databricks/databricks-agent-skills

databricks/databricks-agent-skills

Language: Python

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Created: 2026-01-14T09:51:58Z

Pushed: 2026-06-10T21:05:05Z

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README:

Databricks Agent Skills

Skills for AI coding assistants (Claude Code, Cursor, etc.) that provide Databricks-specific guidance.

Installation

Two install paths cover the stable skills. They install to different places but end up loaded by the same agents — pick whichever fits your workflow.

• Databricks CLI writes SKILL.md files directly into each agent's skill

directory (~/.claude/skills/, ~/.cursor/extensions/, etc.).

• Plugin marketplaces (Claude Code, Cursor) cache the plugin under the

agent's plugin directory (e.g. ~/.claude/plugins/cache/databricks-agent-skills/); the agent discovers skills from there.

Via the Databricks CLI (canonical; supports experimental skills):

databricks aitools install

The CLI auto-detects your coding agent(s) and installs the stable skills to the right location:

• Claude Code → ~/.claude/skills/
• Cursor, Codex CLI, OpenCode, GitHub Copilot, Antigravity

→ their respective skill directories

For finer control, use the aitools skills install subcommand directly — it accepts a positional skill name and an --experimental flag (see the [Experimental Skills](#experimental-skills) section).

Via the Claude Code plugin marketplace (stable skills only — installs every skill under [./skills/](./skills/)):

/plugin marketplace add databricks/databricks-agent-skills
/plugin install databricks@databricks-agent-skills

Via the Cursor plugin marketplace:

/add-plugin databricks-skills

CLI vs plugin marketplace

| | CLI | Plugin marketplace | |---|---|---| | Stable skills | ✅ (default) | ✅ | | Experimental skills | ✅ (with --experimental or by name) | ❌ | | Per-skill selection | ✅ (databricks aitools install ) | ❌ (all-or-nothing) | | Updates | databricks aitools update | Plugin marketplace update flow | | Required outside the agent | Databricks CLI v1.0.0+ | None |

If in doubt, use the CLI — it's the canonical install path and the only one that exposes experimental skills.

Available Skills

Stable skills shipped from [skills/](./skills/):

• databricks-core — CLI, authentication, profile selection, data exploration. Parent skill for all product skills.
• databricks-apps — Build full-stack TypeScript apps on Databricks using AppKit.
• databricks-dabs — Declarative Automation Bundles (formerly Asset Bundles) for deploying and managing Databricks resources.
• databricks-jobs — Lakeflow Jobs orchestration: task types, triggers, schedules, notifications.
• databricks-lakebase — Lakebase Postgres: projects, branching, autoscaling, synced tables, Data API.
• 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

The [experimental/](./experimental/) directory contains additional skills originally imported from databricks-solutions/ai-dev-kit (now deprecated — this repo is the source of truth going forward) 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 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.

Structure

Each skill follows the Agent Skills Specification:

skill-name/
├── SKILL.md # Main skill file with frontmatter + instructions
└── references/ # Additional documentation loaded on demand

Development

Adding New Skills

For a narrower variation of an existing skill, create a subskill that declares its parent via frontmatter. This is how the stable skills are organized today — each product skill sets parent: databricks-core.

---
name: "databricks-apps-chatbots"
description: "Databricks apps with chatbot features"
parent: databricks-apps
---

# Chatbot Apps

**FIRST**: Use the parent `databricks-apps` skill for app development basics.

Then apply these patterns:
- Pattern 1
- Pattern 2

This approach:

• Keeps the main skill stable and focused
• Allows experimentation without modifying core skills
• Makes it easy to follow the changes in the main skill

Manifest Management

manifest.json is generated by scripts/skills.py from the skill directories and frontmatter. Do not edit it by hand. CI rejects manual changes via two checks: content drift (parsed dict doesn't match what generate would produce) and canonical form (on-disk bytes don't match json.dumps(..., indent=2, sort_keys=True)).

Sync assets and regenerate the manifest after adding or updating skills:

python3 scripts/skills.py

Validate that assets and manifest are up to date (used by CI):

python3 scripts/skills.py validate

The manifest is consumed by the CLI to discover available skills.

Security

Please see [SECURITY](./SECURITY) for vulnerability reporting guidelines.

Integrity

Release tags are created by the [Release workflow](./.github/workflows/release.yml) and map 1:1 to a published version.

Contributing

• All changes require approval from a code owner (see [CODEOWNERS](./.github/CODEOWNERS)).
• Documentation examples must follow least-privilege defaults — avoid suggesting elevated permissions or broad scopes unless explicitly necessary.