Skill UI

This skill helps create detailed step-by-step technical tutorials, quickstarts, and code walkthroughs. It focuses on clear prerequisite handling, environment setup instructions, and troubleshooting sections to ensure users achieve successful results. Suitable for developers needing structured guidance on software implementation and project initialization.

Provision and manage AWS cloud infrastructure using Terraform Infrastructure as Code (IaC). Create reusable modules, manage state files, and implement best practices for declarative resource deployment. Suitable for DevOps workflows requiring automated server, network, and storage setup.

This skill provides production-ready Terraform module patterns for AWS, Azure, and GCP infrastructure. It helps build reusable infrastructure components, standardize cloud resource provisioning, and implement infrastructure as code best practices. Users can create multi-cloud compatible modules and establish organizational Terraform standards. Includes guidance on module structure, variables, outputs, and testing with Terratest.

Expert in Terraform and OpenTofu for Infrastructure as Code (IaC). Covers advanced module design, state management, multi-cloud deployments, and CI/CD automation. Ensures secure, scalable, and compliant enterprise infrastructure patterns through policy-as-code and GitOps workflows.

This skill provides a systematic, multi-step approach to identify and resolve all failing unit tests within a codebase. It guides the user through smart error grouping (e.g., grouping by ImportError or AttributeError), prioritizing fixes from infrastructure to business logic, and ensuring thorough verification to prevent regressions. Ideal for use after major refactoring, debugging CI/CD failures, or when explicitly tasked with making the test suite pass.

This comprehensive workflow provides a complete cycle of quality assurance for software development. It covers every stage from defining the test strategy (TDD, Unit Testing) through integration, E2E testing, browser automation, performance profiling, security scanning, and final code review. Use this when setting up robust testing infrastructure or ensuring production-ready software quality.

This skill automates the creation of comprehensive unit tests across multiple programming languages like Python, JavaScript, and Java. It analyzes source code to identify functions and classes, then generates maintainable test suites with strong coverage, edge case handling, and proper mocking. Ideal for developers seeking consistent test structures and improved code quality without manual writing.

LWC is a durable memory system for coding agents that preserves project decisions, code structure, and verified context across sessions. It utilizes a physical Wiki document graph and a CodeGraph index to enable source-grounded recall. This tool helps agents search, update, and maintain knowledge without losing critical information during future coding-agent interactions.

WGM is a robust, agentic methodology designed to transform vague or rough requirements into working, validated software. It enforces a disciplined workflow across six stages: deep alignment (Grill), structured planning, deterministic iterative building (Loop), mandatory holdout-scenario judging, and final documentation audits. It ensures that the resulting code converges against rigorously tested acceptance criteria rather than relying on single-pass generation.

This skill acts as a documentation architect to generate structured wiki catalogues and onboarding guides directly from codebases. It scans repository file trees, detects technologies, and creates hierarchical documentation including principal-level guides, getting started instructions, and deep dive architectures. Every section cites specific files to ensure accuracy and relevance for developers.

This skill optimizes LLM context usage through prompt caching, log pruning, and AST-based file inspection. It enforces ultra-dense output, minimizes filler text, and manages token budgets efficiently. Ideal for technical tasks requiring precise code edits, structured data handling, and reduced context window consumption during long sessions.