القائمة
جمع SkillsMP عدد ٥٣ من skills من ruvnet/RuView. افتح أي skill لمراجعة مصدره وتفاصيله.
انسخ هذا الطلب إلى المساعد الذكي الذي تستخدمه.
Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/ruvnet/RuView.عرض ٤٠ من أصل ٥٣ skills مجمعة.
Reach RuView sensing hardware from the machine it is attached to — ESP32 CSI nodes (serial + UDP stream), 60 GHz MR60BHA2 / 24 GHz LD2410 mmWave radars, RPLIDAR and iPhone LiDAR — and from other machines over SSH, read-only.
لغة النص الأصلي: الإنجليزية
Build, flash, and provision an ESP32-S3/C6 CSI node for RuView — firmware variant choice, cross-platform checksum-verified esptool flashing, NVS/WiFi/channel/MAC-filter overrides, boot-log evidence.
لغة النص الأصلي: الإنجليزية
Train/evaluate WiFi pose models honestly — camera-supervised (MediaPipe + CSI) and camera-free (WiFlow), always checked against the mean-pose baseline before any PCK is quoted.
لغة النص الأصلي: الإنجليزية
Evolve this harness with Darwin Mode — frozen model, evolving harness (real, sandboxed, safety-gated).
لغة النص الأصلي: الإنجليزية
Turn a feature request into a minimal, file-level implementation plan before any code.
لغة النص الأصلي: الإنجليزية
Map a Homecore capability to reviewed source, tests, ADRs, and limitations.
لغة النص الأصلي: الإنجليزية
Review Home Assistant migration as untrusted versioned input and no-clobber output.
لغة النص الأصلي: الإنجليزية
Review Homecore server startup, restore, authentication, feature, and provider configuration.
لغة النص الأصلي: الإنجليزية
Review native registration or external Wasm plugin trust boundaries.
لغة النص الأصلي: الإنجليزية
Run the smallest relevant core, Wasmtime, HAP, or full Homecore test profile.
لغة النص الأصلي: الإنجليزية
ESP32-S3 / ESP32-C6 firmware build, flash, WiFi provisioning, and serial monitoring for RuView CSI sensing nodes. Use when setting up physical hardware, reflashing a node, or debugging a device that isn't streaming CSI.
لغة النص الأصلي: الإنجليزية
Run the ADR-151 per-room calibration pipeline — baseline → enroll → extract → train → a bank of small specialists (presence/posture/breathing/heartbeat/restlessness/anomaly).
لغة النص الأصلي: الإنجليزية
Zero-to-sensing path picker for RuView (WiFi-DensePose) — pick docker-demo, repo-build, or live-esp32 and run the next concrete step.
لغة النص الأصلي: الإنجليزية
Prove a RuView result is real — run the deterministic SHA-256 proof and the witness bundle (ADR-028), and lint any claim for MEASURED-vs-CLAIMED honesty.
لغة النص الأصلي: الإنجليزية
Explore and prototype rvAgent + RVF integration for RuView agentic flows. Use when working on cross-cog coordination, operator-facing agents reading BFLD / pose / vitals events live, or persisting agent state alongside sensing data in the same RVF container.
لغة النص الأصلي: الإنجليزية
Advanced RuView capabilities — RuvSense multistatic sensing (attention-weighted fusion, geometric diversity, persistent field model), cross-viewpoint fusion across multiple nodes, RF tomography (ISTA L1 solver, voxel grids), longitudinal biomechanics drift,…
لغة النص الأصلي: الإنجليزية
Run RuView sensing applications — presence/occupancy, breathing & heart rate, activity & fall detection, 17-keypoint pose estimation (WiFlow), sleep monitoring & apnea screening, environment mapping, Mass Casualty Assessment (MAT), and the 3D point-cloud…
لغة النص الأصلي: الإنجليزية
Use the RuView `wifi-densepose` CLI binary (incl. MAT scan/status/zones/survivors/alerts/export subcommands), the REST API (`wifi-densepose-api`, Axum), and the browser/WASM build (`wifi-densepose-wasm`, `wifi-densepose-wasm-edge`). Use when integrating…
لغة النص الأصلي: الإنجليزية
Configure RuView — ESP32 sdkconfig variants, NVS provisioning, WiFi channel / MAC filter overrides (ADR-060), edge intelligence modules (ADR-041), sensing-server flags, multi-node mesh, and Cognitum Seed integration. Use when adjusting how a deployed RuView…
لغة النص الأصلي: الإنجليزية
Set up and run RuView mmWave / FMCW radar sensing — ESP32-C6 + Seeed MR60BHA2 (60 GHz, heart rate / breathing rate / presence) and HLK-LD2410 (24 GHz, presence + distance), plus mmWave↔WiFi-CSI sensor fusion (48-byte fused vitals, MR60BHA2/LD2410 auto-detect,…
لغة النص الأصلي: الإنجليزية
Train RuView models — camera-free WiFlow pose (10 sensor signals, no labels), camera-supervised pose (MediaPipe + ESP32 CSI → 92.9% PCK@20, ADR-079), RuVector contrastive embeddings (AETHER, ADR-024), domain generalization (MERIDIAN, ADR-027), local SNN…
لغة النص الأصلي: الإنجليزية
Onboarding and first-run for RuView (WiFi-DensePose) — Docker demo with simulated data, repo build, and the fastest path to a live sensing dashboard. Use when someone is new to RuView or wants the shortest path to "it works on my machine".
لغة النص الأصلي: الإنجليزية
Verify a RuView build — full Rust workspace tests, the deterministic Python pipeline proof (SHA-256 Trust Kill Switch), firmware hash manifest, and the ADR-028 witness bundle with one-command self-verification. Use after any significant change, before merging…
لغة النص الأصلي: الإنجليزية
Web browser automation with AI-optimized snapshots for claude-flow agents
لغة النص الأصلي: الإنجليزية
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
لغة النص الأصلي: الإنجليزية
Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.
لغة النص الأصلي: الإنجليزية
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector…
لغة النص الأصلي: الإنجليزية
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through…
لغة النص الأصلي: الإنجليزية
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
لغة النص الأصلي: الإنجليزية
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
لغة النص الأصلي: الإنجليزية
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
لغة النص الأصلي: الإنجليزية
Comprehensive GitHub code review with AI-powered swarm coordination
لغة النص الأصلي: الإنجليزية
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
لغة النص الأصلي: الإنجليزية
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
لغة النص الأصلي: الإنجليزية
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
لغة النص الأصلي: الإنجليزية
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
لغة النص الأصلي: الإنجليزية
Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced…
لغة النص الأصلي: الإنجليزية
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code…
لغة النص الأصلي: الإنجليزية
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or…
لغة النص الأصلي: الإنجليزية
Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills…
لغة النص الأصلي: الإنجليزية