Skill UI

This comprehensive guide outlines the requirements for submitting computational artifacts for post-acceptance evaluation at PPoPP. It details PPoPP's unique badge policy (Functional, Reusable, Results Reproduced), addresses the challenges of ensuring results reproduce across different hardware architectures, and provides a detailed packaging plan, including containerization, README structure, and provenance documentation for maximizing reproducibility.

This skill guides the execution and stress-testing of empirical analysis for innovation studies (Research Policy). It details how to build reproducible bibliometric and patent variables, select appropriate econometric models (like Poisson/Negative Binomial for counts), and establish robust evidence. The focus is on addressing methodological challenges, ensuring transparent variable construction, and performing rigorous sensitivity checks to withstand expert scrutiny.

This comprehensive guide outlines best practices for creating and submitting supplementary materials for top-tier academic conferences. It addresses the critical challenges of maintaining strict anonymity, adhering to page limits, and structuring extended proofs, code links, and datasets across multi-round, double-anonymous review cycles.

This comprehensive guide helps researchers determine if their academic research question aligns with the scope and criteria of top-tier strategic management journals (e.g., SMJ). It provides a multi-part fit test covering strategic DNA, unit of analysis (firm-level), theoretical stakes, and empirical identification challenges. It guides authors on sharpening their questions and choosing the correct specialized journal (SMJ, SEJ, GSJ).

A comprehensive methodology for rigorous scientific research in operating systems and complex systems. This guide details how to pin environments (OS, firmware, hardware), automate data capture, and script all figures to ensure that experimental results are auditable and fully reproducible, protecting findings against review challenges.

A comprehensive guide for preparing replication and transparency packages for World Development manuscripts. It provides checklists and best practices for both quantitative (code reproducibility, data provenance, de-identification) and qualitative (evidence-to-claim trail, methods appendix) research. It addresses ethical constraints and the unique challenges of double-anonymized review.

A comprehensive framework for ensuring reproducibility in Web Search and Data Mining (WSDM) research. It addresses unique challenges associated with behavioral data, covering data provenance, temporal splitting discipline, bias assumption reporting, statistical rigor (seeds, variance), and the 'honesty ladder' for non-reproducible results, helping researchers publish robust and verifiable work.

A specialized downstream skill for CTF-sandbox workflows. Used to analyze complex security challenges driven by AI agent interactions, prompt injection, or infrastructure vulnerabilities. Focuses on tracing control chains involving untrusted input, tool side effects, deployment drift, container runtime issues, and CI/CD supply chain provenance. Ideal for rigorous vulnerability assessment in modern, distributed systems.

A specialized downstream skill for complex CTF challenges, focusing on cryptographic analysis, steganography, and mobile system forensics. It guides the user through recovering complex data chains, such as decoding blobs, tracing cryptographic transforms (keys, IVs, nonces), inspecting hidden media payloads, and analyzing mobile trust boundaries (e.g., APK/IPA signing logic, local storage, SSL pinning). This skill is designed to be used only after a main sandbox orchestrator has established the operational context.

This specialized skill guides deep-dive analysis for binary-heavy challenges, including CTF, malware analysis, and advanced forensics. It covers reverse engineering binaries, unpacking samples, inspecting memory dumps, debugging crashes, and building exploit chains by correlating artifacts like files, memory, and network packets.

This advanced skill specializes in detecting and recovering hidden data (steganography) embedded within various media containers, including images, audio, video, and documents. It is crucial for forensic analysis and CTF challenges, allowing users to inspect metadata, LSBs, alpha/palette channels, and appended trailers to reconstruct hidden payloads without brute force.

A specialized, downstream skill designed for forensic analysis within a confined sandbox environment, particularly for CTF challenges. It guides the user to inspect the full stack behavior, including API interactions, server routing, browser state (cookies, local storage), and asynchronous worker processes. Use this skill to trace complex, end-to-end request flows, debug authentication/session leaks, or diagnose discrepancies between frontend UI and backend enforcement.