Skill UI

This file is currently undergoing Japanese localization for the production scheduling functionality. It serves as a placeholder for the Japanese translation and refers to the original English skill file for the core logic and details.

A comprehensive guide for building robust, production-grade desktop applications using Electron. This skill covers advanced topics including multi-process architecture, mandatory security hardening (contextIsolation, sandbox), secure IPC communication, and best practices for packaging, code signing, and implementing auto-update features.

A comprehensive guide to building robust database layers in Kotlin using the Exposed ORM framework. It covers advanced patterns including DSL queries, DAO entity management, transaction handling, connection pooling with HikariCP, schema migration via Flyway, and implementing the Repository pattern for clean, production-grade data access.

This skill provides methods for reliably extracting typed, validated, and structured data from Large Language Models (LLMs), moving beyond simple text parsing. It covers best practices across major APIs (OpenAI's response_format, Anthropic's tool_use, Google's responseSchema) and local models. Key workflows include defining schemas (Pydantic/Zod), implementing constrained decoding, and building robust retry loops for production-grade data pipelines.

Opinionated Docker development assistant that analyzes Dockerfiles, docker-compose setups, multi-stage builds, and container security to shrink images, speed builds, and enforce production-ready practices when users need optimized containers.

Helm Chart Builder skill scaffolds production-grade charts, audits security, manages dependencies, and validates values/templates via slash commands for creation, review, and hardening workflows in Kubernetes deployments.

A comprehensive collection of six expert-level, structured workflows designed to elevate AI assistance from ad-hoc querying to repeatable, production-grade engineering practices. Users can evaluate prompts, design RAG architectures, plan context budgets, run security audits, build eval harnesses, and coach product strategy.

A comprehensive strategy for regression testing in AI-assisted development. It focuses on identifying systematic blind spots, such as schema inconsistencies between sandbox and production paths, and integrating automated bug checks into the development workflow. This guide teaches how to build robust, database-free API tests to ensure code quality when AI models contribute to the codebase.

This comprehensive guide details the deployment and hardening of the Havoc C2 framework, a modern post-exploitation Command and Control system. Learn how to establish a production-grade infrastructure, including configuring Teamservers, setting up various listeners (HTTP/HTTPS/SMB), and integrating Nginx redirectors. It provides OPSEC-hardened techniques for authorized red team adversary emulation engagements.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

This comprehensive guide details security best practices for hardening Docker containers and their underlying infrastructure (daemon, runtime, images). It aligns with standards like the CIS Docker Benchmark v1.8.0, enforcing least privilege through non-root users, capability dropping, read-only filesystems, and advanced security profiles (seccomp/AppArmor). Essential for building highly secure, compliant, and production-ready container environments.

This guide details the implementation of a robust, ransomware-resilient backup architecture following the extended 3-2-1-1-0 rule. It covers critical steps such as classifying assets, defining RPO/RTO, implementing immutable or air-gapped storage, and isolating backup credentials from the production domain. Use this knowledge to design a multilayered defense against data loss and ensure reliable recovery points.