plugins/faos-ux-designer/skills/react-components/SKILL.md
<!-- AUTO-GENERATED by export-plugins.py — DO NOT EDIT --> --- name: react-components description: Converts Stitch designs into modular Vite and React components using system-level networking and AST-based validation. tags: [react, tooling] --- # Stitch to React Components You are a frontend engineer focused on transforming designs into clean React code. You follow a modular approach and use automated tools to ensure code quality. ## Retrieval and networking 1. **Namespace discovery**: Run `l
npx skillsauth add frank-luongt/faos-skills-marketplace plugins/faos-ux-designer/skills/react-componentsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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You are a frontend engineer focused on transforming designs into clean React code. You follow a modular approach and use automated tools to ensure code quality.
list_tools to find the Stitch MCP prefix. Use this prefix (e.g., stitch:) for all subsequent calls.[prefix]:get_screen to retrieve the design JSON.Bash tool to run: bash scripts/fetch-stitch.sh "[htmlCode.downloadUrl]" "temp/source.html".screenshot.downloadUrl to confirm the design intent and layout details.src/hooks/.src/data/mockData.ts.Readonly TypeScript interface named [ComponentName]Props.tailwind.config from the HTML <head>.resources/style-guide.json.node_modules is missing, run npm install to enable the validation tools.src/data/mockData.ts based on the design content.resources/component-template.tsx as a base. Find and replace all instances of StitchComponent with the actual name of the component you are creating.App.tsx) to render the new components.npm run validate <file_path> for each component.resources/architecture-checklist.md.npm run dev to verify the live result.development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-mlflow-evaluation --- # MLflow 3 GenAI Evaluation ## Before Writing Any Code 1. **Read GOTCHAS.md** - 15+ common mistakes that cause failures 2. **Read CRITICAL-interfaces.md** - Exact API signatures and data schemas ## End-to-End Workflows Follow these workflows based on your goal. Each step indicates which reference files to read. ### Workflow 1: First-Time Evaluation Setup For users new to MLflow GenAI evalu
development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-lakebase-provisioned --- # Lakebase Provisioned Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads. ## When to Use Use this skill when: - Building applications that need a PostgreSQL database for transactional workloads - Adding persistent state to Databricks Apps - Implementing reverse ETL from Delta Lake to an operational database - Storing chat/agent m
tools
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-jobs --- # Databricks Lakeflow Jobs ## Overview Databricks Jobs orchestrate data workflows with multi-task DAGs, flexible triggers, and comprehensive monitoring. Jobs support diverse task types and can be managed via Python SDK, CLI, or Asset Bundles. ## Reference Files | Use Case | Reference File | | ----------------------
development
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: databricks-genie --- # Databricks Genie Create and query Databricks Genie Spaces - natural language interfaces for SQL-based data exploration. ## Overview Genie Spaces allow users to ask natural language questions about structured data in Unity Catalog. The system translates questions into SQL queries, executes them on a SQL warehouse, and presents results conversationally. ## When to Use This Skill Use this skill when: -