Skill UI

A comprehensive guide for developers migrating and upgrading Obsidian plugins across major API versions. It covers critical steps such as auditing plugin compatibility, implementing version-aware settings migration logic (for user data persistence), replacing deprecated API calls (e.g., Vault, Editor, FileManager), and updating configuration files like manifest.json to ensure stability on new Obsidian releases.

This guide identifies and explains common anti-patterns and critical pitfalls encountered when building applications on the Replit platform. Topics include data persistence, secret management, networking bindings, and environment configuration. Use this resource when conducting code reviews, onboarding new developers, or auditing existing Replit applications for best practices.

This pattern demonstrates how to build a robust, thread-safe data persistence layer in Swift using the 'actor' model. It combines fast in-memory caching with reliable file-backed storage, automatically eliminating data races and the need for manual locks. Ideal for offline-first applications and managing shared mutable state in modern Swift concurrency.

This skill provides advanced context management for AI in large-scale, complex codebases. It optimizes context windows, ensures memory persistence across multiple sessions, and helps prioritize critical information. Use it when working with massive code repositories to maintain context and improve developer workflow.

Master the architecture of reliable distributed systems using advanced workflow orchestration patterns. This guide covers fundamental design decisions, including the distinction between Workflows and Activities, and introduces critical patterns like Saga for distributed transactions, Entity Workflows, and Fan-Out/Fan-In. Learn best practices for handling long-running processes, state persistence, and failure recovery to build robust business logic.

This skill provides best practices for managing application state and ensuring data persistence within large-scale applications, particularly for systems using Makepad architecture (Robrix/Moly). It details core structures like AppState, techniques for passing state through widget trees (Scope), and handling persistent data serialization (serde) across sessions, making it essential for building robust, multi-session UIs.

A comprehensive guide for digital forensics analysts to investigate compromised Linux systems. This workflow details the collection and analysis of critical system artifacts, including authentication logs, shell histories, SSH keys, and system configurations. Use this methodology during incident response to detect rootkits, unauthorized persistence mechanisms, and reconstruct full attacker activity.

A comprehensive tool for security professionals to enumerate and analyze malware persistence mechanisms across critical Windows Auto-Start Extensibility Points (ASEPs). It systematically scans registry run keys, scheduled tasks, services, drivers, and startup locations. Ideal for incident response, threat hunting, and validating the complete removal of malicious autostart entries.

This comprehensive skill scans Linux systems for various persistence vectors, including crontab entries, systemd units, LD_PRELOAD injections, and shell profile modifications. It correlates these findings with auditd logs to build a detailed installation timeline, which is critical for incident response and threat hunting to detect hidden backdoors.

A comprehensive toolkit using Splunk's SPL language to analyze Windows Security, System, and Sysmon event logs. It maps advanced detection queries to specific MITRE ATT&CK techniques, enabling SOC analysts to investigate authentication attacks (e.g., brute force, password spraying), detect privilege escalation, locate persistence mechanisms, and trace lateral movement for detailed forensic timeline analysis.

This comprehensive guide details the systematic extraction and analysis of Windows Registry hives (SAM, SYSTEM, SOFTWARE, NTUSER.DAT) from forensic images. It demonstrates how to use specialized tools like RegRipper and Python scripts to uncover critical artifacts, including user activity history, persistence mechanisms (autorun keys), installed software records, and evidence of system compromise, which is crucial for digital forensics investigations.

This skill implements an autonomous, multi-round review loop for refining complex research or codebases. It iteratively reviews content using specified external backends (e.g., Codex, manual review), implements necessary fixes based on feedback, and re-reviews until the positive assessment criteria are met or the maximum round limit is reached. It manages state persistence and allows for configurable difficulty levels, making it ideal for projects requiring rigorous, self-correcting quality assurance.