From 5954d106be42709e06e1ee747e6e34885cb6e416 Mon Sep 17 00:00:00 2001 From: James Broadhead Date: Mon, 25 May 2026 13:55:59 +0000 Subject: [PATCH 1/3] skills: promote databricks-vector-search to stable Per Lennart's audit on #73: vector-search is no longer considered experimental in the Genie Code world. Promote it from `experimental/databricks-vector-search/` to `skills/databricks-vector-search/`. Changes: - `git mv experimental/databricks-vector-search skills/databricks-vector-search`. - Move the 4 top-level reference files into `references/` for layout consistency with other stable skills (apps, lakebase, pipelines). - SKILL.md: add `parent: databricks-core`, `metadata.version: "0.1.0"`, and the standard "FIRST: Use the parent databricks-core skill" prelude. Rewrite 10 path references for the new `references/.md` locations. - scripts/skills.py: add `databricks-vector-search` to `SKILL_METADATA` with a stable description. - Update root README "Available Skills" list to include it; remove from experimental/README list. Manifest regenerated. `python3 scripts/skills.py validate` passes. Once this lands, the matching change in the a-d-k tombstone PR (databricks-solutions/ai-dev-kit#546) is to drop the `--experimental` flag from the vector-search tombstone's install command. I'll update that PR directly. Co-authored-by: Isaac --- README.md | 1 + experimental/README.md | 1 - manifest.json | 84 +++++++++--------- scripts/skills.py | 3 + .../databricks-vector-search/SKILL.md | 15 ++-- .../agents/openai.yaml | 0 .../assets/databricks.png | Bin .../assets/databricks.svg | 0 .../references}/end-to-end-rag.md | 0 .../references}/index-types.md | 0 .../references}/search-modes.md | 0 .../troubleshooting-and-operations.md | 0 12 files changed, 56 insertions(+), 48 deletions(-) rename {experimental => skills}/databricks-vector-search/SKILL.md (92%) rename {experimental => skills}/databricks-vector-search/agents/openai.yaml (100%) rename {experimental => skills}/databricks-vector-search/assets/databricks.png (100%) rename {experimental => skills}/databricks-vector-search/assets/databricks.svg (100%) rename {experimental/databricks-vector-search => skills/databricks-vector-search/references}/end-to-end-rag.md (100%) rename {experimental/databricks-vector-search => skills/databricks-vector-search/references}/index-types.md (100%) rename {experimental/databricks-vector-search => skills/databricks-vector-search/references}/search-modes.md (100%) rename {experimental/databricks-vector-search => skills/databricks-vector-search/references}/troubleshooting-and-operations.md (100%) diff --git a/README.md b/README.md index 5dfb51b..b9132d0 100644 --- a/README.md +++ b/README.md @@ -37,6 +37,7 @@ Stable skills shipped from [`skills/`](./skills/): - **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. +- **databricks-vector-search** — Vector Search endpoints + indexes for RAG and semantic search. ## Experimental Skills diff --git a/experimental/README.md b/experimental/README.md index f56cdda..dcab58c 100644 --- a/experimental/README.md +++ b/experimental/README.md @@ -41,7 +41,6 @@ See the root [README](../README.md) for details on the stable install path. - **databricks-agent-bricks** - Knowledge Assistants, Genie Spaces, Supervisor Agents - **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) diff --git a/manifest.json b/manifest.json index f0fe8fe..a7103c6 100644 --- a/manifest.json +++ b/manifest.json @@ -1,12 +1,12 @@ { "version": "2", - "updated_at": "2026-05-22T20:18:49Z", + "updated_at": "2026-05-25T13:55:45Z", "skills": { "databricks-apps": { "version": "0.1.2", "description": "Databricks Apps development and deployment (evaluates analytics vs synced tables data access)", "repo_dir": "skills", - "updated_at": "2026-05-22T15:54:04Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -33,7 +33,7 @@ "version": "0.1.0", "description": "Core Databricks skill for CLI, auth, and data exploration", "repo_dir": "skills", - "updated_at": "2026-05-15T09:44:24Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -48,7 +48,7 @@ "version": "0.0.1", "description": "Declarative Automation Bundles (DABs) for deploying and managing Databricks resources", "repo_dir": "skills", - "updated_at": "2026-05-12T15:39:50Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -66,7 +66,7 @@ "version": "0.2.0", "description": "Develop and deploy Lakeflow Jobs on Databricks via DABs, Python SDK, or the CLI \u2014 covers all task types, triggers, notifications, and worked examples", "repo_dir": "skills", - "updated_at": "2026-05-22T15:54:01Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -82,7 +82,7 @@ "version": "0.1.0", "description": "Databricks Lakebase Postgres: projects, scaling, connectivity, synced tables, and Data API", "repo_dir": "skills", - "updated_at": "2026-05-22T15:54:04Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -101,7 +101,7 @@ "version": "0.1.0", "description": "Databricks Model Serving endpoint management", "repo_dir": "skills", - "updated_at": "2026-05-22T15:54:04Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -114,7 +114,7 @@ "version": "0.1.0", "description": "Databricks Spark Declarative Pipelines (SDP) for ETL and streaming", "repo_dir": "skills", - "updated_at": "2026-05-12T15:39:50Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -161,7 +161,7 @@ "version": "0.1.0", "description": "Migrate Databricks workloads from classic compute to serverless compute, including compatibility checks and concrete fixes", "repo_dir": "skills", - "updated_at": "2026-05-12T15:39:50Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -174,11 +174,27 @@ "references/streaming-migration.md" ] }, + "databricks-vector-search": { + "version": "0.1.0", + "description": "Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns", + "repo_dir": "skills", + "updated_at": "2026-05-25T13:54:43Z", + "files": [ + "SKILL.md", + "agents/openai.yaml", + "assets/databricks.png", + "assets/databricks.svg", + "references/end-to-end-rag.md", + "references/index-types.md", + "references/search-modes.md", + "references/troubleshooting-and-operations.md" + ] + }, "databricks-agent-bricks": { "version": "0.0.1", "description": "Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).", "repo_dir": "experimental", - "updated_at": "2026-05-22T20:18:49Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "1-knowledge-assistants.md", "2-supervisor-agents.md", @@ -192,7 +208,7 @@ "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": "2026-05-22T20:17:46Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "1-task-functions.md", "2-ai-query.md", @@ -208,7 +224,7 @@ "version": "0.0.1", "description": "Create Databricks AI/BI dashboards. Must use when creating, updating, or deploying Lakeview dashboards as Databricks Dashboard have a unique json structure. CRITICAL: You MUST test ALL SQL queries via CLI BEFORE deploying. Follow guidelines strictly.", "repo_dir": "experimental", - "updated_at": "2026-05-22T20:17:46Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "1-widget-specifications.md", "2-advanced-widget-specifications.md", @@ -225,7 +241,7 @@ "version": "0.0.1", "description": "Builds Databricks applications. Prefers AppKit (TypeScript + React SDK) for new apps; falls back to Python frameworks (Dash, Streamlit, Gradio, Flask, FastAPI, Reflex) when Python is required. Handles OAuth authorization, app resources, SQL warehouse and Lakebase connectivity, model serving, foundation model APIs, and deployment. Use when building web apps, dashboards, ML demos, or REST APIs for Databricks, or when the user mentions AppKit, Streamlit, Dash, Gradio, Flask, FastAPI, Reflex, or Databricks app.", "repo_dir": "experimental", - "updated_at": "2026-05-22T20:17:46Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "1-authorization.md", "2-app-resources.md", @@ -247,7 +263,7 @@ "version": "0.0.1", "description": "Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities. This skill MUST be invoked when the user mentions: \"DBSQL\", \"Databricks SQL\", \"SQL warehouse\", \"SQL scripting\", \"stored procedure\", \"CALL procedure\", \"materialized view\", \"CREATE MATERIALIZED VIEW\", \"pipe syntax\", \"|>\", \"geospatial\", \"H3\", \"ST_\", \"spatial SQL\", \"collation\", \"COLLATE\", \"ai_query\", \"ai_classify\", \"ai_extract\", \"ai_gen\", \"AI function\", \"http_request\", \"remote_query\", \"read_files\", \"Lakehouse Federation\", \"recursive CTE\", \"WITH RECURSIVE\", \"multi-statement transaction\", \"temp table\", \"temporary view\", \"pipe operator\". SHOULD also invoke when the user asks about SQL best practices, data modeling patterns, or advanced SQL features on Databricks.", "repo_dir": "experimental", - "updated_at": "2026-05-22T15:54:01Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -264,7 +280,7 @@ "version": "0.0.1", "description": "Databricks documentation reference via llms.txt index. Use when other skills do not cover a topic, looking up unfamiliar Databricks features, or needing authoritative docs on APIs, configurations, or platform capabilities.", "repo_dir": "experimental", - "updated_at": "2026-05-22T15:54:01Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -276,7 +292,7 @@ "version": "0.0.1", "description": "Execute code and manage compute on Databricks. Use this skill when the user mentions: \"run code\", \"execute\", \"run on databricks\", \"serverless\", \"no cluster\", \"run python\", \"run scala\", \"run sql\", \"run R\", \"run file\", \"push and run\", \"notebook run\", \"batch script\", \"model training\", \"run script on cluster\", \"create cluster\", \"new cluster\", \"resize cluster\", \"modify cluster\", \"delete cluster\", \"terminate cluster\", \"create warehouse\", \"new warehouse\", \"resize warehouse\", \"delete warehouse\", \"node types\", \"runtime versions\", \"DBR versions\", \"spin up compute\", \"provision cluster\".", "repo_dir": "experimental", - "updated_at": "2026-05-22T15:57:09Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -292,7 +308,7 @@ "version": "0.0.1", "description": "Apache Iceberg tables on Databricks \u2014 Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mode, Iceberg REST Catalog (IRC), Iceberg v3, Snowflake interop, PyIceberg, OSS Spark, external engine access and credential vending. Use when creating Iceberg tables, enabling External Iceberg Reads (uniform) on Delta tables (including Streaming Tables and Materialized Views via compatibility mode), configuring external engines to read Databricks tables via Unity Catalog IRC, integrating with Snowflake catalog to read Foreign Iceberg tables", "repo_dir": "experimental", - "updated_at": "2026-05-22T20:17:46Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "1-managed-iceberg-tables.md", "2-uniform-and-compatibility.md", @@ -309,7 +325,7 @@ "version": "0.0.1", "description": "Unity Catalog metric views: define, create, query, and manage governed business metrics in YAML. Use when building standardized KPIs, revenue metrics, order analytics, or any reusable business metrics that need consistent definitions across teams and tools.", "repo_dir": "experimental", - "updated_at": "2026-05-22T20:17:46Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -323,7 +339,7 @@ "version": "0.0.1", "description": "MLflow 3 GenAI agent evaluation. Use when writing mlflow.genai.evaluate() code, creating @scorer functions, using built-in scorers (Guidelines, Correctness, Safety, RetrievalGroundedness), building eval datasets from traces, setting up trace ingestion and production monitoring, aligning judges with MemAlign from domain expert feedback, or running optimize_prompts() with GEPA for automated prompt improvement.", "repo_dir": "experimental", - "updated_at": "2026-05-22T15:56:43Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -346,7 +362,7 @@ "version": "0.0.1", "description": "Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.", "repo_dir": "experimental", - "updated_at": "2026-05-22T15:54:01Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -364,7 +380,7 @@ "version": "0.0.1", "description": "Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime, availableNow), handling stateful operations with watermarks, optimizing checkpoints, performing stream-stream or stream-static joins, writing to multiple sinks, or tuning streaming cost and performance.", "repo_dir": "experimental", - "updated_at": "2026-05-22T15:54:01Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -385,7 +401,7 @@ "version": "0.0.1", "description": "Generate realistic synthetic data using Spark + Faker (strongly recommended). Supports serverless execution, multiple output formats (Parquet/JSON/CSV/Delta), and scales from thousands to millions of rows. For small datasets (<10K rows), can optionally generate locally and upload to volumes. Use when user mentions 'synthetic data', 'test data', 'generate data', 'demo dataset', 'Faker', or 'sample data'.", "repo_dir": "experimental", - "updated_at": "2026-05-22T15:54:01Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -400,7 +416,7 @@ "version": "0.0.1", "description": "Unity Catalog system tables and volumes. Use when querying system tables (audit, lineage, billing) or working with volume file operations (upload, download, list files in /Volumes/).", "repo_dir": "experimental", - "updated_at": "2026-05-22T20:17:46Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "5-system-tables.md", "6-volumes.md", @@ -415,7 +431,7 @@ "version": "0.0.1", "description": "Generate PDF documents from HTML and upload to Unity Catalog volumes. Use for creating test PDFs, demo documents, reports, or evaluation datasets.", "repo_dir": "experimental", - "updated_at": "2026-05-22T15:56:43Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", @@ -424,27 +440,11 @@ "scripts/pdf_generator.py" ] }, - "databricks-vector-search": { - "version": "0.0.1", - "description": "Patterns for Databricks Vector Search: create endpoints and indexes, query with filters, manage embeddings. Use when building RAG applications, semantic search, or similarity matching. Covers both storage-optimized and standard endpoints.", - "repo_dir": "experimental", - "updated_at": "2026-05-22T15:54:01Z", - "files": [ - "SKILL.md", - "agents/openai.yaml", - "assets/databricks.png", - "assets/databricks.svg", - "end-to-end-rag.md", - "index-types.md", - "search-modes.md", - "troubleshooting-and-operations.md" - ] - }, "databricks-zerobus-ingest": { "version": "0.0.1", "description": "Build Zerobus Ingest clients for near real-time data ingestion into Databricks Delta tables via gRPC. Use when creating producers that write directly to Unity Catalog tables without a message bus, working with the Zerobus Ingest SDK in Python/Java/Go/TypeScript/Rust, generating Protobuf schemas from UC tables, or implementing stream-based ingestion with ACK handling and retry logic.", "repo_dir": "experimental", - "updated_at": "2026-05-22T20:17:46Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "1-setup-and-authentication.md", "2-python-client.md", @@ -461,7 +461,7 @@ "version": "0.0.1", "description": "Build custom Python data sources for Apache Spark using the PySpark DataSource API \u2014 batch and streaming readers/writers for external systems. Use this skill whenever someone wants to connect Spark to an external system (database, API, message queue, custom protocol), build a Spark connector or plugin in Python, implement a DataSourceReader or DataSourceWriter, pull data from or push data to a system via Spark, or work with the PySpark DataSource API in any way. Even if they just say \"read from X in Spark\" or \"write DataFrame to Y\" and there's no native connector, this skill applies.", "repo_dir": "experimental", - "updated_at": "2026-05-22T20:17:46Z", + "updated_at": "2026-05-25T13:54:06Z", "files": [ "SKILL.md", "agents/openai.yaml", diff --git a/scripts/skills.py b/scripts/skills.py index d182e9a..9bd5cfe 100644 --- a/scripts/skills.py +++ b/scripts/skills.py @@ -46,6 +46,9 @@ "databricks-serverless-migration": { "description": "Migrate Databricks workloads from classic compute to serverless compute, including compatibility checks and concrete fixes", }, + "databricks-vector-search": { + "description": "Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns", + }, } diff --git a/experimental/databricks-vector-search/SKILL.md b/skills/databricks-vector-search/SKILL.md similarity index 92% rename from experimental/databricks-vector-search/SKILL.md rename to skills/databricks-vector-search/SKILL.md index 4859425..19e13c4 100644 --- a/experimental/databricks-vector-search/SKILL.md +++ b/skills/databricks-vector-search/SKILL.md @@ -1,10 +1,15 @@ --- name: databricks-vector-search description: "Patterns for Databricks Vector Search: create endpoints and indexes, query with filters, manage embeddings. Use when building RAG applications, semantic search, or similarity matching. Covers both storage-optimized and standard endpoints." +metadata: + version: "0.1.0" +parent: databricks-core --- # Databricks Vector Search +**FIRST**: Use the parent `databricks-core` skill for CLI basics, authentication, and profile selection. + Patterns for creating, managing, and querying vector search indexes for RAG and semantic search applications. ## When to Use @@ -184,7 +189,7 @@ results = w.vector_search_indexes.query_index( ### Hybrid Search (Semantic + Keyword) -Hybrid search combines vector similarity (ANN) with BM25 keyword scoring. Use it when queries contain exact terms that must match — SKUs, error codes, proper nouns, or technical terminology — where pure semantic search might miss keyword-specific results. See [search-modes.md](search-modes.md) for detailed guidance on choosing between ANN and hybrid search. +Hybrid search combines vector similarity (ANN) with BM25 keyword scoring. Use it when queries contain exact terms that must match — SKUs, error codes, proper nouns, or technical terminology — where pure semantic search might miss keyword-specific results. See [references/search-modes.md](references/search-modes.md) for detailed guidance on choosing between ANN and hybrid search. ```python # Combines vector similarity with keyword matching @@ -259,10 +264,10 @@ scan_result = w.vector_search_indexes.scan_index( | Topic | File | Description | |-------|------|-------------| -| Index Types | [index-types.md](index-types.md) | Detailed comparison of Delta Sync (managed/self-managed) vs Direct Access | -| End-to-End RAG | [end-to-end-rag.md](end-to-end-rag.md) | Complete walkthrough: source table → endpoint → index → query → agent integration | -| Search Modes | [search-modes.md](search-modes.md) | When to use semantic (ANN) vs hybrid search, decision guide | -| Operations | [troubleshooting-and-operations.md](troubleshooting-and-operations.md) | Monitoring, cost optimization, capacity planning, migration | +| Index Types | [references/index-types.md](references/index-types.md) | Detailed comparison of Delta Sync (managed/self-managed) vs Direct Access | +| End-to-End RAG | [references/end-to-end-rag.md](references/end-to-end-rag.md) | Complete walkthrough: source table → endpoint → index → query → agent integration | +| Search Modes | [references/search-modes.md](references/search-modes.md) | When to use semantic (ANN) vs hybrid search, decision guide | +| Operations | [references/troubleshooting-and-operations.md](references/troubleshooting-and-operations.md) | Monitoring, cost optimization, capacity planning, migration | ## CLI Quick Reference diff --git a/experimental/databricks-vector-search/agents/openai.yaml b/skills/databricks-vector-search/agents/openai.yaml similarity index 100% rename from experimental/databricks-vector-search/agents/openai.yaml rename to skills/databricks-vector-search/agents/openai.yaml diff --git a/experimental/databricks-vector-search/assets/databricks.png b/skills/databricks-vector-search/assets/databricks.png similarity index 100% rename from experimental/databricks-vector-search/assets/databricks.png rename to skills/databricks-vector-search/assets/databricks.png diff --git a/experimental/databricks-vector-search/assets/databricks.svg b/skills/databricks-vector-search/assets/databricks.svg similarity index 100% rename from experimental/databricks-vector-search/assets/databricks.svg rename to skills/databricks-vector-search/assets/databricks.svg diff --git a/experimental/databricks-vector-search/end-to-end-rag.md b/skills/databricks-vector-search/references/end-to-end-rag.md similarity index 100% rename from experimental/databricks-vector-search/end-to-end-rag.md rename to skills/databricks-vector-search/references/end-to-end-rag.md diff --git a/experimental/databricks-vector-search/index-types.md b/skills/databricks-vector-search/references/index-types.md similarity index 100% rename from experimental/databricks-vector-search/index-types.md rename to skills/databricks-vector-search/references/index-types.md diff --git a/experimental/databricks-vector-search/search-modes.md b/skills/databricks-vector-search/references/search-modes.md similarity index 100% rename from experimental/databricks-vector-search/search-modes.md rename to skills/databricks-vector-search/references/search-modes.md diff --git a/experimental/databricks-vector-search/troubleshooting-and-operations.md b/skills/databricks-vector-search/references/troubleshooting-and-operations.md similarity index 100% rename from experimental/databricks-vector-search/troubleshooting-and-operations.md rename to skills/databricks-vector-search/references/troubleshooting-and-operations.md From 17bbf8ff9e49feff7652602e0d31af5b13e8844c Mon Sep 17 00:00:00 2001 From: James Broadhead Date: Thu, 28 May 2026 11:14:21 +0000 Subject: [PATCH 2/3] fix(vector-search): sync SKILL.md description with manifest override Frontmatter description still carried the old verbose text while the manifest.json and scripts/skills.py override carried the concise version. That meant tools reading SKILL.md saw one description; tools reading the manifest saw another. Update the frontmatter to match. Co-authored-by: Isaac --- skills/databricks-vector-search/SKILL.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/skills/databricks-vector-search/SKILL.md b/skills/databricks-vector-search/SKILL.md index 19e13c4..ad8eebc 100644 --- a/skills/databricks-vector-search/SKILL.md +++ b/skills/databricks-vector-search/SKILL.md @@ -1,6 +1,6 @@ --- name: databricks-vector-search -description: "Patterns for Databricks Vector Search: create endpoints and indexes, query with filters, manage embeddings. Use when building RAG applications, semantic search, or similarity matching. Covers both storage-optimized and standard endpoints." +description: "Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns" metadata: version: "0.1.0" parent: databricks-core From aad97f85b20607fc99eb1234c9108aa999fa8b5d Mon Sep 17 00:00:00 2001 From: James Broadhead Date: Thu, 28 May 2026 11:21:04 +0000 Subject: [PATCH 3/3] fix: restore SKILL_METADATA opening lost in merge resolution --- scripts/skills.py | 1 + 1 file changed, 1 insertion(+) diff --git a/scripts/skills.py b/scripts/skills.py index 7ef8874..0c8fc80 100644 --- a/scripts/skills.py +++ b/scripts/skills.py @@ -24,6 +24,7 @@ # check_plugin_manifest to verify .claude-plugin/plugin.json keywords stay # aligned with the shipped skills. Descriptions live in each skill's SKILL.md # frontmatter and are synthesized into the manifest via _build_stable_entry. +SKILL_METADATA = { "databricks-core": {"plugin_keyword": "cli"}, "databricks-apps": {"plugin_keyword": "apps"}, "databricks-jobs": {"plugin_keyword": "jobs"},