New: 97,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Official agent skill

Databricks Vector Search

by databricks in databricks/databricks-agent-skills

Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns

OfficialCustom licenceAuto-check passedAI & LLM Engineering

Install Databricks Vector Search

skills CLI
$ npx skills add databricks/databricks-agent-skills --skill databricks-vector-search -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install databricks/databricks-agent-skills databricks-vector-search --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/databricks/databricks-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/databricks-vector-search .claude/skills/databricks-vector-search && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
databricks-vector-search
GitHub stars
345
Token cost
~2.9k tokens
SKILL.md length
593 words
Files
8 (incl. references, assets)
Skills in repo
32
Repo updated
First seen
Licence
Custom licence

At a glance

Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns

  • Tasks that involve Vector databases
  • SKILL.md covers When to Use, Overview, Endpoint Types and Index Types, plus 9 more sections
  • Calls databricks
  • Tasks that involve Retrieval-augmented generation

What it does

Databricks Vector Search is an agent skill from databricks/databricks-agent-skills, published by the product's own GitHub organization. Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns

Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files and assets (for example `agents/openai.yaml`, `references/end-to-end-rag.md` and `references/index-types.md`).

It sits in AI & LLM Engineering, covering Vector databases, Retrieval-augmented generation and Embeddings. It works with Databricks. The repository describes itself as: Databricks AI Tools: skills and plugins for building on Databricks with Claude Code, Cursor, Codex, GitHub Copilot, and other AI coding agents.

When your agent uses it

  • Tasks that involve Vector databases
  • Tasks that involve Retrieval-augmented generation
  • Tasks that involve Embeddings

Example prompts

  • “Use the databricks-vector-search skill to databrick Vector Search endpoints and indexes for RAG and semantic search; covers index types, search…”
  • “/databricks-vector-search”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit f4fcec5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • databricks

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Databricks Vector Search loads about 2.9k tokens when it runs, and up to ~9.9k if it reads all its reference files. Until then it costs about 40 tokens; SKILL.md has 593 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~40
When it runs · the whole SKILL.md, loaded when a task matches
~2.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 593 words (~2,924 tokens).

“FIRST: Use the parent databricks-core skill for CLI basics, authentication, and profile selection.”

— opening of SKILL.md by databricks, Custom licence
name
databricks-vector-search
metadata.version
0.1.0
parent
databricks-core

Read the full SKILL.md on GitHub

Files

SKILL.md and 7 other files (references, assets) in skills/databricks-vector-search of databricks/databricks-agent-skills.

  • 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

Open the folder on GitHubat commit f4fcec5

Compare with similar skills

Databricks Vector Search next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Databricks Vector Search compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Databricks Vector Search this skilldatabricks/databricks-agent-skills345—~2.9kAutomated safety check: PassCustom licence
Chroma Vector DatabaseOrchestra-Research/AI-Research-SKILLs13k8 repos~2.3kAutomated safety check: PassMIT
Ms Agent Framework RAGshuyu-labs/WebCode278—~1.1kAutomated safety check: PassCustom licence
Pgvector Semantic Searchtimescale/pg-aiguide1.9k1 repos~3.8kAutomated safety check: PassApache-2.0
RAG ArchitectJeffallan/claude-skills12k1 repos~2kAutomated safety check: PassMIT
RAG Implementationwshobson/agents40k9 repos~1.1kAutomated safety check: PassMIT

Similar skills

  • Chroma Vector Database

    Orchestra-Research/AI-Research-SKILLs

    Shows how to store documents and embeddings in Chroma, query them by similarity with metadata filters, and persist them to disk for RAG and semantic search projects.

    13k GitHub starsUsed in 8 repos~2.3k tokens
    AI & LLM EngineeringAuto-check passed

  • Ms Agent Framework RAG

    shuyu-labs/WebCode

    Comprehensive guide for building Agentic RAG systems using Microsoft Agent Framework in C.

    278 GitHub stars~1.1k tokensUpdated 3 mo ago
    AI & LLM EngineeringAuto-check passed

  • Pgvector Semantic Search

    timescale/pg-aiguide

    A skill your agent uses for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search.

    1.9k GitHub starsUsed in 1 repo~3.8k tokens
    AI & LLM EngineeringAuto-check passed

  • RAG Architect

    Jeffallan/claude-skills

    Designs retrieval-augmented generation systems: document chunking, embeddings, vector store setup, hybrid search, reranking and retrieval evaluation, with checks at each step.

    12k GitHub starsUsed in 1 repo~2k tokens
    AI & LLM EngineeringAuto-check passed

  • RAG Implementation

    wshobson/agents

    Build retrieval-augmented generation systems: pick a vector database and embedding model, choose retrieval and reranking strategies, and start from a LangGraph pipeline.

    40k GitHub starsUsed in 9 repos~1.1k tokens
    AI & LLM EngineeringAuto-check passed

  • RAG Engineer

    davila7/claude-code-templates

    Expert in building Retrieval-Augmented Generation systems. An agent skill from davila7/claude-code-templates.

    32k GitHub starsUsed in 5 repos~729 tokens
    AI & LLM EngineeringAuto-check passed

More from databricks/databricks-agent-skills

All 32 skills in this repo

  • Databricks Dbsql

    databricks/databricks-agent-skills

    Official

    Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities.

    345 GitHub starsUsed in 1 repo~2.8k tokens
    Auto-check passed

  • Databricks Synthetic Data Gen

    databricks/databricks-agent-skills

    Official

    Generate realistic synthetic data using Spark + Faker (strongly recommended).

    345 GitHub stars~3.2k tokensUpdated yesterday
    Auto-check passed

  • Databricks Model Serving

    databricks/databricks-agent-skills

    Official

    Databricks Model Serving endpoint lifecycle and ops. An agent skill from databricks/databricks-agent-skills.

    345 GitHub starsUsed in 1 repo~3.3k tokens
    Auto-check passed

  • Databricks Python SDK

    databricks/databricks-agent-skills

    Official

    Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API.

    345 GitHub starsUsed in 1 repo~4.6k tokens
    Auto-check passed

  • Databricks Spark Structured Streaming

    databricks/databricks-agent-skills

    Official

    Comprehensive guide to Spark Structured Streaming for production workloads.

    345 GitHub starsUsed in 1 repo~956 tokens
    Auto-check passed

  • Databricks App Design

    databricks/databricks-agent-skills

    Official

    Design the UX of custom-code Databricks Apps (AppKit/React) data screens — KPI/overview pages, reports, charts, tables, and Genie/chat data assistants — mapped to concrete AppKit components.

    345 GitHub stars~1.7k tokensUpdated yesterday
    Auto-check passed

Works with

Categories

Questions about Databricks Vector Search

What does Databricks Vector Search do?

Databricks Vector Search endpoints and indexes for RAG and semantic search; covers index types, search modes, end-to-end RAG patterns. Databricks Vector Search is an agent skill from databricks/databricks-agent-skills, published by the product's own GitHub organization.

When should I use Databricks Vector Search?

Databricks Vector Search fits situations like: tasks that involve Vector databases; tasks that involve Retrieval-augmented generation; tasks that involve Embeddings.

How do I install Databricks Vector Search in Claude Code?

Run `npx skills add databricks/databricks-agent-skills --skill databricks-vector-search -a claude-code`. Or copy the skill folder (skills/databricks-vector-search in databricks/databricks-agent-skills) into .claude/skills/databricks-vector-search in your project. Claude Code loads it when a task matches its description.

How do I install Databricks Vector Search in Codex?

Run `npx skills add databricks/databricks-agent-skills --skill databricks-vector-search -a codex`. Or copy the skill folder (skills/databricks-vector-search in databricks/databricks-agent-skills) into .agents/skills/databricks-vector-search in your project. Codex loads it when a task matches its description.

Can I use Databricks Vector Search in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add databricks/databricks-agent-skills --skill databricks-vector-search -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/databricks-vector-search, .gemini/skills/databricks-vector-search, .github/skills/databricks-vector-search and .opencode/skills/databricks-vector-search in your project.

What does Databricks Vector Search need to run?

Going by SKILL.md and its folder, Databricks Vector Search needs the command-line tools its instructions call (databricks). Our summary lists: Python 3.

Does Databricks Vector Search access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Databricks Vector Search safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Databricks Vector Search use?

Databricks Vector Search has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Databricks Vector Search use?

About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7k tokens, read only when the agent opens those files.

What are the alternatives to Databricks Vector Search?

Skills that share tags, products or a category with Databricks Vector Search: Chroma Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars), Ms Agent Framework RAG (shuyu-labs/WebCode, 278 stars), Pgvector Semantic Search (timescale/pg-aiguide, 1.9k stars) and RAG Architect (Jeffallan/claude-skills, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Databricks Vector Search?

databricks (a GitHub organization, an official publisher) maintains it in databricks/databricks-agent-skills, which has 345 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on October 6, 2026.

Source: databricks/databricks-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.