw notes into a structured, owner-assigned, due-dated checklist, flagging any missing owners or deadlines. Ideal for transforming unproductive meetings into actionable, accountable outcomes.

SkillOpt-Sleep enables an AI agent to undergo a simulated "sleep cycle" for continuous, measurable self-improvement. It harvests past sessions, mines recurring tasks, and re-runs them offline. It then consolidates findings into the agent's memory and skills, ensuring only validated improvements are adopted. This process maximizes long-term competence from short-term interactions.

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.

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.

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.

A comprehensive security auditing tool designed to analyze codebases for vulnerabilities. It provides a structured workflow to scan entire repositories, review specific changes (like PR diffs or single commits), and suggest verified patch files. Findings are challenged by independent agents, ensuring that suggested fixes are targeted and require manual review before application.

This dashboard provides a comprehensive, single-view operational picture of campaign health. It monitors active campaigns by showing real-time health scores, logging auto-corrections (e.g., bid adjustments, budget reallocation), displaying current guardrail rules, and identifying campaigns needing human attention. It quantifies the estimated savings achieved through automated optimizations, helping users trust the automated system while focusing strategic effort on critical issues.