Skill UI

Zarr is a Python toolkit for chunked N-D array storage with compression, sharding, and native integrations with NumPy/Dask/Xarray, ideal for parallel I/O and scalable cloud pipelines.

Master common data transformations using functional programming patterns in TypeScript. This guide covers essential techniques for arrays, objects, and complex data structures, including mapping, filtering, reducing, grouping, and safely accessing nested values. It teaches how to replace verbose, imperative loops with concise, declarative functional code, improving readability and maintainability.

Master the creation and manipulation of 3D geometry within the Three.js framework. This guide covers built-in primitive shapes (Box, Sphere, Cylinder), advanced procedural geometries (Extrude, Tube, TorusKnot), and text visualization. Crucially, it details the use of BufferGeometry, allowing developers to store vertex, normal, UV, and color data in optimized typed arrays for high-performance rendering and custom mesh construction.

This skill covers implementing complex user interactions within Three.js scenes. It demonstrates techniques like raycasting for precise object selection and click detection, handling mouse and touch inputs, and integrating various camera controls (OrbitControls, FlyControls, FirstPersonControls). Use this when building highly interactive, immersive 3D web applications.

A comprehensive, systematic framework for auditing and improving web UI designs and frontend code. It teaches core principles like grayscale-first design, constrained scaling (for spacing, type, and color), and establishing clear visual hierarchy. Use this guide when needing to refine an existing UI that 'looks off,' or requires professional structural and aesthetic improvements.

This skill provides a comprehensive guide to detecting and analyzing heap spray exploitation techniques from raw memory dumps. Utilizing Volatility3's advanced plugins (such as malfind and vadinfo), users can identify key forensic artifacts like NOP sled patterns, suspicious executable memory regions, and embedded shellcode. It is essential for malware analysts and digital forensics investigators conducting incident response.

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 provides structured methods for detecting credential stuffing attacks by analyzing authentication logs. It focuses on identifying complex patterns such as login velocity anomalies, high IP diversity, password spray techniques, and suspicious geographical distributions of failed logins. It is essential for SOC analysts conducting threat hunting or building robust detection rules against account takeover attempts.

This skill systematically probes an AI model's core behavioral patterns across six critical dimensions, including reasoning, refusal, formatting, and grounding. It generates a comprehensive, styled HTML report with radar charts and actionable insights, allowing users to understand a model's true capabilities, compare different models, or perform compliance and red-team assessments without needing an external API key.

This guide details how to analyze comprehensive Zeek network logs (conn.log, smb_files.log, ntlm.log, dce_rpc.log, etc.) to detect advanced attacker techniques. It specifically targets indicators of compromise related to lateral movement, such as SMB admin share access, NTLM account spraying, and remote service execution (DCE/RPC patterns). It is a critical network forensics tool for post-incident investigation.

This comprehensive guide dives deep into the internals of Go's built-in data structures (slices, maps, arrays) and standard library packages. It covers critical topics like capacity growth mechanics, preallocation strategies, pointer types (unsafe/weak), and the optimized usage of specialized containers (heap, list, ring). Use this resource to select the correct structure for optimal performance and memory safety in expert Go development.

This skill guides developers in writing robust and defensive Go code. It addresses common pitfalls that lead to runtime panics and silent data corruption, such as nil map writes, slice backing array aliasing, silent numeric truncation (int64 to int32), and inaccurate float comparisons. Use this when designing highly reliable Go systems that must withstand typical programmer errors and maintain data integrity.