Skill UI

This guide enforces a mandatory, multi-stage process for debugging complex software issues. It moves developers beyond merely patching symptoms by forcing them through Root Cause Investigation, Pattern Analysis, Hypothesis Validation, and proper Implementation with testing. It is crucial for solving production bugs, failed tests, and performance issues in a structured manner.

This skill guides the parallel assignment of specialized agents when debugging multiple, independent failure domains. Instead of using one agent for all issues, isolate each problem (e.g., a specific test file or subsystem) to its own dedicated agent. This allows agents to work concurrently without sharing context or interfering with each other, significantly accelerating the debugging process and maintaining context purity.

This structured skill guides users through root-cause-first debugging when an implementer is blocked, verification fails, or repeated attempts at fixing do not converge. It mandates a systematic approach combining local evidence inspection, runtime analysis, and external documentation research to accurately classify the failure's true source (e.g., missing dependency, spec conflict). It prevents speculative patching and generates a clear, actionable fix plan.

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 utility provides comprehensive capabilities for viewing, creating, uploading, editing, and comparing Markdown files stored in the cloud drive. It is designed for scenarios requiring local content manipulation, such as creating new files, fetching existing content, performing localized text patching (regex replacement), comparing version differences, or overwriting content. Note that it specifically handles structured Markdown files, not docx conversions, and defers cloud space management operations (like searching, moving, or permissions) to other dedicated skills.

A comprehensive playbook for defeating anti-debugging mechanisms in protected binaries. Covers advanced techniques across both Linux (ptrace, /proc/self/status, timing checks) and Windows (PEB flags, NtQueryInformationProcess). Provides detailed detection methods and corresponding bypass strategies (e.g., patching, hooking, kernel modules) essential for advanced binary reverse engineering.

This critical protocol is the ultimate measure for dealing with deeply corrupted, unmaintainable, or structurally rotten code modules. Instead of risky patching, it mandates a controlled, multi-phase process to completely delete the target and rebuild it from scratch. It ensures precise identification of all public interfaces, implicit contracts, and working behaviors (the Preservation List) before any removal occurs, guaranteeing the new implementation matches the original functionality while resolving deep architectural debt.

A powerful plugin enabling Claude Code to delegate complex tasks to external AI CLIs (such as OpenAI Codex or Google Antigravity/Gemini) without exiting the conversation. It supports multi-model workflows, allowing users to seek a second opinion, cross-check deep analysis, or delegate side tasks (like research or code review). The core value is that Claude synthesizes the raw outputs, providing a critical review and reconciliation of findings across all consulted models.

This harness transforms standard code environments into fully persistent, autonomous agent systems. It leverages native features like scheduled tasks (Crons), remote dispatching, and structured memory storage (MCP) to enable continuous, self-directing automation. Ideal for building AI assistants that require long-term context, recurring workflows, and complex, multi-step operations, eliminating the need for external agent frameworks like AutoGPT.

A robust framework for orchestrating complex, multi-step coding tasks using multiple AI agents. It functions by first planning the entire project into a mission dependency graph (DAG), then dispatching specialized agents to isolated Git worktrees for parallel development. The system automatically monitors progress, handles merges, and generates structured, comprehensive reports detailing changes, completed tasks, and next steps.

This skill automates the entire GitHub Pull Request (PR) review cycle, specifically targeting Copilot Code Review comments. It runs a robust loop: automatically triggering reviews, triaging open threads, dispatching parallel fixes that adhere to repo conventions, committing changes, and resolving comments. It continues iterating until the PR is deemed clean and ready for merge, minimizing manual effort and ensuring high code quality.

A comprehensive methodology for advanced red teaming and adversary emulation. This skill details how to bypass modern Endpoint Detection and Response (EDR) solutions (e.g., Defender, CrowdStrike, SentinelOne). Techniques include unhooking ntdll, utilizing indirect syscalls (Hell's Gate), patching ETW providers, and AMSI context blinding. Essential for authorized penetration testing and self-developed implant development, aligning with MITRE ATT&CK T1562.