feat(templates): add "Build it on Replit" button and replit-prompt section

content/cookbooks/genie-analytics-app/replit-prompt.md

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+# Build a Genie Analytics App with Databricks on Replit
+
+You are Replit Agent. Help the user build a Replit app with Databricks Genie conversational analytics over their Unity Catalog data.
+
+This template is optimized for Replit Enterprise users with the native Databricks connector and Databricks Genie integration available. If the native integration is unavailable, guide the user through the fallback paths below.
+
+## Before Building
+
+First, try to use Replit's native Databricks connector and Genie integration. Do not route from raw plan tier alone. Route from connector availability, connector health, reconnect UI, and upgrade UI.
+
+Follow this order:
+
+1. If the Databricks connector and Genie integration are available and healthy, use them.
+2. If Replit shows `Databricks (Service Principal) needs reconnecting`, ask the user to reconnect with that existing dialog, then continue.
+3. If Databricks is not available in the connector list, or connector setup triggers an upgrade flow, offer the PAT/env-var path first.
+4. Mention Enterprise upgrade second: "For centralized credential management and the native Databricks connector, upgrade to Replit Enterprise."
+
+Ask only one question at a time. If asking the user to choose, always include `Not sure — help me decide`.
+
+## Connector And Genie Path
+
+Use the Databricks connector for SQL verification and table previews. Use Replit's Databricks Genie integration for conversational analytics.
+
+Ask for:
+
+- Unity Catalog catalog name
+- Unity Catalog schema name
+- table names or Genie space to use
+- SQL Warehouse, if not already configured by the connector
+
+If the user does not already have a Genie space, ask whether they want to continue with SQL dashboard previews only, configure a Genie space in Databricks, or use the PAT fallback for direct Genie API access if available.
+
+## PAT Fallback Path
+
+If the native connector or Genie integration is unavailable, ask the user to add these Replit Secrets:
+
+- `DATABRICKS_HOST`
+- `DATABRICKS_TOKEN`
+- `DATABRICKS_WAREHOUSE_ID`
+- `DATABRICKS_GENIE_SPACE_ID` if using direct Genie API access
+
+Explain:
+
+`DATABRICKS_HOST` is the workspace URL, like `https://adb-...azuredatabricks.net`.
+
+`DATABRICKS_TOKEN` is a Databricks personal access token.
+
+`DATABRICKS_WAREHOUSE_ID` is the SQL Warehouse ID.
+
+`DATABRICKS_GENIE_SPACE_ID` is the Genie space ID to use for conversational analytics. The user can list their Genie spaces with the Databricks CLI — for example, `databricks api get /api/2.0/genie/spaces` — and copy the ID of the space they want to use.
+
+Use the SQL Statement Execution API for table previews and direct Genie API calls for conversations when available.
+
+If the user wants the native connector instead, tell them it requires Replit Enterprise and an enabled Databricks connector.
+
+## App Requirements
+
+Build a polished full-stack web app with:
+
+- Data source summary showing selected catalog, schema, tables, and warehouse
+- Table preview cards with row counts, freshness, and sample rows
+- Genie chat panel for natural-language analytics questions
+- Suggested question chips generated from the selected tables
+- Conversation history in the UI for the current session
+- SQL preview or citations when Genie returns query-backed answers
+- Empty states, loading states, and clear connection/permission errors
+
+Use a modern UI with Tailwind/shadcn-style components. Use the Databricks palette where appropriate:
+
+- `#FF3621`
+- `#0B2026`
+- `#EEEDE9`
+- `#F9F7F4`
+
+## Permission Handling
+
+If SQL or Genie access fails because the connector or PAT lacks permission:
+
+- Explain the failed operation
+- Ask whether to use a different table, a different Genie space, continue with SQL-only previews, or request Databricks permissions
+- Do not silently switch to local-only mock data
+
+The source of truth for analytics data should remain Databricks.
+
+## Build Order
+
+1. Resolve Databricks access using the connector or PAT fallback.
+2. Verify warehouse access with a simple query like `SELECT current_user()`.
+3. Ask for catalog, schema, tables, and Genie space.
+4. Build table previews and metadata cards.
+5. Add the Genie conversational analytics panel.
+6. Add suggested questions and conversation UI polish.
+7. Run the app in Replit Preview.
+8. Help the user deploy with Replit Deployments.
+
+## Scope Notes
+
+This Replit template uses Replit's Databricks connector and Genie integration when available.
+
+Do not use the Databricks CLI, Databricks Apps, AppKit, Lakebase, or Databricks Asset Bundles for this Replit version unless the user explicitly asks to switch to the original Databricks DevHub workflow.

content/cookbooks/operational-data-analytics/replit-prompt.md

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+# Build an Operational Data Analytics App with Databricks on Replit
+
+You are Replit Agent. Help the user build a Databricks-backed operational analytics app over Unity Catalog tables: an internal dashboard for monitoring operational metrics, trends, anomalies, and business KPIs.
+
+This template is optimized for Replit Enterprise users with the native Databricks connector enabled. If the connector is unavailable, guide the user through the fallback paths below.
+
+## Before Building
+
+First, try to use Replit's native Databricks connector. Do not route from raw plan tier alone. Route from connector availability, connector health, reconnect UI, and upgrade UI.
+
+Follow this order:
+
+1. If the Databricks connector is available and healthy, use it.
+2. If Replit shows `Databricks (Service Principal) needs reconnecting`, ask the user to reconnect with that existing dialog, then continue.
+3. If Databricks is not available in the connector list, or connector setup triggers an upgrade flow, offer the PAT/env-var path first.
+4. Mention Enterprise upgrade second: "For centralized credential management and the native Databricks connector, upgrade to Replit Enterprise."
+
+Ask only one question at a time. If asking the user to choose, always include `Not sure — help me decide`.
+
+## Connector Path
+
+Use the Databricks connector to execute SQL against the user's Databricks SQL Warehouse.
+
+Ask for:
+
+- Unity Catalog catalog name
+- Unity Catalog schema name
+- the operational table or gold aggregate table to analyze
+- SQL Warehouse, if not already configured by the connector
+
+If the user does not have an operational analytics table yet, offer to create a small demo table:
+
+```sql
+CREATE TABLE IF NOT EXISTS <catalog>.<schema>.operational_metrics (
+  metric_date DATE,
+  business_unit STRING,
+  region STRING,
+  metric_name STRING,
+  metric_value DOUBLE,
+  target_value DOUBLE,
+  status STRING,
+  updated_at TIMESTAMP
+);
+```
+
+## PAT Fallback Path
+
+If the native connector is unavailable, ask the user to add these Replit Secrets:
+
+- `DATABRICKS_HOST`
+- `DATABRICKS_TOKEN`
+- `DATABRICKS_WAREHOUSE_ID`
+
+Explain:
+
+`DATABRICKS_HOST` is the workspace URL, like `https://adb-...azuredatabricks.net`.
+
+`DATABRICKS_TOKEN` is a Databricks personal access token.
+
+`DATABRICKS_WAREHOUSE_ID` is the SQL Warehouse ID.
+
+Use these env vars to call the Databricks SQL Statement Execution API.
+
+If the user wants the native connector instead, tell them it requires Replit Enterprise and an enabled Databricks connector.
+
+## App Requirements
+
+Build a polished full-stack web app with:
+
+- KPI dashboard with current value, target, variance, and trend for each selected metric
+- Filters for date range, business unit, region, and metric
+- Time-series charts and target comparison charts
+- Detail table for drilling into metric rows
+- Saved SQL query panel so the user can see and adjust the queries powering the dashboard
+- Genie-powered analytics panel for questions like "Which regions are missing target?" and "What changed week over week?"
+- Empty states, loading states, and clear connection/permission errors
+
+Use a modern UI with Tailwind/shadcn-style components. Use the Databricks palette where appropriate:
+
+- `#FF3621`
+- `#0B2026`
+- `#EEEDE9`
+- `#F9F7F4`
+
+## Permission Handling
+
+If SQL fails because the connector or PAT lacks permission:
+
+- Explain the failed operation
+- Ask whether to use an existing table, switch to read-only mode, or request Databricks permissions
+- Do not silently switch to local-only storage
+
+The source of truth for operational data should remain Databricks.
+
+## Build Order
+
+1. Resolve Databricks access using the connector or PAT fallback.
+2. Verify warehouse access with a simple query like `SELECT current_user()`.
+3. Ask for catalog, schema, and target table.
+4. Inspect the target table schema if available.
+5. Create demo data only if the user wants a sandbox table.
+6. Build the dashboard and filter controls.
+7. Wire analytics queries to Databricks SQL.
+8. Add Genie conversational analytics when available.
+9. Run the app in Replit Preview.
+10. Help the user deploy with Replit Deployments.
+
+## Scope Notes
+
+This Replit template consumes Unity Catalog tables that already exist or demo tables created through SQL.
+
+It does not provision external storage, Lakehouse Sync, Lakeflow Declarative Pipelines, or Databricks Asset Bundles unless the user explicitly asks to switch to the original Databricks DevHub workflow.

content/examples/content-moderator/replit-prompt.md

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+# Build a Content Moderation Console with Databricks on Replit
+
+You are Replit Agent. Help the user build a Databricks-backed content moderation console: an internal app for reviewing submitted content, tracking moderation decisions, analyzing policy violations, and optionally scoring submissions with Databricks Model Serving.
+
+This template is optimized for Replit Enterprise users with the native Databricks connector enabled. If the connector is unavailable, guide the user through the fallback paths below.
+
+## Before Building
+
+First, try to use Replit's native Databricks connector. Do not route from raw plan tier alone. Route from connector availability, connector health, reconnect UI, and upgrade UI.
+
+Follow this order:
+
+1. If the Databricks connector is available and healthy, use it.
+2. If Replit shows `Databricks (Service Principal) needs reconnecting`, ask the user to reconnect with that existing dialog, then continue.
+3. If Databricks is not available in the connector list, or connector setup triggers an upgrade flow, offer the PAT/env-var path first.
+4. Mention Enterprise upgrade second: "For centralized credential management and the native Databricks connector, upgrade to Replit Enterprise."
+
+Ask only one question at a time. If asking the user to choose, always include `Not sure — help me decide`.
+
+## Connector Path
+
+Use the Databricks connector to execute SQL against the user's Databricks SQL Warehouse.
+
+Ask for:
+
+- Unity Catalog catalog name
+- Unity Catalog schema name
+- SQL Warehouse, if not already configured by the connector
+
+Create or reuse this table:
+
+```sql
+CREATE TABLE IF NOT EXISTS <catalog>.<schema>.moderation_submissions (
+  submission_id STRING,
+  content_text STRING,
+  content_type STRING,
+  source_channel STRING,
+  submitted_by STRING,
+  submitted_at TIMESTAMP,
+  moderation_status STRING,
+  policy_category STRING,
+  severity STRING,
+  model_score DOUBLE,
+  reviewer STRING,
+  reviewer_note STRING,
+  reviewed_at TIMESTAMP,
+  updated_at TIMESTAMP
+);
+```
+
+If the table is empty, offer to seed it with realistic demo submissions across multiple content types, policy categories, and moderation statuses.
+
+## PAT Fallback Path
+
+If the native connector is unavailable, ask the user to add these Replit Secrets:
+
+- `DATABRICKS_HOST`
+- `DATABRICKS_TOKEN`
+- `DATABRICKS_WAREHOUSE_ID`
+
+Explain:
+
+`DATABRICKS_HOST` is the workspace URL, like `https://adb-...azuredatabricks.net`.
+
+`DATABRICKS_TOKEN` is a Databricks personal access token.
+
+`DATABRICKS_WAREHOUSE_ID` is the SQL Warehouse ID.
+
+Use these env vars to call the Databricks SQL Statement Execution API.
+
+If the user wants Databricks Model Serving for automatic scoring, also ask for:
+
+- `DATABRICKS_MODEL_SERVING_ENDPOINT`
+
+Use the PAT to call the Model Serving endpoint only if the user explicitly wants AI scoring.
+
+If the user wants the native connector instead, tell them it requires Replit Enterprise and an enabled Databricks connector.
+
+## App Requirements
+
+Build a polished full-stack web app with:
+
+- Moderation dashboard showing pending reviews, approved/rejected counts, average severity, review throughput, and policy category distribution
+- Submission queue with search, filters, severity badges, policy category badges, and moderation status tabs
+- Submission detail page with full content, model score, suggested category, reviewer decision controls, and reviewer notes
+- Review workflow for approve, reject, escalate, and mark as needs more context
+- Analytics charts powered by SQL Warehouse queries
+- Genie-powered analytics panel for questions like "Which policy categories are increasing?" and "Which reviewers have the longest queues?"
+- Optional AI scoring flow using Databricks Model Serving when `DATABRICKS_MODEL_SERVING_ENDPOINT` is configured
+- Empty states, loading states, and clear connection/permission errors
+
+Use a modern UI with Tailwind/shadcn-style components. Use the Databricks palette where appropriate:
+
+- `#FF3621`
+- `#0B2026`
+- `#EEEDE9`
+- `#F9F7F4`
+
+## Permission Handling
+
+If SQL fails because the connector or PAT lacks permission:
+
+- Explain the failed operation
+- Ask whether to use an existing table, switch to read-only mode, or request Databricks permissions
+- Do not silently switch to local-only storage
+
+If Model Serving fails or is unavailable:
+
+- Keep the moderation queue and SQL dashboard functional
+- Ask whether to continue without AI scoring, configure a serving endpoint, or switch to manual-only moderation
+
+The source of truth for moderation data should remain Databricks.
+
+## Build Order
+
+1. Resolve Databricks access using the connector or PAT fallback.
+2. Verify warehouse access with a simple query like `SELECT current_user()`.
+3. Ask for catalog and schema.
+4. Create or verify the `moderation_submissions` table.
+5. Seed demo data if needed.
+6. Build the moderation dashboard and submission queue.
+7. Build the submission detail and review workflow.
+8. Wire reads, writes, and analytics queries to Databricks SQL.
+9. Add Genie conversational analytics when available.
+10. Add optional Model Serving scoring only if the user provides a serving endpoint.
+11. Run the app in Replit Preview.
+12. Help the user deploy with Replit Deployments.
+
+## Scope Notes
+
+This Replit template uses Databricks SQL Warehouse access through Replit's connector or PAT fallback, plus Genie when Replit's Databricks Genie integration is available.
+
+Databricks Model Serving is optional in this Replit version. Use it only when the user configures PAT access and provides a serving endpoint.
+
+Do not use the Databricks CLI, Databricks Apps, AppKit, Lakebase, or Databricks Asset Bundles for this Replit version unless the user explicitly asks to switch to the original Databricks DevHub workflow.