# Dashboard View Builder

> Building and managing premium statistical dashboards, RAG explorer UIs, warehouse log monitors, and real-time visualization centers.

- Skill: `gitwalter/dashboard-view-builder` (Agent Skill)
- Install (CLI): `npx skillmds@latest add gitwalter/dashboard-view-builder`
- Raw SKILL.md: https://api.skillmd.com/api/skills/gitwalter/dashboard-view-builder/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: gitwalter (https://skillmd.com/u/gitwalter)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/gitwalter/dashboard-view-builder

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# Premium Dashboards & Interactive Explorers

This skill enables the development, hosting, and data management of interactive dashboards (Streamlit/Next.js), RAG explorer centers, database connectors, and warehouse tracking tools.

## When to Use
Use this skill when modifying statistical dashboards, writing custom connectors (news, financial, economic), implementing data guards, or deploying interactive knowledge explorers.

## Prerequisites
- Streamlit, Next.js, and web dependency libraries installed.
- Conda environment initialized.

## Process

Follow these procedures to build and launch interactive dashboards.

### Launching Streamlit Applications
Start the statistical warehouse dashboard or RAG knowledge explorer locally:
```bash
conda run -p D:\Anaconda\envs\cursor-factory streamlit run projects/statistical_dashboards/app.py
conda run -p D:\Anaconda\envs\cursor-factory streamlit run projects/rag_knowledge_explorer/app.py
```

### Running Data Guard Scans
Scan incoming metrics for outliers or schema anomalies:
```bash
conda run -p D:\Anaconda\envs\cursor-factory python projects/statistical_dashboards/scripts/data_guard.py
```

## Best Practices
- **Data Cleanliness**: Always route raw stream inputs through the database validation managers first.
- **Rich Visuals**: Follow premium UX design standards with HSL colors and clear responsive metrics.