メニュー
Build production-grade Streamlit apps. Used when creating, editing, debugging, or deploying Streamlit applications. Routes to specialized sub-skills for performance, layouts, design, data display, and more.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | developing-with-streamlit |
| description | Build production-grade Streamlit apps. Used when creating, editing, debugging, or deploying Streamlit applications. Routes to specialized sub-skills for performance, layouts, design, data display, and more. |
A collection of skills for building production-grade Streamlit apps. Each skill focuses on a specific aspect of Streamlit development.
Activate these skills when:
Performance issues or slow apps? → optimizing-streamlit-performance
Building a new UI? → choosing-streamlit-selection-widgets + using-streamlit-layouts
Building a dashboard? → building-streamlit-dashboards + displaying-streamlit-data
Making it look good? → improving-streamlit-design
Formatting text with markdown? → using-streamlit-markdown
Multi-page architecture? → building-streamlit-multipage-apps
Customizing appearance or creating a custom theme? → creating-streamlit-themes
Setting up a project? → setting-up-streamlit-environment
App getting complex? → organizing-streamlit-code
Connecting to Snowflake? → connecting-streamlit-to-snowflake
Building a chatbot or AI assistant? → building-streamlit-chat-ui
Need features not in core Streamlit? → using-streamlit-custom-components
Using the Streamlit CLI? → using-streamlit-cli
State management and session state? → using-streamlit-session-state
| Skill | Covers |
|---|---|
| building-streamlit-chat-ui | Chat interfaces, streaming responses, message history |
| building-streamlit-dashboards | KPI cards, metrics, dashboard layouts |
| building-streamlit-multipage-apps | Page structure, navigation, shared state |
| choosing-streamlit-selection-widgets | Selectbox vs radio vs segmented control vs pills vs multiselect |
| connecting-streamlit-to-snowflake | st.connection, query caching, credentials |
| creating-streamlit-themes | Theme configuration, colors, fonts, light/dark modes, professional brand alignment, CSS avoidance |
| displaying-streamlit-data | Dataframes, column config, charts |
| improving-streamlit-design | Icons, badges, colored text, visual polish |
| optimizing-streamlit-performance | Caching, fragments, forms, static vs dynamic widgets |
| organizing-streamlit-code | When to split into modules, separating UI from logic |
| setting-up-streamlit-environment | Python environment, dependency management |
| using-streamlit-custom-components | Third-party components from the community |
| using-streamlit-cli | CLI commands, running apps |
| using-streamlit-layouts | Sidebar, columns, containers, tabs, expanders, dialogs, alignment, spacing |
| using-streamlit-markdown | Colored text, badges, icons, LaTeX, and all markdown features |
| using-streamlit-session-state | Session state, widget keys, callbacks, state persistence |
How to custom-style a Streamlit application with a modern, stable theming stack — reusable theme TOML files, self-hosted fonts, light/dark modes, sidebar theming, chart palettes, shared page bootstrap, and scoped CSS for custom component variants. Use this skill PROACTIVELY whenever the user wants to style, theme, brand, or customize the appearance of a Streamlit app — including changing colors, fonts, buttons, sidebar look, dark mode, chart colors, or adding custom CSS. Also use when the user mentions config.toml theming, Streamlit design systems, or asks how to make a Streamlit app look professional/branded. Even if the user only asks about one aspect (e.g. "change the sidebar color"), apply this skill because the answer depends on which styling layer is appropriate.
Quick reference for building full-stack Databricks Apps with apx (React + FastAPI). Use when working on apx projects, creating routes, adding components, or managing dev servers.
Create and manage Databricks Agent Bricks: Knowledge Assistants (KA) for document Q&A, Genie Spaces for SQL exploration, and Multi-Agent Supervisors (MAS) for multi-agent orchestration. Use when building conversational AI applications on Databricks.
Create and configure Databricks Asset Bundles (DABs) with best practices for multi-environment deployments. Use when working with: (1) Creating new DAB projects, (2) Adding resources (dashboards, pipelines, jobs, alerts), (3) Configuring multi-environment deployments, (4) Setting up permissions, (5) Deploying or running bundle resources
Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads.
Deploy and query Databricks Model Serving endpoints. Use when (1) deploying MLflow models or AI agents to endpoints, (2) creating ChatAgent/ResponsesAgent agents, (3) integrating UC Functions or Vector Search tools, (4) querying deployed endpoints, (5) checking endpoint status. Covers classical ML models, custom pyfunc, and GenAI agents.
