Skill UI

A comprehensive guide for authors targeting the IEEE CASE conference. This tool helps assess manuscript fit by focusing on automation science, manufacturing, logistics, and cyber-physical systems. It guides authors on how to re-frame algorithmic designs with practical operational evidence, structure the contribution, and anticipate reviewer expectations for top-tier automation venues.

A specialized tool designed for researchers targeting the International Journal of Plasticity (IJP). It guides authors on whether their manuscript—especially those related to plastic deformation—is a strong fit, focusing on the necessity of developing a rigorous, constitutive model and validating it against experimental data. Use this skill to re-frame observational studies into impactful theoretical contributions.

A comprehensive guide for designing, auditing, and reporting reliable robotic experiments, particularly for major conferences like IROS. It moves beyond simple success rates, detailing how to map every claim to verifiable evidence (trials, simulations, field data). Key areas covered include defining pre-set success criteria, reporting failure taxonomies, ensuring fair baselines, and quantifying the critical sim-to-real gap using advanced small-n statistical methods.

A detailed guide on how to write a rigorous and comparative 'Related Work' section for top-tier microarchitecture conferences (e.g., MICRO). It teaches authors to structure the section as a 'mechanism taxonomy,' differentiating designs based on structural and cost differences rather than merely listing citations. Key areas covered include sweeping academic venues, integrating industry disclosures, and verifying all venue attributions using tools like dblp.

A comprehensive guide designed to help researchers determine the optimal top-tier conference venue for their computer architecture work. It provides detailed criteria—such as mechanism-residency tests, hardware cost analysis, and scope boundaries—to guide authors in correctly placing their research between venues like MICRO, ISCA, ASPLOS, and DAC.

This guide provides a comprehensive audit checklist for designing and evaluating sensor-based systems (SenSys). It mandates rigorous, real-world measurements across five core axes: energy efficiency, on-device latency distribution, ground truth accuracy, deployment realism, and embedded AI footprint. It ensures that research results are based on measured hardware performance, not simulations or idealized baselines.

This guide provides comprehensive best practices for designing and auditing cloud system evaluations, particularly for academic submissions. It mandates that claims must be supported by measured evidence from real or realistic deployments, moving beyond simple simulations. Key metrics emphasized include tail latency (p99), operational cost modeling, and verifiable behavior under scale and multi-tenancy.

A comprehensive guide for authors submitting to high-impact scientific journals. It outlines the essential principles for structuring experiments and presenting evidence, emphasizing claims-evidence matching, fair benchmarking, differentiating result sources (simulation, hardware, theory), and ensuring statistical rigor. Covers best practices across computer science, control, communication, and microelectronics.

A comprehensive guide for designing and presenting highly rigorous technical evaluations for database or system papers. It covers establishing baseline necessity, proving mechanism causality through ablation, testing scalability across data sizes, and mandating the disclosure of loss cases to satisfy skeptical academic reviewers.

This specialized skill is designed for advanced security analysis, tracing the complete trust chain from cloud metadata services to accepted privilege. It is used in penetration testing or CTF environments to meticulously prove how metadata-derived credentials (such as instance identities or tokens) are issued and subsequently accepted by a cloud or control plane API, thereby exposing the decisive trust edge.

This specialized skill is designed for deep forensic analysis in complex Windows environments, crucial for CTF and red teaming. It traces identity flows, including Active Directory (AD) origins, Kerberos ticket lifecycles, and OAuth authorization claims. Use it to correlate host artifacts (LSA, DPAPI, Sysmon) with identity evidence to map complete lateral movement and privilege escalation chains.

This skill is designed for deep security and behavioral analysis within the Kubernetes control plane. It specializes in tracing complex interactions, including RBAC edge cases, service-account trust paths, admission webhook behavior, resource mutation, and cluster-level state drift. Use it when diagnosing why live workloads differ from manifest declarations, or when investigating cluster-wide permission issues.