address Dustin's review

- Drop the -experimental suffix model entirely. Skills install under their
  plain names; the install dir is `~/.claude/skills/<name>/`. Stable+experimental
  collisions are resolved upstream by renaming (not by suffixing), and the
  manifest generator raises if a collision shows up.
- Update README install instructions to the new top-level
  `databricks aitools install [name] --experimental` surface (was the legacy
  `databricks experimental aitools skills install ...` path).
- Trim the experimental/README "Provenance & sync model" section per Dustin's
  L113/L126 asks — the long-term deprecation plan lives in ai-dev-kit when
  it's ready, not here.
- Apply Dustin's L78 wording suggestion for the "previously experimental"
  callout.
- Add @cankoklu-db and @yogesh-dbx as Code Owners on /experimental/.
- Fix the databricks-pipelines manifest description: "Databricks Spark
  Declarative Pipelines (SDP) for ETL and streaming".
- Drop the broken n8n-to-databricks cross-reference in
  databricks-ai-functions/4-document-processing-pipeline.md (the referenced
  skill does not exist).

Paired with the cli-side suffix removal in databricks/cli#5243.

Co-authored-by: Isaac

Author: jamesbroadhead

.github/CODEOWNERS

@@ -13,6 +13,6 @@
 # Required-Code-Owner-Review branch protection alongside the d-a-s
 # maintainers. All confirmed Databricks employees via Slack lookup at
 # import time (Field Engineering / SSA / Strategy & Execution).
-/experimental/ @lennartkats-db @simonfaltum @databricks/eng-apps-devex @calreynolds @dustinvannoy-db @malcolndandaro @auschoi96 @jacksandom @QuentinAmbard @NatyraB @jiteshsoni @scottDBX1886 @alexmillerdb
+/experimental/ @lennartkats-db @simonfaltum @databricks/eng-apps-devex @calreynolds @dustinvannoy-db @malcolndandaro @auschoi96 @jacksandom @QuentinAmbard @NatyraB @jiteshsoni @scottDBX1886 @alexmillerdb @cankoklu-db @yogesh-dbx
 
 /.github/CODEOWNERS @lennartkats-db @simonfaltum @fjakobs

README.md

@@ -47,10 +47,10 @@ 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`).
+- They are **not installed by default** by `databricks aitools install`.
+  Pass `--experimental` to install all of them, or install a specific one
+  by name (with the `--experimental` flag — e.g. `databricks aitools install
+  databricks-iceberg --experimental`).
 - See [`experimental/README.md`](./experimental/README.md) for the full list
   and caveats.
 

experimental/README.md

@@ -8,11 +8,8 @@
 > - 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).
+> - They are not installed by `databricks aitools 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`.
@@ -29,17 +26,12 @@ These experimental skills are **not** installed by default. To install them via
 
 ```bash
 # Install all experimental skills at once
-databricks experimental aitools skills install --experimental
+databricks aitools install --experimental
 
-# Install a single experimental skill by name (note the -experimental suffix)
-databricks experimental aitools skills install databricks-iceberg-experimental --experimental
+# Install a single experimental skill by name
+databricks aitools install databricks-iceberg --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
@@ -75,52 +67,18 @@ See the root [README](../README.md) for details on the stable install path.
 > - **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.
+> Previously experimental copies of these (`databricks-bundles`, `databricks-lakebase-autoscale`, `databricks-config`) were already merged with the stable skills.
 
 ### 📚 Reference
 - **databricks-docs** - Documentation index via llms.txt
 
-## Provenance & sync model
+## Provenance
 
 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.
+on the `experimental` branch of `databricks-solutions/ai-dev-kit`.
+
+While `ai-dev-kit` is the upstream source, this directory receives periodic
+manual re-syncs.

experimental/databricks-ai-functions/4-document-processing-pipeline.md

@@ -2,8 +2,6 @@
 
 End-to-end patterns for building batch document processing pipelines using AI Functions in a Lakeflow Declarative Pipeline (DLT). Covers function selection, `config.yml` centralization, error handling, and guidance on near-real-time variants with DSPy or LangChain.
 
-> For workflow migration context (e.g., migrating from n8n, LangChain, or other orchestration tools), see the companion skill `n8n-to-databricks`.
-
 ---
 
 ## Function Selection for Document Pipelines

manifest.json

@@ -1,6 +1,6 @@
 {
   "version": "2",
-  "updated_at": "2026-05-19T14:54:40Z",
+  "updated_at": "2026-05-20T15:27:57Z",
   "skills": {
     "databricks-apps": {
       "version": "0.1.1",
@@ -107,7 +107,7 @@
     },
     "databricks-pipelines": {
       "version": "0.1.0",
-      "description": "Databricks Pipelines (DLT) for ETL and streaming",
+      "description": "Databricks Spark Declarative Pipelines (SDP) for ETL and streaming",
       "repo_dir": "skills",
       "updated_at": "2026-05-12T15:39:50Z",
       "files": [
@@ -187,7 +187,7 @@
       "version": "0.0.1",
       "description": "Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_query, ai_forecast) to add AI capabilities directly to SQL and PySpark pipelines without managing model endpoints. Also covers document parsing and building custom RAG pipelines (parse \u2192 chunk \u2192 index \u2192 query).",
       "repo_dir": "experimental",
-      "updated_at": "2026-05-15T09:44:54Z",
+      "updated_at": "2026-05-20T15:27:46Z",
       "files": [
         "1-task-functions.md",
         "2-ai-query.md",

scripts/skills.py

@@ -41,7 +41,7 @@
         "description": "Databricks Model Serving endpoint management",
     },
     "databricks-pipelines": {
-        "description": "Databricks Pipelines (DLT) for ETL and streaming",
+        "description": "Databricks Spark Declarative Pipelines (SDP) for ETL and streaming",
     },
     "databricks-serverless-migration": {
         "description": "Migrate Databricks workloads from classic compute to serverless compute, including compatibility checks and concrete fixes",
@@ -326,10 +326,9 @@ def _add_skill(skills: dict, entry: tuple[str, dict]) -> None:
     name, skill = entry
     if name in skills:
         # Stable + experimental copies of the same logical skill can't coexist
-        # in one map. The cli applies a "-experimental" suffix to install-side
-        # keys at install time, but the manifest itself stores the natural
-        # repo-dir name. If a collision shows up, resolve it upstream (rename
-        # one of the two) before regenerating.
+        # in one map. The cli installs each entry under its plain skill name,
+        # so a future collision must be resolved upstream (rename one of the
+        # two, or merge them) before regenerating.
         raise ValueError(
             f"Duplicate skill name '{name}': present under both '{STABLE_REPO_DIR}/' "
             f"and '{EXPERIMENTAL_REPO_DIR}/'. Rename one to disambiguate."