Skill UI

This comprehensive guide details the end-to-end setup for Granola AI, an advanced AI meeting note-taking solution. It covers initial installation on macOS/Windows, authenticating with major cloud services (Google/Microsoft), and critically, granting all necessary system permissions (Screen Recording, Microphone) to ensure seamless, background audio capture and transcription. Use this guide when setting up Granola for the first time or troubleshooting connectivity issues.

Automates designing and implementing table partitioning strategies to keep large databases performant, optimize time-series workloads, and shorten maintenance windows, with guidance on key selection, SQL scripts, and query tuning.

This skill provides methodologies for designing sophisticated, layered memory architectures for AI agents. It moves beyond simple context windows and basic vector stores by incorporating short-term, long-term, and graph-based memory systems. Implementing this is crucial for agents that require persistence across sessions, maintaining complex entity consistency, and performing advanced, relationship-driven reasoning over accumulated knowledge bases, including time-aware fact tracking.

A comprehensive utility designed to monitor, analyze, and predict blockchain gas costs across multiple major chains (e.g., Ethereum, Polygon, Arbitrum). It fetches real-time pricing, estimates transaction costs in both ETH and USD, and identifies the optimal time windows for executing DeFi or NFT transactions, ensuring maximum cost efficiency.

This skill details the forensic analysis of Windows LNK shortcut files and Jump Lists. These artifacts record critical user activity, including file access and program execution, even after the original source files have been deleted. It covers using specialized tools (LECmd, JLECmd) and Python parsing techniques to reconstruct user timelines, making it essential for incident response and deep digital forensics examinations.

This skill details advanced digital forensics techniques for recovering metadata and content of deleted files by analyzing the NTFS Master File Table ($MFT). It covers examining key system artifacts like $LogFile and $UsnJrnl, and analyzing MFT slack space. Use this when reconstructing file system timelines, investigating data loss, or detecting anti-forensic techniques like timestomping during a Windows forensic examination.

This skill guides the process of analyzing Windows Prefetch (.pf) files to reconstruct a detailed program execution history. By parsing these system artifacts, users can determine which applications were run, how many times, and when. It is crucial for building forensic timelines, confirming suspicious binary execution during malware investigations, and localizing evidence in a Windows system.

A comprehensive guide utilizing Splunk Enterprise Security and SPL to conduct deep forensic analysis of security incidents. This skill covers correlating disparate sources like Windows event logs, firewall records, proxy data, and Sysmon logs to detect TTPs, reconstruct timelines, and identify anomalies, making it essential for incident response and threat hunting.

This tool correlates multiple system artifacts, including Windows registry keys (USBSTOR, MountedDevices), Event Logs, and SetupAPI logs, to reconstruct a detailed timeline of USB device usage. It determines first/last connection timestamps, tracks device provenance, and maps drive letter assignments. Essential for digital forensics investigations, insider threat detection, and verifying compliance regarding removable media usage.

This guide details a comprehensive workflow for digital forensic investigations focusing on Amcache.hve registry hive. It teaches how to use AmcacheParser to extract evidence of program execution, application installation, and driver loading, including correlating SHA-1 hashes with threat intelligence and reconstructing timelines. This is crucial for DFIR work to identify deleted executables and malicious activity.

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 skill parses Windows Prefetch (.pf) files to reconstruct detailed application execution history. It is crucial for digital forensics, allowing analysts to track execution timelines, identify suspicious or renamed binaries, and investigate potential malware activity or lateral movement during incident response. It uses Python to extract run counts and accessed file details.