Skill UI

A remote MCP server designed for AI agents to dynamically discover, inspect, and verify external tools, APIs, and services. It allows agents to search a curated index of AI-ready websites, check for machine-readable endpoints (like OpenAPI or MCP), and confirm if an endpoint responds correctly to JSON-RPC, enabling robust, dynamic agent workflow building.

This guide provides three fundamental examples for integrating with the Notion API. It demonstrates how to search for existing pages, create new content within a database, and retrieve the newly created page's metadata. Ideal for developers starting a new Notion integration or implementing basic automated workflows.

A comprehensive tool for interacting with Notion via its API. It allows users to perform workspace-wide searches, run complex queries against structured databases using compound filters (AND/OR), retrieve specific pages, and deeply traverse and extract all nested block content. Supports pagination for handling large datasets, enabling full data visibility and structured data extraction.

A comprehensive guide and workflow for managing a personal knowledge vault using Obsidian. It details best practices for structuring notes in a flat file system, utilizing index notes, and leveraging wikilinking syntax ([[wikilinks]]) for robust connectivity. Includes command-line methods (grep/find) for efficient searching, note creation, and finding related backlinks across the entire vault, ensuring organized, interconnected learning.

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.

This guide provides a comprehensive operational checklist for exploit development. It covers the entire lifecycle, from initial bug identification and vulnerability analysis (e.g., stack overflow, UAF) to payload development, mitigation bypass (ASLR, DEP, CFG), and reliable weaponization. Essential for security researchers developing Proof-of-Concept exploits and establishing a professional exploit development environment.

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 the architecture of low-level keyloggers. It covers techniques such as kernel driver hooks, using WH_KEYBOARD_LL, ETW-based input capture, and analyzing user-mode vs. kernel-mode approaches. Use this methodology to understand input capture mechanisms, research EDR evasion methods, or analyze malware architecture for advanced security threat detection.