Skill UI

A comprehensive guide for writing the evaluation section of a systems paper for top-tier conferences. It teaches authors how to map every technical claim to verifiable experiments, establish fair state-of-the-art baselines, utilize mixed workloads (microbenchmarks, E2E applications, and traces), and honestly report critical metrics like performance tails, variance, and overheads. The goal is to maximize credibility and withstand rigorous peer review.

This guide outlines the methodology for preparing research artifacts for rigorous academic reproducibility evaluations, such as those run by VLDB/SIGMOD. It details the required components—including prototype code, input data, workloads, and analysis scripts—to structure a comprehensive package. The goal is to ensure that any external evaluator can independently and flawlessly rebuild and validate all claimed results, maximizing the chances of winning reproducibility awards.

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 is designed for deep forensic analysis of compromised Linux environments, specifically tracing the sequence of credential usage (tokens, keys, service accounts) that leads to lateral movement or privilege escalation. It helps map the decisive path from a recovered artifact to an accepted replay mechanism, identifying the exact trust edge or capability abuse responsible for the host-to-host pivot.

A highly specialized, downstream skill for advanced threat analysis. This tool is used to recover hidden configurations, decode C2 (Command and Control) parameters, unpack staged payloads, and extract Indicators of Compromise (IOCs) from complex malware samples. It focuses on identifying the exact decode chains—including compression, encoding, and crypto steps—and linking recovered fields to observed behavioral outcomes within a sandbox environment.

This skill is designed for deep forensic analysis of asynchronous processing chains, specifically focusing on 'drift'—behavioral or configuration differences between a synchronous request path and subsequent worker-executed tasks. Use it to trace payloads, inspect worker-only state, follow retry mechanisms, handle dead-letter queues, or connect enqueued items to eventual side effects (e.g., file writes, cache updates, emails). It is a specialized downstream tool, requiring prior orchestration context.

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.

This skill converts free-text radiology narratives (CT, MRI, X-ray, etc.) into structured, machine-readable data. It automatically identifies and segments key report sections (Technique, Findings, Impression) and extracts critical clinical details such as anatomy, measurements, laterality, BI-RADS/Lung-RADS scores, and follow-up recommendations. It is crucial for building structured medical records and decision support systems.