Agent skill

Databricks CLI

by aehrc in aehrc/pathling

Expert guidance for using the Databricks CLI to manage Databricks workspaces, clusters, jobs, pipelines, Unity Catalog, SQL warehouses, serving endpoints, secrets, bundles, and all other Databricks…

Apache-2.0Auto-check passedGame Development

Install Databricks CLI

skills CLI
$ npx skills add aehrc/pathling --skill databricks-cli -a claude-code

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

GitHub CLI
$ gh skill install aehrc/pathling databricks-cli --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/aehrc/pathling.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/databricks-cli .claude/skills/databricks-cli && 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-cli
GitHub stars
137
Token cost
~2.1k tokens
SKILL.md length
567 words
Files
10 (incl. references)
Skills in repo
25
Repo updated
First seen
Licence
Apache-2.0

At a glance

Expert guidance for using the Databricks CLI to manage Databricks workspaces, clusters, jobs, pipelines, Unity Catalog, SQL warehouses, serving endpoints, secrets, bundles, and all other Databricks…

  • Works in 3 steps: Bundle settings files (if running from… → Environment variables (DATABRICKS_HOST,… → .databrickscfg profiles
  • Running databricks commands
  • SKILL.md covers Command syntax, Authentication, Global flags and JSON input, plus 3 more sections
  • Calls databricks and jq; reaches accounts.cloud.databricks.com; needs DATABRICKS_TOKEN

What it does

Databricks CLI is an agent skill from aehrc/pathling. Expert guidance for using the Databricks CLI to manage Databricks workspaces, clusters, jobs, pipelines, Unity Catalog, SQL warehouses, serving endpoints, secrets, bundles, and all other Databricks resources. Use this skill when running databricks commands, managing Databricks infrastructure, deploying bundles, querying serving endpoints, managing Unity Catalog objects, or automating Databricks workflows. Trigger keywords include "databricks", "databricks cli", "dbfs", "unity catalog", "databricks bundle"…

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files (for example `references/account.md`, `references/bundles.md` and `references/compute.md`).

It sits in Game Development, covering SQL. It works with Databricks and SQL. The repository describes itself as: Tools that make it easier to use FHIR and clinical terminology within data analytics, built on Apache Spark. The licence is Apache-2.0.

When your agent uses it

  • Running databricks commands
  • Managing Databricks infrastructure
  • Deploying bundles
  • Querying serving endpoints

Example prompts

  • “databricks”
  • “databricks cli”
  • “unity catalog”
  • “/databricks-cli”

Requirements

  • A credential in DATABRICKS_TOKEN

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Bundle settings files (if running from bundle directory)
  2. Environment variables (DATABRICKS_HOST, DATABRICKS_TOKEN, etc.)
  3. .databrickscfg profiles

What it can do on your machine

Read from SKILL.md and the folder at commit 56a3b4a. 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
    • jq

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • accounts.cloud.databricks.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • DATABRICKS_TOKEN

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

Context cost

Databricks CLI loads about 2.1k tokens when it runs, and up to ~14k if it reads all its reference files. Until then it costs about 157 tokens; SKILL.md has 567 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~157
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~14k

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

The full file from aehrc/pathling at commit 56a3b4a, republished under its Apache-2.0 licence (© aehrc). 567 words, ~2,133 tokens.

Download SKILL.mdSave it as .claude/skills/databricks-cli/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
databricks-cli
description
Expert guidance for using the Databricks CLI to manage Databricks workspaces, clusters, jobs, pipelines, Unity Catalog, SQL warehouses, serving endpoints, secrets, bundles, and all other Databricks resources. Use this skill when running databricks commands, managing Databricks infrastructure, deploying bundles, querying serving endpoints, managing Unity Catalog objects, or automating Databricks workflows. Trigger keywords include "databricks", "databricks cli", "dbfs", "unity catalog", "databricks bundle", "databricks jobs", "databricks clusters", "sql warehouse", "serving endpoint", "databricks secrets".

Databricks CLI

Comprehensive reference for the Databricks CLI (v0.205+). Covers authentication, all command groups, flags, and common patterns.

Command syntax

databricks <command-group> [<command>] [<subcommand>] [args] [--flags]

Get help at any level with -h or --help.

Authentication

bash
# Workspace-level
databricks auth login --host https://<workspace>.cloud.databricks.com

# Account-level
databricks auth login --host https://accounts.cloud.databricks.com --account-id <id>

Saves credentials to ~/.databrickscfg as a named profile. Tokens auto-refresh and expire in under an hour.

OAuth M2M (service principals)

Add to ~/.databrickscfg:

ini
[my-sp-profile]
host = https://<workspace>.cloud.databricks.com
client_id = <service-principal-client-id>
client_secret = <service-principal-oauth-secret>
Credential resolution order
  1. Bundle settings files (if running from bundle directory)
  2. Environment variables (DATABRICKS_HOST, DATABRICKS_TOKEN, etc.)
  3. .databrickscfg profiles
Profile management
bash
databricks auth profiles          # List all profiles
databricks auth env -p PROD       # Show profile settings
databricks auth token -p PROD     # Show current token
databricks auth describe          # Current auth config details

Use -p <profile> or --profile <profile> on any command. Default profile is DEFAULT.

Global flags

FlagDescription
--debugEnable debug logging
-h, --helpDisplay help
-o, --outputOutput format: text or json
-p, --profileConfig profile from ~/.databrickscfg
--log-fileLog output file path
--log-formattext or json
--log-levelLogging verbosity
--progress-formatdefault, append, inplace, or json
-t, --targetBundle target

JSON input

Use --json with inline JSON or file reference:

bash
# Inline (Linux/macOS)
databricks jobs create --json '{"name": "my-job", ...}'

# From file
databricks jobs create --json @job-config.json

Filter JSON output with jq:

bash
databricks clusters get <id> | jq -r .cluster_name

Direct REST API access

bash
databricks api get /api/2.0/clusters/list
databricks api post /api/2.0/clusters/create --json '{"cluster_name": "test", ...}'
databricks api post /api/2.0/clusters/edit --json @edit-cluster.json

Supports: get, post, put, patch, delete, head.

Command groups

For detailed subcommands, flags, and examples, see the reference files below.

Compute and runtime
  • clusters - Cluster lifecycle (create, start, edit, resize, terminate, delete, pin). See references/compute.md.
  • cluster-policies - Cluster configuration rules.
  • libraries - Install/uninstall packages on clusters. See references/compute.md.
  • instance-pools - Manage cloud instance pools.
  • instance-profiles - IAM instance profile administration (AWS).
  • policy-families - Available policy templates.
Jobs and pipelines
Workspace and files
Unity Catalog
  • catalogs - Create, list, update, delete catalogs. See references/unity-catalog.md.
  • schemas - Manage schemas within catalogs.
  • tables - Table metadata (get, list, delete, exists).
  • volumes - File storage with governance. See references/unity-catalog.md.
  • grants - Data access authorisation. See references/unity-catalog.md.
  • credentials, storage-credentials - Authentication for external storage.
  • connections - External data source linkage.
  • functions - User-defined function management.
  • metastores - Top-level container management.
  • registered-models, model-versions - MLflow registry in UC.
  • online-tables - Low-latency data access.
  • quality-monitors - Data quality metric tracking.
Show full SKILL.md (201 more words)Show less
SQL and analytics
  • warehouses - SQL warehouse lifecycle (create, start, stop, edit, permissions). See references/sql-analytics.md.
  • queries - SQL query CRUD. See references/sql-analytics.md.
  • alerts - SQL alert management.
  • dashboards, lakeview - Dashboard operations.
  • query-history - Query execution history.
  • data-sources - Data source listing.
ML and serving
  • serving-endpoints - Model endpoint deployment, querying, and AI Gateway. See references/ml-serving.md.
  • experiments - MLflow experiment and run management.
  • model-registry - Model version and transition management.
  • feature-engineering - Databricks Feature Store operations.
  • vector-search-endpoints, vector-search-indexes - Embedding search infrastructure.
Identity and access
  • auth - Authentication management. See references/identity.md.
  • current-user - Authenticated user info.
  • users, groups, service-principals - Identity management.
  • permissions - Access control for any resource type. See references/identity.md.
Bundles (infrastructure as code)
  • bundle - Deploy, run, validate, and manage Databricks Asset Bundles. See references/bundles.md.
  • sync - Local-to-workspace directory synchronisation.
Account administration
  • account - Multi-workspace account-level management (identity, Unity Catalog, billing, networking, OAuth). See references/account.md.
Utilities
  • completion - Shell autocompletion setup.
  • labs - Community extension management.
  • version - CLI version information.
  • configure - Legacy configuration command.

Common patterns

Wait vs no-wait

Long-running operations (cluster start, job run) block by default. Use --no-wait to return immediately, --timeout to set a deadline:

bash
databricks clusters start <id> --no-wait
databricks jobs run-now <job-id> --timeout 30m
Permission management

Most resource types support four permission commands:

bash
databricks <resource> get-permission-levels <id>
databricks <resource> get-permissions <id>
databricks <resource> set-permissions <id> --json @perms.json
databricks <resource> update-permissions <id> --json @perms.json
Pagination

List commands with large result sets support pagination:

bash
databricks jobs list --limit 10 --page-token <token>
Proxy support

Set HTTPS_PROXY environment variable to route requests through a proxy.

© aehrc, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (references) in .claude/skills/databricks-cli of aehrc/pathling.

  • SKILL.md
  • references/account.md
  • references/bundles.md
  • references/compute.md
  • references/identity.md
  • references/jobs-pipelines.md
  • references/ml-serving.md
  • references/sql-analytics.md
  • references/unity-catalog.md
  • references/workspace.md

Open the folder on GitHubat commit 56a3b4a

Compare with similar skills

Databricks CLI 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 CLI compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Databricks CLI this skillaehrc/pathling137—~2.1kAutomated safety check: PassApache-2.0
SQL Correctnessdatabricks-solutions/ai-dev-kit1.9k—~438Automated safety check: PassCustom licence
Databricksrocky-data/rocky304—~2kAutomated safety check: PassApache-2.0
Optimizing Databricks SQLAltimateAI/data-engineering-skills127—~6.7kAutomated safety check: PassMIT
Databricks Coredatabricks/databricks-agent-skills345—~1.9kAutomated safety check: PassCustom licence
Databricks Dbsqldatabricks/databricks-agent-skills3451 repos~2.8kAutomated safety check: PassCustom licence

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Works with

Questions about Databricks CLI

What does Databricks CLI do?

Expert guidance for using the Databricks CLI to manage Databricks workspaces, clusters, jobs, pipelines, Unity Catalog, SQL warehouses, serving endpoints, secrets, bundles, and all other Databricks…. Databricks CLI is an agent skill from aehrc/pathling. Expert guidance for using the Databricks CLI to manage Databricks workspaces, clusters, jobs, pipelines, Unity Catalog, SQL warehouses, serving endpoints, secrets, bundles, and all other Databricks resources.

When should I use Databricks CLI?

Databricks CLI fits situations like: running databricks commands; managing Databricks infrastructure; deploying bundles; querying serving endpoints.

How do I install Databricks CLI in Claude Code?

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

How do I install Databricks CLI in Codex?

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

Can I use Databricks CLI 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 aehrc/pathling --skill databricks-cli -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-cli, .gemini/skills/databricks-cli, .github/skills/databricks-cli and .opencode/skills/databricks-cli in your project.

What does Databricks CLI need to run?

Going by SKILL.md and its folder, Databricks CLI needs the command-line tools its instructions call (databricks and jq) and credentials named DATABRICKS_TOKEN. Our summary lists: A credential in DATABRICKS_TOKEN.

Does Databricks CLI access the network?

SKILL.md names 1 domain. In commands or code: accounts.cloud.databricks.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Databricks CLI 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 CLI use?

Databricks CLI is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Databricks CLI use?

About 2.1k tokens (SKILL.md is roughly 8.5k 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 12k tokens, read only when the agent opens those files.

What are the alternatives to Databricks CLI?

Skills that share tags, products or a category with Databricks CLI: SQL Correctness (databricks-solutions/ai-dev-kit, 1.9k stars), Databricks (rocky-data/rocky, 304 stars), Optimizing Databricks SQL (AltimateAI/data-engineering-skills, 127 stars) and Databricks Core (databricks/databricks-agent-skills, 345 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Databricks CLI?

aehrc (a GitHub organization) maintains it in aehrc/pathling, which has 137 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 7, 2026.

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