Skill UI

Conduct comprehensive, systematic literature reviews across biomedical, scientific, and technical domains. This skill facilitates meta-analyses, scoping reviews, and research syntheses by searching multiple academic databases (e.g., PubMed, arXiv). It generates professionally formatted reports (Markdown/PDF) with verified citations and mandates the inclusion of AI-generated scientific schematics (e.g., PRISMA flow diagrams). Ideal for academic research and thesis writing.

This skill transforms an LLM into a disciplined wiki maintainer, enabling the creation of a persistent, compounding personal knowledge base (Second Brain) within Obsidian. Unlike standard RAG workflows, which retrieve and synthesize information at query time, this system actively ingests sources, automatically updates entity pages, maintains cross-references, and continually synthesizes knowledge. Ideal for deep research, personal journaling, or building comprehensive business wikis over time.

A powerful command-line interface (CLI) tool that connects to the MiniMax AI platform. It allows users to generate and manage various forms of media content, including text chat, images, videos, speech synthesis, music generation, and performing real-time web searches, all directly from the terminal. Ideal for developers, researchers, and content creators who need automated, programmatic access to advanced generative AI capabilities.

A comprehensive methodology for discovering potential software vulnerabilities. It outlines advanced techniques including static analysis, dynamic analysis, fuzzing, taint tracking, and modern attack surface mapping (e.g., kernel, drivers). Ideal for professional code audits, bug bounty hunting, and building robust vulnerability research pipelines.

This skill guides the comprehensive process of crash triage, enabling the assessment of vulnerability exploitability. It covers advanced techniques using debuggers (WinDbg/GDB), sanitizers (ASAN/MSAN), and interpreting low-level data like stack traces and register dumps. It is essential for vulnerability researchers analyzing crash dumps or fuzzer-generated failures to identify root causes and potential attack vectors.

This is a detailed offensive checklist for identifying and exploiting insecure deserialization vulnerabilities across multiple programming languages (Java, Python, PHP, .NET, Node.js, etc.). It covers techniques like gadget chain generation, magic method abuse, type confusion, and modern attack vectors, providing a deep methodology for penetration testing and vulnerability research.

This comprehensive checklist provides a deep dive into Endpoint Detection and Response (EDR) architecture and monitoring mechanisms. It details advanced evasion techniques, such as direct syscalls, AMSI bypass, kernel patching, and memory manipulation. This skill is essential for red team engagements, penetration testing, and advanced malware research to thoroughly assess and bypass modern security defenses.

This comprehensive curriculum provides a detailed roadmap for mastering exploit development and vulnerability research. It covers fundamental techniques like fuzzy testing using AFL++, and progresses through advanced topics such as in-process fuzzing with Google FuzzTest. It is ideal for structuring professional security training programs or onboarding new research engineers.

A comprehensive guide detailing advanced offensive fuzzing methodologies. It covers the full lifecycle from target identification (parsers, network protocols, kernels) to tool selection (AFL++, libFuzzer, Honggfuzz, syzkaller), building harnesses, curating seed corpora, executing fuzz campaigns, and finally, performing crash triage and vulnerability analysis. Essential for security researchers and embedded systems developers.

This skill provides a deep dive into modern Windows exploit mitigations, including ASLR, DEP/NX, CFG, and CET. It covers how these core protections work, techniques for detecting them, and advanced methodologies for analyzing bypass strategies. It is essential reading for security researchers and penetration testers planning advanced exploitation chains against modern operating systems.

This technique guides users through a rigorous two-phase research strategy. First, conduct a broad search to identify potential papers or authors. Crucially, the system instructs the user to use the extracted "author full name" as a highly specific anchor in subsequent queries. Combining the author's name with details like journal, institution, year, or biographical information ensures the most precise and reliable results, significantly narrowing down the search scope and achieving deep academic insights.

This advanced skill is an end-to-end tool for transforming complex research topics into professional, visualized knowledge graph PDFs. It automatically conducts multi-round web searches, extracts key entities, structures related knowledge, and designs the optimal visualization (supporting Graphviz, PlantUML, etc.). Ideal for deep academic analysis, mapping character relationships, or visualizing complex technical architectures where existing structured data is unavailable.