Skill UI

This guide details how to use Skyvern's AI-powered Command Line Interface (CLI) for advanced browser automation. Users can perform tasks such as quick data validation, structured data extraction, form filling, secure login, and building complex, multi-step, reusable workflows across various websites. It offers solutions for scenarios where deterministic selectors fail.

This tool automates complex Git workflows to save time and reduce manual overhead. It intelligently detects and groups related code changes, automatically generates descriptive branch names (e.g., fix/auth-bug), and streamlines the entire cycle: staging, committing, pushing, and creating Pull Requests (PRs). Use it to maintain clean, consistent commit histories efficiently.

This skill generates SmartUI visual regression test configurations for screenshot comparison on TestMu AI cloud. It is framework-agnostic, supporting Playwright, Selenium, Cypress, and Puppeteer. Users can create baselines, compare screenshots, and approve changes via the LambdaTest SmartUI dashboard. Ideal for automated visual testing workflows.

This skill enables encryption of secrets within configuration files using Mozilla SOPS. It supports GitOps workflows, Kubernetes secret management, and secure configuration storage. Users can encrypt files with KMS or PGP keys, decrypt them for editing, and integrate with tools like ArgoCD. It ensures sensitive data remains protected while maintaining file structure visibility for version control.

Expert TDD orchestrator for enforcing red-green-refactor discipline, coordinating multi-agent workflows, and applying modern test-driven development practices across software projects. Covers test suite architecture, AI-assisted test generation, metrics, and framework integration.

This skill acts as an alias for the canonical TDD workflow cycle. It assists developers in implementing Test-Driven Development methodologies by structuring testing cycles and ensuring quality assurance. Use it when working on software development tasks requiring a test-first approach. It redirects to the full TDD cycle implementation for detailed guidance on writing tests before code.

This skill focuses on the 'Green Phase' of Test-Driven Development (TDD). It involves writing the minimal amount of code required to make failing tests pass. It emphasizes simplicity and avoiding premature optimization or architectural changes. Use this when moving from red to green status in your test cycle.

Guides the TDD red phase by generating comprehensive failing tests that define expected behavior, edge cases, and error handling across multiple frameworks (Jest, pytest, JUnit, Go, RSpec). Ensures failures are meaningful and test isolation.

Safely refactor code with a comprehensive TDD safety net: establish a green baseline, detect code smells, apply design patterns and SOLID principles, optimize performance, and verify all tests remain green.

This skill provides a robust system for tracking all code modifications using structured JSON records and enforcing a defined state machine (e.g., planned -> deployed). It is critical for AI coding workflows, ensuring that if a session expires or is abandoned, the next session receives the full context, progress summary, and blockers to resume seamlessly. Ideal for complex, multi-stage development projects and onboarding new codebases.

This skill provides comprehensive, programmatic automation capabilities for the Telegram platform via Rube MCP. Users can manage virtually every aspect of Telegram interaction, including sending various media types (text, photos, documents), retrieving detailed chat information, listing members, editing and deleting messages, and setting custom bot commands. It is essential for building sophisticated, automated bot workflows and integrations.

Master Temporal workflow orchestration using the Python SDK. Covers durable workflows, saga patterns, and distributed transactions. Includes guidance on async/await execution models, worker configuration, activity implementation, error handling, retry policies, and signal/query patterns. Ideal for building reliable, scalable distributed systems and production-ready workflow applications with Python.