docs(databricks-dabs): port DAB content vendored in devhub

skills/databricks-dabs/references/bundle-structure.md

@@ -99,6 +99,54 @@ resources:
         timezone_id: 'America/Los_Angeles'
 ```
 
+### Job Resource (Shared Classic Cluster)
+
+When multiple tasks should reuse the same cluster, declare it once under `job_clusters` and reference it via `job_cluster_key`:
+
+```yaml
+resources:
+  jobs:
+    sample_job:
+      name: sample_job
+      tasks:
+        - task_key: notebook_task
+          notebook_task:
+            notebook_path: ../src/sample_notebook.ipynb
+          job_cluster_key: job_cluster
+          libraries:
+            - whl: ../dist/*.whl
+
+        - task_key: main_task
+          depends_on:
+            - task_key: notebook_task
+          python_wheel_task:
+            package_name: my_project
+            entry_point: main
+          job_cluster_key: job_cluster
+          libraries:
+            - whl: ../dist/*.whl
+
+      job_clusters:
+        - job_cluster_key: job_cluster
+          new_cluster:
+            spark_version: 16.4.x-scala2.12
+            node_type_id: i3.xlarge
+            data_security_mode: SINGLE_USER
+            autoscale:
+              min_workers: 1
+              max_workers: 4
+```
+
+## Registered Model Resources
+
+```yaml
+resources:
+  registered_models:
+    customer_churn:
+      name: '${var.catalog}.${var.schema}.customer_churn_model'
+      description: 'Customer churn prediction model'
+```
+
 ## Volume Resources
 
 ```yaml
@@ -177,6 +225,23 @@ databricks bundle generate app <app-name>
 
 DABs supports schemas, models, experiments, clusters, warehouses, etc. Use `databricks bundle schema` to inspect schemas.
 
+## Substitutions
+
+Substitutions are resolved at deploy time and are usable in any string field across `databricks.yml`, resource files, and variable defaults.
+
+| Substitution                            | Resolves to                                            |
+| --------------------------------------- | ------------------------------------------------------ |
+| `${var.my_variable}`                    | User-defined variable from `variables:` block          |
+| `${bundle.name}`                        | The bundle's `bundle.name`                             |
+| `${bundle.target}`                      | The active target (`dev`, `staging`, `prod`, …)        |
+| `${workspace.current_user.userName}`    | Deployer's email                                       |
+| `${workspace.current_user.short_name}`  | Deployer's short name (handle before `@`)              |
+| `${workspace.file_path}`                | Bundle's workspace file path                           |
+| `${resources.jobs.<key>.id}`            | ID of another job in the same bundle                   |
+| `${resources.pipelines.<key>.id}`       | ID of another pipeline in the same bundle              |
+
+Variables themselves are declared in `databricks.yml` (with optional `default:` or `lookup:`) and overridden per target.
+
 ## Key Principles
 
 1. **Path resolution**: `../src/` in resources/\*.yml, `./src/` in databricks.yml

skills/databricks-dabs/references/deploy-and-run.md

@@ -1,5 +1,39 @@
 # Deploy and Run Declarative Automation Bundles
 
+## Initialization
+
+Start a new bundle interactively:
+
+```bash
+databricks bundle init
+```
+
+Built-in templates:
+
+| Template             | Use for                                            |
+| -------------------- | -------------------------------------------------- |
+| `default-python`     | Python project with jobs and a pipeline            |
+| `default-sql`        | SQL project with jobs                              |
+| `default-scala`      | Scala/Java project                                 |
+| `lakeflow-pipelines` | Lakeflow Declarative Pipelines (Python or SQL)     |
+| `dbt-sql`            | dbt integration                                    |
+| `default-minimal`    | Minimal bundle skeleton                            |
+
+Pass a template name or a Git URL pointing at a template directory to skip the interactive picker.
+
+## Generate from Existing Resources
+
+If a workspace already has the resource, generate its bundle YAML instead of writing it by hand:
+
+```bash
+databricks bundle generate job <job-id>
+databricks bundle generate pipeline <pipeline-id>
+databricks bundle generate dashboard <dashboard-id>
+databricks bundle generate app <app-name>
+```
+
+This writes a resource file under `resources/` plus any referenced source assets.
+
 ## Validation
 
 Validate bundle configuration:
@@ -32,6 +66,13 @@ Run resources:
 
 View status: `bundle summary`
 
+## Destroy
+
+`bundle destroy` removes everything the bundle previously deployed to the target workspace. It is destructive; confirm the target before running it.
+
+- `bundle destroy -t dev`
+- `bundle destroy -t prod`
+
 ## Monitoring and Logs
 
 ```bash
@@ -56,3 +97,5 @@ databricks apps logs <app-name> --profile <profile-name>
 | **App not starting after deploy**  | Apps require `databricks bundle run <resource_key>` to start            |
 | **App env vars not working**       | Environment variables go in `app.yaml` (source dir), not databricks.yml |
 | **Debugging any app issue**        | First step: `databricks apps logs <app-name>`                           |
+| **Variable shows as `${var.name}` literal** | Variable not declared in `databricks.yml` `variables:`, missing from the active target, or wrong syntax (use `${var.<name>}`) |
+| **Validation errors unclear**      | Re-run with `databricks bundle validate --strict --debug`                |