Skill UI

This skill implements a comprehensive brand monitoring system to detect brand impersonation attacks across multiple digital attack surfaces, including domain squatting, social media profiles, phishing sites, mobile apps, and the dark web. It uses tools like dnstwist and integrates APIs (Google Safe Browsing, VirusTotal) to proactively identify unauthorized brand usage and potential cyber threats targeting an organization.

This comprehensive guide details industry best practices for container image hardening. It covers minimizing attack surface through multi-stage builds, utilizing distroless images, enforcing non-root users, and configuring read-only root filesystems. The techniques ensure compliance with standards like the CIS Docker Benchmark, making images secure and production-ready.

This comprehensive guide details a multi-step workflow for detecting and extracting covert data hidden within images, audio, and video files. It covers initial metadata analysis, running advanced steganalysis tools (like zsteg, binwalk, stegoveritas), and performing low-level analysis such as Least Significant Bit (LSB) analysis to uncover hidden communication channels used in digital forensics and cybersecurity investigations.

Grype is an open-source vulnerability scanner from Anchore. It inspects container images, filesystems, and SBOMs for known CVEs. It leverages Syft-generated SBOMs to match packages against multiple vulnerability databases (NVD, GitHub Advisories). Use it for security assessments, auditing, and integrating into CI/CD pipelines to enforce vulnerability standards and manage supply chain risks.

A Manus-style file planning system for breaking down complex tasks, tracking progress, and preserving context across sessions. It creates task_plan.md, findings.md, and progress.md for multi-step projects and research workflows.

A Manus-style file planning system for organizing complex multi-step tasks. It creates task_plan.md, findings.md, and progress.md to track research, planning, and execution, with automatic session recovery after /clear.

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.

A comprehensive guide to hardening Windows Active Directory environments using Group Policy Objects (GPO). This skill configures multiple layers of defense, including AppLocker, Controlled Folder Access, and Attack Surface Reduction (ASR) rules, to prevent ransomware execution paths, block unauthorized file modifications, and restrict lateral movement across the domain.

This comprehensive skill guides the user through the entire process of creating a deep, multi-layered AI persona (Soul.md). It helps define the identity, core rules, name, and visual prompts for agents designed for the OpenClaw platform. Users can initiate character creation via guided prompts or a random 'gacha' draw, ensuring a cohesive and compelling character profile.

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.

This framework manages the ingestion, organization, synchronization, and search of knowledge across multiple storage layers, including local files, persistent memory, vector stores, and Git repositories. It provides a structured approach for ensuring knowledge durability, deduplication, and maintaining a 'single source of truth' across complex development and operational contexts.