Skill UI

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 specialized downstream skill for advanced CTF and security sandbox environments. This tool is used when the challenge requires reconstructing the exact message sequence, state transitions, and field mutations necessary for a system to accept a session. It handles complex tasks like recovering custom framing, checksum validation, stateful replay, and identifying the minimal conversation path that proves a specific branch acceptance.

This specialized skill is designed for Digital Forensics and Incident Response (DFIR) scenarios. It correlates evidence from multiple disparate sources—including EVTX, PCAP, registry, memory, and filesystem artifacts—to build a comprehensive, ordered, and replayable forensic timeline. Use it when the goal is to map the full sequence of attacker actions, establishing initial access, lateral movement, and persistence chains based on cross-source evidence correlation.

This specialized skill automates advanced forensic network analysis on captured packet data (PCAP). It is designed for reconstructing complex network sessions (TCP/UDP), decoding obscure or custom protocols (e.g., C2, custom binary), and correlating packet sequences with host or malware behavior. Use when evidence is embedded in protocol framing, timing, or session state, requiring reassembly beyond simple packet inspection.

This advanced skill specializes in detecting and recovering hidden data (steganography) embedded within various media containers, including images, audio, video, and documents. It is crucial for forensic analysis and CTF challenges, allowing users to inspect metadata, LSBs, alpha/palette channels, and appended trailers to reconstruct hidden payloads without brute force.

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 guide for authorized digital forensics investigation. It covers critical areas including memory dump analysis (using Volatility), disk timeline reconstruction, PCAP network traffic analysis, and system artifact triage (like Event Logs and Prefetch). Essential for incident response, evidence preservation, and threat hunting to maintain a robust chain of custody.

Guideline for front-end JavaScript reverse engineering using js-reverse MCP tools and jshookmcp. Covers locating signature and encrypted parameters, tracing request initiators, runtime sampling via hooks, local Node environment reconstruction, and evidence-first output for reproducing signing logic.

A comprehensive multi-step pipeline tool that executes a fully validated development plan. It handles worktree isolation, TDD scaffolding, parallel task execution across architectural layers, quality gating (linting, testing, smoke tests), documentation reconciliation, PR creation, and final merge, ensuring the feature is fully documented and integrated.

A comprehensive, multi-phase workflow guide for authorized reverse engineering of complex network protocols. Ideal for analyzing proprietary formats such as custom TCP/UDP binary protocols, Protobuf, gRPC, WebSocket frames, and reconstructing state machines from raw PCAP data. This guide covers data collection, field layout restoration, serialization recovery, and secure replaying.

A robust template designed for creating complex, multi-stage commands or 'recipes.' It enforces a highly structured process by mandating 'Context Validation Checkpoints' before any step executes. This pattern ensures that preconditions are explicitly verified, significantly increasing the reliability and predictability of complex automated workflows.

This skill processes raw mentions of conditions and diagnoses extracted from clinical notes. It performs synonym deduplication, filters out negated or hypothetical mentions, and assigns a structured clinical status (active, resolved, or historical). The output is a clean, reconciled problem list, structured for USCDI Problem or FHIR Condition elements.