feat: add reusable-ip skill for JIT access to databricks-field-eng/reusable-ip-ai

databricks-skills/databricks-reusable-ip/SKILL.md

@@ -0,0 +1,38 @@
+---
+name: databricks-reusable-ip
+description: "Production-ready Databricks reference implementations (agent deployment, model serving, CI/CD, Genie Spaces, Lakebase, DABs, A/B testing, Claude Code). TRIGGER: when implementing a new Databricks pattern or porting a reference implementation. ACTION: fetch llms.txt index first, then fetch only relevant files."
+---
+
+# Reusable IP — Databricks Reference Implementations
+
+## When to Use
+
+When implementing a new Databricks pattern or porting a reference implementation, check this repo
+for existing solutions. Covers: agent deployment, model serving (concurrent PyFunc), CI/CD,
+Genie Spaces, Lakebase, Databricks Asset Bundles (DABs), A/B testing, and Claude Code
+integration.
+
+## JIT Fetch Protocol
+
+**Step 1: Always fetch the index first**
+```bash
+gh api repos/databricks-field-eng/reusable-ip-ai/contents/llms.txt \
+  --jq '.content' | base64 -d
+```
+
+If this command fails (authentication error, access denied, or file not found), stop and inform
+the user that the reusable-ip-ai repo is inaccessible. Do not proceed with this skill.
+
+**Step 2: Identify relevant files** from the descriptions (not filenames alone).
+If nothing is relevant, proceed without fetching further.
+
+**Step 3: Fetch only the files you need**
+```bash
+gh api repos/databricks-field-eng/reusable-ip-ai/contents/PATH/TO/FILE \
+  --jq '.content' | base64 -d
+```
+
+**Rules:**
+- Always fetch `llms.txt` first — do not guess file paths
+- Fetch MINIMUM files (1–3). Fetch additional files incrementally only if needed
+- Do not dump the full directory tree

databricks-skills/install_skills.sh

@@ -42,7 +42,7 @@ MLFLOW_REPO_RAW_URL="https://raw.githubusercontent.com/mlflow/skills"
 MLFLOW_REPO_REF="main"
 
 # Databricks skills (hosted in this repo)
-DATABRICKS_SKILLS="databricks-agent-bricks databricks-aibi-dashboards databricks-asset-bundles databricks-app-python databricks-config databricks-dbsql databricks-docs databricks-genie databricks-iceberg databricks-jobs databricks-lakebase-autoscale databricks-lakebase-provisioned databricks-metric-views databricks-mlflow-evaluation databricks-model-serving databricks-parsing databricks-python-sdk databricks-spark-declarative-pipelines databricks-spark-structured-streaming databricks-synthetic-data-gen databricks-unity-catalog databricks-unstructured-pdf-generation databricks-vector-search databricks-zerobus-ingest spark-python-data-source"
+DATABRICKS_SKILLS="databricks-agent-bricks databricks-aibi-dashboards databricks-asset-bundles databricks-app-python databricks-config databricks-dbsql databricks-docs databricks-genie databricks-iceberg databricks-jobs databricks-lakebase-autoscale databricks-lakebase-provisioned databricks-metric-views databricks-mlflow-evaluation databricks-model-serving databricks-parsing databricks-python-sdk databricks-reusable-ip databricks-spark-declarative-pipelines databricks-spark-structured-streaming databricks-synthetic-data-gen databricks-unity-catalog databricks-unstructured-pdf-generation databricks-vector-search databricks-zerobus-ingest spark-python-data-source"
 
 # MLflow skills (fetched from mlflow/skills repo)
 MLFLOW_SKILLS="agent-evaluation analyze-mlflow-chat-session analyze-mlflow-trace instrumenting-with-mlflow-tracing mlflow-onboarding querying-mlflow-metrics retrieving-mlflow-traces searching-mlflow-docs"
@@ -73,6 +73,7 @@ get_skill_description() {
         "databricks-iceberg") echo "Apache Iceberg - managed tables, UniForm, IRC, Snowflake interop, migration" ;;
         "databricks-jobs") echo "Databricks Lakeflow Jobs - workflow orchestration" ;;
         "databricks-python-sdk") echo "Databricks Python SDK, Connect, and REST API" ;;
+        "databricks-reusable-ip") echo "JIT access to reference implementations: agents, model serving, CI/CD, DABs, A/B testing" ;;
         "databricks-unity-catalog") echo "System tables for lineage, audit, billing" ;;
         "databricks-lakebase-autoscale") echo "Lakebase Autoscale - managed PostgreSQL with autoscaling" ;;
         "databricks-lakebase-provisioned") echo "Lakebase Provisioned - data connections and reverse ETL" ;;