Skill UI

Seaborn is a high-level Python visualization library designed for creating publication-quality statistical graphics. It facilitates dataset-oriented plotting, multivariate analysis, and complex statistical visualizations (like KDEs, distributions, and relationships) directly from Pandas DataFrames with minimal code. It builds upon Matplotlib to provide semantic mapping and statistical awareness.

A comprehensive white-box security auditing workflow designed for proprietary source code. It integrates static analysis security testing (SAST) tools like Semgrep and CodeQL to detect common vulnerabilities (e.g., injection, IDOR, crypto misuse), followed by mandatory manual threat modeling and verification steps. Applicable for PR reviews and pre-deployment security checks.

This skill specializes in analyzing built frontend artifacts, going beyond static source code. It reconstructs the dynamic JavaScript structure, tracks chunk loading paths, and interprets source maps and build manifests to recover hidden routes, APIs, and runtime behaviors. Essential for deep security analysis and understanding execution flow from deployed bundles.

A highly specialized, downstream skill for advanced threat analysis. This tool is used to recover hidden configurations, decode C2 (Command and Control) parameters, unpack staged payloads, and extract Indicators of Compromise (IOCs) from complex malware samples. It focuses on identifying the exact decode chains—including compression, encoding, and crypto steps—and linking recovered fields to observed behavioral outcomes within a sandbox environment.

This specialized skill is designed to analyze complex security flaws involving forced authentication (coercion) and identity relay chains. It guides users to trace and document the complete, minimal path from the initial coercion trigger (e.g., a specific service or protocol edge) through intermediate hops, to the final service that accepts the relayed credentials. Use this for deep security research, forensics, and documenting the decisive sequence leading to privilege escalation or code execution.

This specialized skill analyzes the complete lifecycle of real-time web communications, including WebSocket and Server-Sent Events (SSE). It is designed to map the initial handshake, decode complex message streams (subscriptions, keepalives, pushes, reconnects), and trace how frame activity leads to persistent or rendered state changes. Use this to isolate the minimal, decisive sequence of events that prove a system's behavior.

A comprehensive skill for AI agents to perform advanced filesystem operations. It provides features for intelligent file listing with deep filtering, powerful content and pattern searching, safe batch file copying, and detailed directory analysis (statistics, tree visualization). Ideal for code analysis, system auditing, and managing project assets.

This tool tests your deep understanding of code you have recently written or reviewed. It generates structured, multi-level questions (Recall, Understanding, Application, Analysis, Synthesis) based on the provided code. Users can focus the quiz on specific areas like error handling, performance, or security, making it an excellent mechanism for continuous learning and solidifying technical knowledge.

This comprehensive guide details the methodology for reverse engineering macOS and Mach-O binaries. It covers analyzing application bundles, deciphering Objective-C/Swift symbols, examining code signing and hardened runtime features, and performing both static (using tools like Ghidra, IDA) and dynamic analysis (using lldb, Frida) to aid in malware analysis and platform security research.

A comprehensive methodology for deep security testing of both Android (APK) and iOS (IPA) applications. This guide covers the entire workflow, from initial information gathering and static analysis (decompilation, code structure analysis) to advanced dynamic instrumentation, network interception, and bypassing modern security measures like SSL Pinning, Root/Jailbreak detection, and anti-debugging.

This skill parses standardized C-CDA/CCD XML clinical documents exported from EHRs. It extracts both human-readable section narrative text and coded entries, mapping them by LOINC codes and template IDs. It is essential for preparing clinical free-text data for subsequent NLP analysis and supports XML-aware de-identification while preserving document structure.

This skill decodes complex pipe-delimited HL7 v2.x messages (including ADT, ORU, MDM) into structured segments and fields. It is essential for ingesting HL7 feeds from interface engines, allowing users to surface embedded clinical narratives (OBX-5 and NTE-3) for subsequent Natural Language Processing (NLP) analysis. It also provides segment-aware de-identification capabilities to redact PHI while preserving the native HL7 message structure.