Official agent skill

Databricks Pipelines

by databricks in databricks/databricks-agent-skills

Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks.

OfficialCustom licenceAuto-check passedData & Analytics

Install Databricks Pipelines

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

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

GitHub CLI
$ gh skill install databricks/databricks-agent-skills databricks-pipelines --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-pipelines .claude/skills/databricks-pipelines && 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-pipelines
GitHub stars
345
Used in
1 other repo
Token cost
~8.6k tokens
SKILL.md length
2,393 words
Files
37 (incl. references, assets)
Skills in repo
32
Repo updated
First seen
Licence
Custom licence

At a glance

Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks.

  • Streaming data pipelines with Python
  • SKILL.md covers Decision Tree, Common Traps, Common Issues and Publishing Modes, plus 6 more sections
  • Calls databricks
  • Including Auto CDC from event streams

What it does

Databricks Pipelines is an agent skill from databricks/databricks-agent-skills, published by the product's own GitHub organization. Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks. Use when building batch or streaming data pipelines with Python or SQL, including Auto CDC from event streams or periodic complete snapshots. Invoke BEFORE starting implementation.

Its SKILL.md is about 8.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 39 other files, including reference files and assets (for example `agents/openai.yaml`, `references/1-project-initialization-with-dab.md` and `references/2-rapid-iteration-with-cli.md`). Compatibility notes: Requires databricks CLI (= v1.0.0)

It sits in Data & Analytics, covering Data pipelines and ETL and SQL. It works with Databricks, SQL and Python. 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

  • Streaming data pipelines with Python
  • Including Auto CDC from event streams
  • Periodic complete snapshots

Example prompts

  • “/databricks-pipelines”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Requires databricks CLI (>= v1.0.0)

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.

  • Compatibility

    Requires databricks CLI (>= v1.0.0)

    From compatibility in the SKILL.md frontmatter.

Context cost

Databricks Pipelines loads about 8.6k tokens when it runs, and up to ~45k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 2,393 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~73
When it runs · the whole SKILL.md, loaded when a task matches
~8.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~45k

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 2,393 words (~8,600 tokens).

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

— opening of SKILL.md by databricks, Custom licence
name
databricks-pipelines
compatibility
Requires databricks CLI (>= v1.0.0)
metadata.version
0.3.0
parent
databricks-core

Read the full SKILL.md on GitHub

Files

SKILL.md and 36 other files (references, assets) in skills/databricks-pipelines of databricks/databricks-agent-skills.

  • SKILL.md
  • agents/openai.yaml
  • assets/databricks.png
  • assets/databricks.svg
  • references/1-project-initialization-with-dab.md
  • references/2-rapid-iteration-with-cli.md
  • references/auto-cdc-python.md
  • references/auto-cdc-sql.md
  • references/auto-loader-python.md
  • references/auto-loader-sql.md
  • references/dlt-migration.md
  • references/expectations-python.md
  • references/expectations-sql.md
  • references/foreach-batch-sink-python.md
  • references/kafka.md
  • references/materialized-view-python.md
  • references/materialized-view-sql.md
  • references/options-avro.md
  • … and 19 more

Open the folder on GitHubat commit f4fcec5

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in databricks/databricks-agent-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Databricks Pipelines 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 Pipelines compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Databricks Pipelines this skilldatabricks/databricks-agent-skills3451 repos~8.6kAutomated safety check: PassCustom licence
Databricks JobsKilo-Org/kilo-marketplace1891 repos~3.1kAutomated safety check: PassCustom licence
Frappe Syntax ReportsImpertio-Studio/Frappe_Claude_Skill_Package187—~2.3kAutomated safety check: PassMIT
Optimizing Databricks SQLAltimateAI/data-engineering-skills127—~6.7kAutomated safety check: PassMIT
Snowflake Developmentsickn33/agentic-awesome-skills47k2 repos~2.1kAutomated safety check: PassMIT
Snowflake Developmentalirezarezvani/claude-skills28k—~3.2kAutomated safety check: PassMIT

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Questions about Databricks Pipelines

What does Databricks Pipelines do?

Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks. Databricks Pipelines is an agent skill from databricks/databricks-agent-skills, published by the product's own GitHub organization. Develop Lakeflow Spark Declarative Pipelines (formerly Delta Live Tables) on Databricks.

When should I use Databricks Pipelines?

Databricks Pipelines fits situations like: streaming data pipelines with Python; including Auto CDC from event streams; periodic complete snapshots.

How do I install Databricks Pipelines in Claude Code?

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

How do I install Databricks Pipelines in Codex?

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

Can I use Databricks Pipelines 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-pipelines -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-pipelines, .gemini/skills/databricks-pipelines, .github/skills/databricks-pipelines and .opencode/skills/databricks-pipelines in your project.

What does Databricks Pipelines need to run?

Going by SKILL.md and its folder, Databricks Pipelines needs the command-line tools its instructions call (databricks). Our summary lists: Python 3. Compatibility (from SKILL.md): Requires databricks CLI (>= v1.0.0).

Does Databricks Pipelines 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 Pipelines 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 Pipelines use?

Databricks Pipelines 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 Pipelines use?

About 8.6k tokens (SKILL.md is roughly 34k 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 36k tokens, read only when the agent opens those files.

What are the alternatives to Databricks Pipelines?

Skills that share tags, products or a category with Databricks Pipelines: Databricks Jobs (Kilo-Org/kilo-marketplace, 189 stars), Frappe Syntax Reports (Impertio-Studio/Frappe_Claude_Skill_Package, 187 stars), Optimizing Databricks SQL (AltimateAI/data-engineering-skills, 127 stars) and Snowflake Development (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Databricks Pipelines?

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.