Streamlit Expert

Streamlit Web application development expert skill. Provides guidance on OIDC authentication (st.login/st.logout/st.user), secrets management, data visualization with Plotly/Altair, performance optimization with caching, and modern Streamlit features (v1.42-1.52+). Use this skill when building Streamlit apps, implementing user authentication, creating data dashboards, or optimizing app performance. Triggers include “streamlit app”, “st.login”, “data dashboard”, “streamlit authentication”, “streamlit visualization”.

No API Required

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

Streamlit Web application development expert skill supporting the latest features from v1.42 to v1.52+ (2025-2026). Provides comprehensive guidance on:

  • Authentication: Native OIDC authentication with st.login(), st.logout(), st.user
  • Data Visualization: Optimal library selection (Plotly, Altair, native charts) and performance tuning
  • Secrets Management: Secure credential handling with st.secrets
  • Performance Optimization: Caching strategies, large dataset handling, session state management
  • Modern Features: Custom themes, layout containers, multipage apps, Custom Components v2

2. Prerequisites

  • API Key: None required
  • Python 3.9+ recommended

3. Quick Start 

User Request
├── "Add authentication" → Authentication Workflow
├── "Create dashboard/visualization" → Visualization Workflow
├── "App is slow/optimize" → Performance Optimization Workflow
├── "New Streamlit app" → Project Setup Workflow
└── "Deploy app" → Deployment Workflow

4. How It Works 

User Request
├── "Add authentication" → Authentication Workflow
├── "Create dashboard/visualization" → Visualization Workflow
├── "App is slow/optimize" → Performance Optimization Workflow
├── "New Streamlit app" → Project Setup Workflow
└── "Deploy app" → Deployment Workflow

5. Usage Examples

  • Building new Streamlit applications from scratch
  • Implementing user authentication with OIDC providers (Google, Microsoft, Okta, Auth0)
  • Creating data visualization dashboards
  • Optimizing Streamlit app performance
  • Managing secrets and credentials securely
  • Implementing modern Streamlit features (v1.42+)

6. Understanding the Output

  • A structured response or artifact aligned to the skill’s workflow.
  • Reference support from 4 guide file(s).
  • Reusable output that can be reviewed, refined, and incorporated into a wider project workflow.

7. Tips & Best Practices

  • Begin with the smallest realistic sample input so you can validate the workflow before scaling up.
  • Keep skills/streamlit-expert/SKILL.md open while working; it remains the authoritative source for the full procedure.
  • Review the most relevant reference files first instead of scanning every guide: visualization_best_practices.md, release_notes_summary.md, authentication_guide.md.
  • Preserve intermediate outputs so you can explain assumptions, diffs, and follow-up actions clearly.

8. Combining with Other Skills

  • Combine this skill with adjacent skills in the same category when the work spans planning, implementation, and review.
  • Browse the broader category for neighboring workflows: category index.
  • Use the English skill catalog when you need to chain this workflow into a larger end-to-end process.

9. Troubleshooting

  • Re-check prerequisites first: missing runtime dependencies and unsupported file formats are the most common failures.
  • If a helper script is involved, run it with a minimal sample input before applying it to a full dataset or repository.
  • Compare your input shape against the reference files to confirm expected fields, sections, or metadata are present.
  • Confirm the expected Python version and required packages are installed in the active environment.

10. Reference

References:

  • skills/streamlit-expert/references/authentication_guide.md
  • skills/streamlit-expert/references/performance_optimization.md
  • skills/streamlit-expert/references/release_notes_summary.md
  • skills/streamlit-expert/references/visualization_best_practices.md