Skill UI

This guide details the end-to-end process of conducting a sophisticated spearphishing simulation campaign, mirroring real red team adversary techniques. It covers initial OSINT research and pretext development, building weaponized payloads that bypass security controls, setting up robust email infrastructure (SPF/DKIM/DMARC), executing the campaign in waves, and performing detailed post-campaign metrics analysis for comprehensive security reporting.

This skill analyzes accumulated usage logs from a complex research harness (ARIS) to propose structural optimizations. It identifies areas for improvement in SKILL scripts, default parameters, workflow ordering, and reviewer prompts. It is designed to automate the meta-level engineering process, ensuring that system efficiency is continuously improved based on real-world usage data.

Provides comprehensive guidelines for authors submitting papers to Acta Automatica Sinica (AAS). It details how to organize and present anonymous, reproducible code, data, and experimental artifacts to enhance the credibility and rigor of research in control, automation, and pattern recognition, supporting the double-blind review process.

A comprehensive guide to help researchers determine if their Additive Manufacturing (AM) manuscript meets the high scientific rigor required by leading journals. It focuses on shifting the narrative from 'part printing' to process-structure-property relationships, process physics, and advanced qualification methods. This tool helps authors refine their work for optimal journal targeting and submission readiness.

A comprehensive guide for researchers in electronics and signal processing preparing submissions to Acta Electronica Sinica (AES). It outlines best practices for proactively structuring, documenting, and disclosing research artifacts—including code, datasets, and hardware designs—to maximize the paper's credibility and chances of acceptance, even without mandatory journal badges. Covers anonymization, reproducibility standards, and proper disclosure in the manuscript.

This guide provides comprehensive best practices for ensuring scientific reproducibility in technical papers, particularly for electronics and information processing fields. It covers the critical pillars of documentation: environment setup, data sourcing and preprocessing, full algorithmic disclosure (including pseudo-code and hyperparameters), and robust statistical evaluation. By adopting these standards, authors can transform their work from potentially unverifiable results into credible, verifiable scientific contributions suitable for top-tier journals.

This guide outlines the process for converting accepted academic papers into optional ACM reproducibility badges. It walks authors through the rigorous evaluation cycle, covering everything from initial opt-in before submission to providing detailed one-page artifact descriptions. The goal is to prove that the research results are available, functionally sound, highly reusable, and accurately reproducible by independent evaluators.

This comprehensive guide details the academic review pipeline for CoNEXT conference submissions. It covers double-anonymous double-blind review, the two-round TPC process, and the critical nature of the one-shot "major revision," which functions similarly to a journal's revise-and-resubmit cycle. It provides authors with strategic insights to structure their research for rigorous academic scrutiny.

This comprehensive audit guide assists researchers in preparing papers for CoNEXT submission. It covers critical workflow stages, including choosing the correct submission cycle (December or June), adhering to ACM acmart formatting and strict page budgets, managing the two-step registration process, ensuring double-anonymous review compliance, and implementing essential security checks to prevent identity leaks in artifacts and metadata.

A detailed model of the ACM/IEEE Design Automation Conference (DAC) research manuscript review process. This guide explains the double-blind, TPC-driven, and single-shot nature of the evaluation, emphasizing the critical balance between genuine novelty and measured Quality-of-Results (QoR). It outlines the high standards for evidence fairness, benchmark credibility, and ablation studies required for acceptance, differentiating DAC's approach from architecture and software venues.

This guide meticulously models the rigorous decision-making machinery of top-tier academic conferences, using EuroSys as a detailed example. It covers the two-round submission cycle, the 'Accept/Revise/Reject' outcome logic, double-blind review mechanics, and critical criteria (like deployment plausibility and verifiable fairness) that determine a paper's success. Ideal for researchers and graduate students preparing systems research submissions.

A comprehensive guide for authors submitting to major signal processing conferences like ICASSP. It details how to audit, define, and precisely position a paper's novelty by comparing it against specific literature lanes (SPS journals, conferences, and ML venues). Learn to articulate the technical delta against the nearest work in a constrained, four-page format.