Diagnose and standardize Go TUI conventions for the Charmbracecelet ecosystem.
npx skills add https://github.com/dotBeeps/pantry --skill go-tui
Please help me install this Agent Skill. Skill: go-tui Source: https://github.com/dotBeeps/pantry/tree/main/morsels/skills/go-tui Command: npx skills add https://github.com/dotBeeps/pantry --skill go-tui
Go TUI conventions provide a standardized blueprint for building terminal user interfaces in Go using the Charmbracelet ecosystem, reducing guesswork and ensuring consistency across projects.
Follow the MVU pattern and styling guidelines to scaffold a minimal terminal UI using Bubble Tea and Lip Gloss.
High-intent search queries and answers about installing and using this skill.
To structure a Go terminal UI with Bubble Tea, follow the MVU pattern by defining explicit expectations for Init, Update, and View methods to separate state, message handling, and rendering logic.
The best way to style Go TUI components consistently is to apply Lip Gloss and Huh conventions, establishing standardized styling rules across your project to ensure uniform look and behavior.
You need standard conventions for Charmbracelet terminal applications when building new terminal dashboards or forms, reducing guesswork and ensuring maintainable code architecture across projects.
To scaffold a minimal terminal UI with Bubble Tea and Lip Gloss, follow the MVU pattern and styling guidelines provided in the Quick Start to structure code, styling, and input handling.
Yes, this approach supports creating interactive forms in Go terminal applications by applying Huh component conventions alongside Bubble Tea workflows to achieve consistent input handling.
DicklesworthstoneBuild Go-based terminal UIs with Charmbracelet libraries and shell-script workflows for dashboards and prompts.
hasnaConvert JSON specifications into interactive terminal component trees.
hoangtran1411Create interactive terminal user interfaces in Go with Bubble Tea and Lipgloss.
HermeticOrmusGenerate Go TUI applications from natural language prompts via iterative meta-prompting.
