experimental: import ai-dev-kit skills into experimental/ directory

.github/CODEOWNERS

@@ -6,4 +6,21 @@
 /skills/databricks-model-serving/ @databricks/eng-apps-devex
 /skills/databricks-jobs/ @lennartkats-db @camielstee-db
 /skills/databricks-pipelines/ @lennartkats-db @camielstee-db
+
+# Experimental skills imported from databricks-solutions/ai-dev-kit on a
+# best-effort basis. The merge gate is the same as the rest of the repo
+# (the existing writers from the `*` line above) so changes here can't be
+# self-approved by a-d-k contributors.
+#
+# The top a-d-k contributors (>=10 commits at import time) are granted
+# repo-level write access so they can push branches and open PRs, but they
+# are deliberately NOT Code Owners on this path — that means their review
+# alone does not satisfy the Required-Code-Owner-Review branch protection.
+# They are the natural suggested reviewers for `/experimental/` changes:
+#   @calreynolds @dustinvannoy-db @malcolndandaro @auschoi96 @jacksandom
+#   @QuentinAmbard @NatyraB @jiteshsoni @scottDBX1886 @alexmillerdb
+# All confirmed Databricks employees via Slack lookup at import time
+# (Field Engineering / SSA / Strategy & Execution).
+/experimental/ @lennartkats-db @simonfaltum @databricks/eng-apps-devex
+
 /.github/CODEOWNERS @lennartkats-db @simonfaltum @fjakobs

README.md

@@ -4,25 +4,55 @@ Skills for AI coding assistants (Claude Code, Cursor, etc.) that provide Databri
 
 ## Installation
 
-**For Claude Code:**
-
 ```bash
 databricks experimental aitools install
 ```
 
-This installs skills to `~/.claude/skills/` for use with Claude Code.
+This auto-detects your coding agent(s) and installs the stable skills to the
+right location:
+
+- **Claude Code** → `~/.claude/skills/`
+- **Cursor**, **Codex CLI**, **OpenCode**, **GitHub Copilot**, **Antigravity**
+  → their respective skill directories
 
-**For Cursor:**
+For finer control, use the `aitools skills install` subcommand directly — it
+accepts a positional skill name and an `--experimental` flag (see the
+[Experimental Skills](#experimental-skills) section).
 
-Run this command in chat:
+**For Cursor (plugin marketplace alternative):**
 
 ```text
 /add-plugin databricks-skills
 ```
 
 ## Available Skills
 
-- **databricks-apps** - Build full-stack TypeScript apps on Databricks using AppKit
+Stable skills shipped from [`skills/`](./skills/):
+
+- **databricks-core** — CLI, authentication, profile selection, data exploration. Parent skill for all product skills.
+- **databricks-apps** — Build full-stack TypeScript apps on Databricks using AppKit.
+- **databricks-dabs** — Declarative Automation Bundles (formerly Asset Bundles) for deploying and managing Databricks resources.
+- **databricks-jobs** — Lakeflow Jobs orchestration: task types, triggers, schedules, notifications.
+- **databricks-lakebase** — Lakebase Postgres: projects, branching, autoscaling, synced tables, Data API.
+- **databricks-model-serving** — Model Serving endpoint management, AI Gateway, traffic config.
+- **databricks-pipelines** — Lakeflow Spark Declarative Pipelines (formerly DLT) for batch and streaming.
+- **databricks-serverless-migration** — Migrate classic-compute workloads to serverless compute.
+
+## Experimental Skills
+
+The [`experimental/`](./experimental/) directory contains additional skills
+imported from [databricks-solutions/ai-dev-kit](https://github.com/databricks-solutions/ai-dev-kit)
+on a **best-effort basis**.
+
+- Experimental skills are **not officially supported** — they may be used, but
+  do not follow the same review / quality bar as the stable skills under
+  [`skills/`](./skills/).
+- They are **not installed by default** by `databricks experimental aitools
+  skills install`. Pass `--experimental` to install all of them, or install
+  a specific one by name (with the `-experimental` suffix and the flag —
+  e.g. `databricks-iceberg-experimental --experimental`).
+- See [`experimental/README.md`](./experimental/README.md) for the full list
+  and caveats.
 
 ## Structure
 
@@ -38,21 +68,24 @@ skill-name/
 
 ### Adding New Skills
 
-When experimenting with new skill variations, create a "subskill" that references the main skill and adds specific guidance:
+For a narrower variation of an existing skill, create a subskill that declares
+its parent via frontmatter. This is how the stable skills are organized today
+— each product skill sets `parent: databricks-core`.
 
 ```markdown
 ---
-name: "ai-databricks-apps"
-description: "Databricks apps with AI features"
+name: "databricks-apps-chatbots"
+description: "Databricks apps with chatbot features"
+parent: databricks-apps
 ---
 
-# AI powered Databricks Apps
+# Chatbot Apps
 
-First, load the base databricks-apps skill for foundational guidance.
+**FIRST**: Use the parent `databricks-apps` skill for app development basics.
 
-Then apply these additional patterns:
-- Custom pattern 1
-- Custom pattern 2
+Then apply these patterns:
+- Pattern 1
+- Pattern 2
 ```
 
 This approach:

experimental/README.md

@@ -0,0 +1,126 @@
+> ⚠️ **Experimental — best-effort, not officially supported**
+>
+> The skills in this directory are imported from
+> [databricks-solutions/ai-dev-kit](https://github.com/databricks-solutions/ai-dev-kit)
+> on a best-effort basis. They may be useful, but they are **not officially
+> supported** as part of `databricks-agent-skills`:
+>
+> - They do not follow the same review / quality bar as the skills in
+>   [`../skills/`](../skills/).
+> - They may be out of date relative to upstream `ai-dev-kit`.
+> - The on-disk install path always carries a `-experimental` suffix so
+>   experimental skills never collide with stable skills of the same name
+>   (see the install-path note below).
+> - They are not installed by `databricks experimental aitools skills install`
+>   by default — you have to opt in (see the root README).
+>
+> File issues against this directory in this repo; do not file issues against
+> `ai-dev-kit` for skills installed via `databricks-agent-skills`.
+
+---
+
+# Databricks Skills for Claude Code
+
+Skills that teach Claude Code how to work effectively with Databricks - providing patterns, best practices, and code examples that work with Databricks MCP tools.
+
+## Installation
+
+These experimental skills are **not** installed by default. To install them via the Databricks CLI:
+
+```bash
+# Install all experimental skills at once
+databricks experimental aitools skills install --experimental
+
+# Install a single experimental skill by name (note the -experimental suffix)
+databricks experimental aitools skills install databricks-iceberg-experimental --experimental
+```
+
+The names in this directory don't carry the `-experimental` suffix — that's
+added at install time so the on-disk skills directory unambiguously
+distinguishes experimental from stable. e.g. `databricks-iceberg` in this
+repo installs to `~/.claude/skills/databricks-iceberg-experimental/`.
+
+See the root [README](../README.md) for details on the stable install path.
+
+## Available Skills
+
+### 🤖 AI & Agents
+- **databricks-ai-functions** - Built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_query, ai_forecast, ai_parse_document, and more) with SQL and PySpark patterns, function selection guidance, document processing pipelines, and custom RAG (parse → chunk → index → query)
+- **databricks-agent-bricks** - Knowledge Assistants, Genie Spaces, Supervisor Agents
+- **databricks-genie** - Genie Spaces: create, curate, and query via Conversation API
+- **databricks-mlflow-evaluation** - End-to-end agent evaluation workflow
+- **databricks-unstructured-pdf-generation** - Generate synthetic PDFs for RAG
+- **databricks-vector-search** - Vector similarity search for RAG and semantic search
+
+### 📊 Analytics & Dashboards
+- **databricks-aibi-dashboards** - Databricks AI/BI dashboards (with SQL validation workflow)
+- **databricks-metric-views** - Metric Views for governed metrics
+- **databricks-unity-catalog** - System tables for lineage, audit, billing
+
+### 🔧 Data Engineering
+- **databricks-dbsql** - Databricks SQL warehouse patterns
+- **databricks-iceberg** - Apache Iceberg tables (Managed/Foreign), UniForm, Iceberg REST Catalog, Iceberg Clients Interoperability
+- **databricks-spark-structured-streaming** - Spark Structured Streaming patterns
+- **databricks-synthetic-data-gen** - Realistic test data with Faker
+- **databricks-zerobus-ingest** - Zerobus ingest patterns
+- **spark-python-data-source** - Python data sources for Spark
+
+### 🚀 Development & Deployment
+- **databricks-apps-python** - Databricks apps. Prefers AppKit (TypeScript + React SDK) for new apps; falls back to Python frameworks (Dash, Streamlit, Gradio, Flask, FastAPI, Reflex) when Python is required
+- **databricks-python-sdk** - Python SDK, Connect, CLI, REST API
+- **databricks-execution-compute** - Execute on Databricks compute
+
+> **Use the stable skill instead** for:
+> - **DABs / bundles** — use stable [`databricks-dabs`](../skills/databricks-dabs/)
+> - **Lakebase Postgres** (projects, branching, synced tables, autoscaling) — use stable [`databricks-lakebase`](../skills/databricks-lakebase/)
+> - **CLI auth / profiles / workspace config** — use stable [`databricks-core`](../skills/databricks-core/)
+>
+> Previously experimental copies of these (`databricks-bundles`, `databricks-lakebase-autoscale`, `databricks-config`) were dropped — they duplicated the stable skills without adding new content.
+
+### 📚 Reference
+- **databricks-docs** - Documentation index via llms.txt
+
+## Provenance & sync model
+
+These skills are imported as a snapshot from
+[`databricks-solutions/ai-dev-kit/databricks-skills/`](https://github.com/databricks-solutions/ai-dev-kit/tree/main/databricks-skills).
+
+**Source SHA**: [`7b07f18`](https://github.com/databricks-solutions/ai-dev-kit/commit/7b07f18b6efb7ff0ac011d3fe81b435eb3cd793a)
+on the `experimental` branch of `databricks-solutions/ai-dev-kit` —
+the merge commit of [a-d-k PR #533](https://github.com/databricks-solutions/ai-dev-kit/pull/533)
+into `experimental`. The PR #533 change set, now part of `experimental`:
+
+- `databricks-app-python` → `databricks-apps-python` rename (folder,
+  baselines, manifests, install scripts, cross-skill mentions) so it
+  does not collide with d-a-s's own `databricks-apps`. The other
+  name collisions from this import were resolved by merging or
+  dropping the experimental copy: `databricks-jobs` was merged into
+  the stable skill (TODO #1a), and `databricks-model-serving` was
+  dropped from the import (TODO #1b).
+- `databricks-apps-python/SKILL.md` leads with AppKit (TypeScript +
+  React SDK) as the recommended approach for new apps; Python
+  frameworks (Dash, Streamlit, Gradio, Flask, FastAPI, Reflex) are
+  demoted to an explicit alternative.
+- `install.sh` / `install.ps1` upstream changes wiring a-d-k to
+  install d-a-s skills via a single GitHub tree call (out of scope
+  for this snapshot, not imported here — only `databricks-skills/`
+  content is mirrored).
+
+**Note**: the `experimental` branch of a-d-k previously removed
+`databricks-lakebase-provisioned`, which is why it is not present in
+this import. `databricks-model-serving` and
+`databricks-spark-declarative-pipelines` are intentionally excluded
+from this snapshot — see TODOs #1b and #5 on the import PR.
+
+The full set of paths brought in is tracked by the import commit on
+this branch.
+
+**Transition phase (until `ai-dev-kit` skills are locked):**
+- Source of truth is **upstream `ai-dev-kit`**. New work and bug fixes go there.
+- This directory receives **periodic manual re-syncs** — someone opens a PR
+  to bring drift from upstream into `experimental/`.
+
+**Post-lock (after `ai-dev-kit` skill contributions are stopped):**
+- Source of truth is **this repo**. New work and bug fixes go directly to
+  `experimental/<skill>/`.
+- `ai-dev-kit/databricks-skills/` becomes read-only and points here.

experimental/databricks-agent-bricks/1-knowledge-assistants.md

@@ -0,0 +1,74 @@
+# Knowledge Assistants - Details
+
+For commands, see [SKILL.md](SKILL.md).
+
+## Source Types
+
+Both shapes go inside the `--json` body alongside `display_name` and `description` — see SKILL.md for the full invocation.
+
+### Files (Volume)
+
+```json
+{
+  "display_name": "...",
+  "description": "...",
+  "source_type": "files",
+  "files": {"path": "/Volumes/catalog/schema/volume/folder/"}
+}
+```
+
+Supported formats: PDF, TXT, MD, DOCX.
+
+### Vector Search Index
+
+Use an existing index instead of auto-indexing:
+
+```json
+{
+  "display_name": "...",
+  "description": "...",
+  "source_type": "index",
+  "index": {
+    "index_name": "catalog.schema.my_index",
+    "text_col": "content",
+    "doc_uri_col": "source_url"
+  }
+}
+```
+
+## Updating Content
+
+1. Add/modify/remove files in the Volume
+2. Re-sync: `databricks knowledge-assistants sync-knowledge-sources "knowledge-assistants/{ka_id}"`
+
+## Troubleshooting
+
+**KA stays in CREATING:**
+- Wait up to 10 minutes
+- Check workspace quotas
+- Verify volume path exists
+
+**Documents not indexed:**
+- Check file format (PDF, TXT, MD, DOCX)
+- Verify volume path (trailing slash matters)
+- Check file permissions
+
+**Poor answer quality:**
+- Ensure documents are well-structured
+- Break large documents into smaller files
+- Add clear headings and sections
+
+## Evaluation Questions
+
+When testing a KA, check if the volume or project contains a `pdf_eval_questions.json` file with test questions:
+
+```json
+{
+  "api_errors_guide.pdf": {
+    "question": "What is the solution for error ERR-4521?",
+    "expected_fact": "Call /api/v2/auth/refresh with refresh_token before the 3600s TTL expires"
+  }
+}
+```
+
+Use these questions to validate retrieval accuracy. See [databricks-unstructured-pdf-generation](../databricks-unstructured-pdf-generation/SKILL.md) for generating test PDFs with eval questions.