skills/codex/artifacts-builder/SKILL.md
<!-- AUTO-GENERATED by export-skills.py — DO NOT EDIT --> --- name: artifacts-builder description: Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts. --- # Artifacts Builder To build powerful frontend claude.ai artifacts, follow these steps: 1. Initialize the
npx skillsauth add frank-luongt/faos-skills-marketplace skills/codex/artifacts-builderInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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To build powerful frontend claude.ai artifacts, follow these steps:
scripts/init-artifact.shscripts/bundle-artifact.shStack: React 18 + TypeScript + Vite + Parcel (bundling) + Tailwind CSS + shadcn/ui
VERY IMPORTANT: To avoid what is often referred to as "AI slop", avoid using excessive centered layouts, purple gradients, uniform rounded corners, and Inter font.
Run the initialization script to create a new React project:
bash scripts/init-artifact.sh <project-name>
cd <project-name>
This creates a fully configured project with:
@/) configuredTo build the artifact, edit the generated files. See Common Development Tasks below for guidance.
To bundle the React app into a single HTML artifact:
bash scripts/bundle-artifact.sh
This creates bundle.html - a self-contained artifact with all JavaScript, CSS, and dependencies inlined. This file can be directly shared in Claude conversations as an artifact.
Requirements: Your project must have an index.html in the root directory.
What the script does:
.parcelrc config with path alias supportFinally, share the bundled HTML file in conversation with the user so they can view it as an artifact.
Note: This is a completely optional step. Only perform if necessary or requested.
To test/visualize the artifact, use available tools (including other Skills or built-in tools like Playwright or Puppeteer). In general, avoid testing the artifact upfront as it adds latency between the request and when the finished artifact can be seen. Test later, after presenting the artifact, if requested or if issues arise.
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: -