Skill UI

A comprehensive guide covering patterns and architectures for automating code execution using LLMs. It spans simple sequential pipelines (e.g., daily dev scripts) to advanced, RFC-driven multi-agent Directed Acyclic Graph (DAG) orchestration. Ideal for building CI/CD style continuous development pipelines, managing complex state, and automating quality gates without human intervention.

This methodology systematically deobfuscates multi-layered PowerShell malware. It utilizes Abstract Syntax Tree (AST) analysis, dynamic execution tracing, and specialized tools (like PSDecode) to recover hidden payloads, original commands, and C2 infrastructure from scripts obfuscated with Base64, string concatenation, or complex invocation tricks. Essential for incident response and deep malware analysis.

A comprehensive guide for authorized penetration testers on identifying and exploiting insecure deserialization vulnerabilities across multiple languages (Java, PHP, Python, .NET). Covers techniques for generating payloads using tools like ysoserial and phpggc, and testing various application components such as cookies, HTTP parameters, and message queues to achieve potential Remote Code Execution (RCE).

Automates the static security analysis of Android APK/AAB files using the Mobile Security Framework (MobSF). This skill identifies critical vulnerabilities such as hardcoded secrets, insecure permissions, weak cryptography, and structural flaws (mapping to OWASP Mobile Top 10) without requiring application execution. It is essential for integrating security gates into CI/CD pipelines, performing pre-release quality assurance, and enhancing penetration testing coverage.

A lightweight CLI tool for systematically comparing various coding AI agents (such as Claude Code, Aider, and Codex) head-to-head. It measures crucial metrics—pass rate, API cost, execution time, and consistency—on reproducible tasks defined via YAML manifests. Use this to objectively select the best agent for your codebase or to validate model updates before production deployment.

This skill guides users through evidence-based terminal operations. It is designed for scenarios requiring direct command execution, Git status checks, debugging CI/build failures, and pushing narrow, verified fixes. It emphasizes following a structured, minimal-scope workflow and accurately reporting the repository's current state (e.g., local changes vs. pushed code).

Copilot Spaces allow users to consolidate and manage project-specific knowledge, including documentation, code snippets, architectural standards, and operational instructions. By loading a Space, Copilot grounds its responses not just on general knowledge, but on the curated, authoritative context of the entire project, enabling accurate Q&A, code generation, and workflow execution based on team standards. Ideal for onboarding, large-scale projects, and maintaining consistency.

Guides how to write JavaScript inside n8n Code nodes, choose execution modes, access data with $input/$node, handle Webhook payloads, and return the required [{json:…}] structure for automation tasks.

A comprehensive guide for writing and managing Python code specifically within n8n Code nodes. Learn how to perform complex data transformations, handle different execution modes (batch vs. item-by-item), and master various data access patterns (_input.all(), _input.item, _node). Note the critical limitations, such as relying only on the standard Python library and the general recommendation to use JavaScript for most n8n use cases.

Accelerate scientific Python code on NVIDIA hardware using CUDA and RAPIDS libraries. Optimizes NumPy, pandas, scikit-learn, and ML workloads for GPU execution. Includes profiling, memory management, and kernel optimization to ensure correctness and performance gains.

This guide outlines critical security best practices for design-to-code pipelines using Anima and Figma. It covers securing API credentials by restricting token scopes (e.g., read-only access for Figma), enforcing server-side execution for SDKs, and implementing robust secret management using cloud services like GCP Secret Manager. This minimizes the risk of credential leakage in CI/CD environments.

This setup implements a pre-execution hook to safeguard code repositories by intercepting and blocking destructive Git operations (e.g., `git push`, `git reset --hard`, `git clean`). It prevents accidental or unauthorized data loss during automated code generation or tool use within AI environments, ensuring robust version control safety.