dashboard-view-builder
Constructs and maintains complex statistical dashboards and data visualization UIs.
Install
mkdir -p .claude/skills/dashboard-view-builder && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/17802" && unzip -o skill.zip -d .claude/skills/dashboard-view-builder && rm skill.zipInstalls to .claude/skills/dashboard-view-builder
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Building and managing premium statistical dashboards, RAG explorer UIs, warehouse log monitors, and real-time visualization centers.Key capabilities
- →Develops interactive dashboards using Streamlit/Next.js
- →Manages data for RAG explorer centers
- →Implements custom connectors for news, financial, and economic data
- →Deploys interactive knowledge explorers
- →Scans incoming metrics for outliers or schema anomalies
- →Ensures data cleanliness through database validation managers
How it works
The skill enables the development, hosting, and data management of interactive dashboards and RAG explorer centers, including custom connectors and data validation.
Inputs & outputs
When to use dashboard-view-builder
- →Building a RAG knowledge explorer UI
- →Creating warehouse inventory dashboards
- →Setting up real-time monitoring visualizations
- →Managing dashboard business logic
About this skill
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:
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:
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.
When not to use it
- →When modifying statistical dashboards
- →When writing custom connectors
- →When implementing data guards
Prerequisites
Limitations
- →Requires Streamlit, Next.js, and web dependency libraries
- →Requires a Conda environment to be initialized
- →Data cleanliness relies on routing raw stream inputs through database validation managers
How it compares
This skill provides a structured approach to building premium statistical dashboards and RAG explorer UIs with integrated data management and validation, unlike general web development.
Compared to similar skills
dashboard-view-builder side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| dashboard-view-builder (this skill) | 0 | 23d | Review | Advanced |
| streamlit | 86 | 9mo | No flags | Intermediate |
| dashboard-build | 6 | 1mo | Review | Advanced |
| developing-with-streamlit | 0 | 4mo | No flags | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
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