Skill UI

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.

A comprehensive guide for designing and presenting rigorous experiments and simulations for top-tier journals in Control Theory, Robotics, and Smart Systems. Covers RQ-driven design, establishing fair baselines, providing theoretical proofs of stability/convergence, performing ablation studies, and ensuring statistical significance, helping authors build an undeniable evidence chain for double-blind external review.

Provides comprehensive guidelines for achieving scientific reproducibility in academic research, particularly for control systems, automation, and pattern recognition. It covers fixing environment dependencies, data handling, random seeds, and process pipelines, helping authors withstand rigorous peer review questioning and build verifiable research artifacts.

This guide outlines the stringent reproducibility and data requirements for submitting manuscripts to Agricultural Systems (AgSy). Because AgSy treats code, models, and algorithms as research data, authors must learn how to deposit all materials in a recognized repository (e.g., Zenodo, OSF), cite them permanently, and document the model structure, parameters, and versions. It provides a checklist for building a reproducible research workflow.

A comprehensive guide for authors developing systems papers for major conferences (like ATC). It details how to build a reproducible story by pinning all environments (hardware, OS, toolchain, workload, code), providing turnkey one-command execution paths, and preparing a runnable, anonymized artifact package for academic review and evaluation.

This skill offers two complementary workflows for locally checked-out codebases. Documentation mode creates a definitive, cited architecture document ideal for onboarding and system research. Modernization mode then builds upon this documentation, generating a phased, safety-laddered plan to upgrade, migrate, or rewrite legacy systems. It emphasizes local-first analysis for maximum accuracy.

A comprehensive guide for drafting and revising top-tier systems papers, specifically for conferences like EuroSys. It details the required academic structure, including building the problem-to-mechanism arc, managing the 12-page technical budget, writing rigorous evaluation sections (including measuring failure cases), and maintaining the necessary double-blind academic voice.

This guide helps researchers determine the most appropriate conference venue (e.g., HPCA, ISCA, MICRO, ASPLOS) for their microarchitecture or systems research paper. It outlines key criteria, such as whether the contribution is a measured microarchitectural cost, a buildable mechanism, or a measurable characterization, and how to strategically route the project based on its novelty and evidence.

This guide helps authors structure the Related Work section for top-tier academic journals like the Journal of Software. It focuses on demonstrating incremental contribution (delta-first positioning), structuring the review across multiple software disciplines (e.g., SE, Systems, Databases), ensuring balanced citations (international vs. domestic), and building comprehensive classification frameworks for review papers.

This skill provides a comprehensive guide for authors targeting the USENIX Symposium on Operating Systems Design and Implementation (OSDI). It helps in positioning complex systems research, covering core scope areas like operating systems, distributed systems, and cloud infrastructure. It details how to frame the contribution, build evidence (artifacts, baselines), and distinguish the work from similar top-tier venues like SOSP and NSDI.

Converts raw OpenMed NER outputs (text spans) into structured, standards-compliant FHIR R4 resources (e.g., Condition, Observation, MedicationStatement). It provides mechanical helpers for building CodeableConcepts using major coding systems like SNOMED, LOINC, and ICD-10, ensuring high interoperability with EHR systems and registries.