Skill UI

Optimizes Dockerfiles and docker-compose files for size, speed, and security. Provides best practices for multi-stage builds, layer caching, and container hardening. Includes analysis tools for production-grade containerization without wasting time or space.

A dedicated tool for forensic analysis of Windows PowerShell Script Block Logs (Event ID 4104) captured in EVTX files. It reconstructs multi-block scripts, applying advanced detection heuristics such as entropy analysis and pattern matching to identify obfuscated commands, encoded payloads (Base64), download cradles, and AMSI bypass attempts, crucial for threat hunting and incident response.

Builds a comprehensive, automated pipeline for malware submission and analysis. It collects suspicious files from multiple sources (EDR, email gateways), automatically submits them to sandbox environments and multi-engine scanners, and generates detailed verdicts and Indicators of Compromise (IOCs). Essential for SOC teams needing to scale high-volume malware triage and incident response.

This skill provides a systematic pipeline for safely executing large-scale code refactors across multiple files or subsystems. It first performs parallel, dependency-aware analysis to map the entire scope, synthesizing a single, actionable plan. The process then breaks the work into independent 'work packets,' which are executed sequentially or in parallel by specialized worker agents, ensuring strict dependency management and behavior parity throughout the entire process.

This system detects ransomware by combining multiple advanced techniques: real-time entropy analysis, file system I/O monitoring, and behavioral heuristics. It identifies abnormal mass file modification patterns, sudden spikes in data entropy (indicating encryption), and suspicious process activities like shadow copy deletion. Ideal for building advanced EDR detection layers to catch zero-day and unknown ransomware variants.

Automates the complex pre-development workflow for large-scale system transformations, such as major rewrites, migrations, or overhauls. This skill performs comprehensive project analysis, task decomposition, planning document generation, and sets up detailed progress tracking across multiple phases, ensuring a structured approach before any coding begins. It supports adaptive control and integrates robust task tracking via GitHub or local files.

The Desktop Commander MCP grants agents deep reach across the user's entire operating environment, extending far beyond the typical IDE sandbox. Key capabilities include maintaining persistent shell sessions, managing long-running background processes, accessing arbitrary filesystems, and natively handling structured data formats (Excel, PDF, DOCX). It also enables remote operations via SSH and large-scale content search, making it ideal for complex, multi-turn development, DevOps, and data analysis workflows.

This skill enables parallel read-only multi-agent root-cause investigation for bugs, regressions, crashes, or unexplained failures. It deploys four specialized sub-agents to analyze reproduction, code paths, recent changes, and proof plans simultaneously. The main agent synthesizes findings into ranked hypotheses without editing files. Ideal for diagnosing complex software issues efficiently.

This skill provides a systematic pipeline for safely executing large-scale code refactors across multiple files or subsystems. It first performs parallel, dependency-aware analysis to map the entire scope, synthesizing a single, actionable plan. The process then breaks the work into independent 'work packets,' which are executed sequentially or in parallel by specialized worker agents, ensuring strict dependency management and behavior parity throughout the entire process.

This skill identifies hidden risks in code changes beyond the diff and verifies safety by executing real code. It helps determine the blast radius of modifications before merging or designing, ensuring multi-file edits and shared path updates do not break existing clients or systems.

This skill enables writing efficient C code with proper memory management and pointer handling. It covers systems programming, embedded systems, multi-threading, and debugging. Best practices include avoiding memory leaks, checking return values, and using static analysis tools. Suitable for creating Makefiles, headers, unit tests, and performance benchmarks following C99/C11 standards.

A command-line interface for comprehensive code review, architectural plan analysis, and large context processing tasks. Supports multiple Gemini models with configurable approval modes for automated or interactive workflows. Ideal for codebases exceeding 200k tokens and multi-file analysis. Uses Gemini 3 Pro by default for state-of-the-art reasoning and coding capabilities.