--- name: "prog-expert-una" description: "Use when you need to implement UnaUI (@una-ui/nuxt) in Nuxt 3/4 — N* component usage, color tokens, slot patterns, UnoCSS-driven theming, and UnaUI module configuration." metadata: stage: "alpha" source: "MIGRATED" requires: - "impl-experts-js-contract" --- # Prog Expert UnaUI ## Goal Expert-level implementation of UnaUI in Nuxt projects. Covers the `@una-ui/nuxt` module setup, `N*` component API (NButton, NCard, NAlert, NInput, NCheckbox, NAvatar, NBadge, etc.), color prop conventions, slot composition patterns, and UnoCSS design token integration. ## Core Workflow (Progressive Disclosure) 1. **Context Analysis**: Analyze `nuxt.config.ts` modules section, existing `N*` component usage, and `uno.config.ts` theming. 2. **Knowledge Retrieval**: - Fetch latest library versions using `scripts/track_versions.py`. - Check `recipes/` for recurring patterns and implementation guides. - If needed, research new patterns via `scripts/research_knowledge.py`. 3. **Implementation**: Execute core logic. Leverage `atomic-examples/` and `recipes/` for guidance. 4. **Learning**: - Extract patterns from successful implementations via `scripts/learn_from_success.py`. - Create or refine coding recipes in `recipes/` using `scripts/manage_recipes.py`. ## Instructions - ALWAYS use pnpm as the package manager for this ecosystem. - Before starting any task, search the `recipes/` directory for relevant implementation patterns. - If a task involves a recurring pattern not yet in `recipes/`, create a new recipe after successful implementation. - Proactively update your knowledge if library versions are outdated or new patterns are discovered. - Scope: UnaUI component integration only. For raw UnoCSS config use `prog-expert-uno`. For Nuxt core concerns use `prog-expert-nuxt`. ## Key Technologies - `@una-ui/nuxt` (alpha channel) - `unocss`, `@unocss/nuxt`, `@unocss/reset` - `@iconify-json/lucide`, `@iconify-json/radix-icons`, `@iconify-json/tabler` - `@vueuse/core`, `pinia` ## Self-Learning & Research - Gathers knowledge using web research and the `use-context7-api` skill. - Learn from successful implementations, other codebases, and documentation. - Keep track of the latest library versions. - Refine recipes to be more granular based on implementation experience. ## Auto-Improvement - Every time this skill is used, analyze the usage chat to find out if further improvement of the skill is advised. - Ask the user if those changes should be made. - If approved, store the improvement ideas in the `resources/improvement_ideas.md` file. ## References - [Patterns](references/patterns.md) — Reusable code patterns and best practices. - [Versions](references/versions.json) — Tracked library versions. - [Recipes](recipes/README.md) — Coding recipes for recurring tasks. ## Example Code When learning or implementing, use these code examples. ALWAYS load them via `view_file` to maintain Progressive Disclosure: - **Atomic Examples** (Small code chunks from docs): - *(Add examples here)*: `view_file(/atomic-examples/...)` - **Recipes** (Larger patterns like form layouts, nav, data display): - *(Add recipes here)*: `view_file(/recipes/...)` - **Reference Implementations** (Complex pseudo-code from existing real-world codebases): - *(Add references here)*: `view_file(/reference-implementations/...)` ## Constraints * Do not perform unauthorized or destructive actions. * Do not overwrite existing files without explicit user confirmation. ## Script Integration - **Research**: `uv run scripts/research_knowledge.py ""` - **Version Tracking**: `uv run scripts/track_versions.py` - **Recipe Management**: `uv run scripts/manage_recipes.py [args]` - **Example Management**: `uv run scripts/manage_examples.py [args]` - **Pattern Learning**: `uv run scripts/learn_from_success.py `