databricks-core
Databricks CLI operations and the parent/entry-point skill for Databricks CLI use: authentication, profile selection, and bundles. Load this first for CLI, auth, profile, and bundle tasks, then load the matching product skill.
Install / Use
npx skills add Paldom/databricks-apps-fastapi-starter --skill databricksInstalls into whichever agent you are using.
Gemini Rules
Gemini CLI config
Quality Score
Category
Data & AnalyticsSupported Platforms
Our assessment of databricks-core
databricks-core scores 77/100 on our quality scale, 548th of 603 Data & Analytics skills we index.
Its Gemini Rules is 7.0 KB long, well organised into 30 sections with 3 code examples: a thorough specification that gives an agent plenty to work with.
It has no GitHub stars yet, so there is no community track record; judge it on its content.
Maintenance, license and trust
- The repository was last updated 10 days ago, so databricks-core is actively maintained.
- Our last check on 2026-09-24 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 80/100, with 2 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
databricks-core compared with similar skills
All 4 of these similar skills score higher than databricks-core; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| databricks-core (this skill)by Paldom | 77 | 0 | 10d ago | Gemini Rules |
| claude-memby thedotmack | 100 | 98.6k | today | CLAUDE.md |
| 360-feedback-systemby sickn33 | 100 | 47.3k | 2d ago | SKILL.md |
| access-matrixby sickn33 | 100 | 47.3k | 2d ago | SKILL.md |
| accounting-audit-system-builderby sickn33 | 100 | 47.3k | 2d ago | SKILL.md |
Frequently asked questions
- How do I install databricks-core?
- Run
npx skills add Paldom/databricks-apps-fastapi-starter. The install tabs above show the steps for each supported agent. - Which AI agents does databricks-core work with?
- It is written for Gemini CLI, as a Gemini Rules file. Other agents that read the same format can often use it too.
- Is databricks-core safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 80/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is databricks-core still maintained?
- The repository was last updated 10 days ago, so databricks-core is actively maintained.
Skill content
View source on GitHubname: "databricks-core" description: "Databricks CLI operations and the parent/entry-point skill for Databricks CLI use: authentication, profile selection, and bundles. Load this first for CLI, auth, profile, and bundle tasks, then load the matching product skill. For finding or exploring data, answering questions about the data, or generating SQL, load the databricks-data-discovery skill (it routes to Genie One). Contains up-to-date guidelines for Databricks-related CLI tasks." compatibility: Requires databricks CLI (>= v0.292.0) metadata: version: "0.1.0"
Databricks
Core skill for Databricks CLI, authentication, and data exploration.
Product Skills
For specific products, use dedicated skills:
- databricks-jobs - Lakeflow Jobs development and deployment
- databricks-pipelines - Lakeflow Spark Declarative Pipelines (batch and streaming data pipelines)
- databricks-apps - Full-stack TypeScript app development and deployment
- databricks-lakebase - Lakebase Postgres Autoscaling project management
- databricks-model-serving - Model Serving endpoint management and inference
For data discovery, exploration, and query generation — finding tables, answering natural-language questions about the data, or generating SQL — use databricks-data-discovery if it is installed (experimental; it asks Genie One first, then falls back to manual exploration). If it isn't installed, use the AI-tool commands below and Manual Data Exploration.
Prerequisites
-
CLI installed: Run
databricks --versionto check.- If the CLI is missing or outdated (< v0.292.0): STOP. Do not proceed or work around a missing CLI.
- Read the CLI Installation reference file and follow the instructions to guide the user through installation.
- Note: In sandboxed environments (Cursor IDE, containers), install commands write outside the workspace and may be blocked. Present the install command to the user and ask them to run it in their own terminal.
- Exception: If CLI installation is blocked (sandboxed containers, restricted environments), ask the user whether to fall back to direct REST API calls using
DATABRICKS_HOSTandDATABRICKS_TOKENenvironment variables if present in the shell. See the Databricks REST API docs.
-
Authenticated:
databricks auth profiles- If not: see CLI Authentication
Profile Selection - CRITICAL
NEVER auto-select a profile.
- List profiles:
databricks auth profiles - Present ALL profiles to user with workspace URLs
- Let user choose (even if only one exists)
- Offer to create new profile if needed
Claude Code - IMPORTANT
Each Bash command runs in a separate shell session.
# WORKS: --profile flag
databricks apps list --profile my-workspace
# WORKS: chained with &&
export DATABRICKS_CONFIG_PROFILE=my-workspace && databricks apps list
# DOES NOT WORK: separate commands
export DATABRICKS_CONFIG_PROFILE=my-workspace
databricks apps list # profile not set!
Data Exploration — Use AI Tools
Use these instead of manually navigating catalogs/schemas/tables:
# discover table structure (columns, types, sample data, stats)
databricks experimental aitools tools discover-schema catalog.schema.table --profile <PROFILE>
# run ad-hoc SQL queries
databricks experimental aitools tools query "SELECT * FROM table LIMIT 10" --profile <PROFILE>
# find the default warehouse
databricks experimental aitools tools get-default-warehouse --profile <PROFILE>
Names are literal. Use catalog/schema/table names exactly as given — never change a
hyphen to an underscore or otherwise normalize them. In SQL, backtick-quote any name part
with special characters (e.g. `my-catalog`.schema.table); unquoted hyphens cause a
parse error.
These commands are first-class for running known SQL and profiling — Genie isn't
required for that. For natural-language data questions, locating data you can't
pin down, or generating a query from a question, prefer the databricks-data-discovery
skill (above) if it's installed. See Manual Data Exploration for the
full command surface, quoting rules, and troubleshooting.
Quick Reference
⚠️ CRITICAL: Some commands use positional arguments, not flags
# current user
databricks current-user me --profile <PROFILE>
# list resources
databricks apps list --profile <PROFILE>
databricks jobs list --profile <PROFILE>
databricks clusters list --profile <PROFILE>
databricks warehouses list --profile <PROFILE>
databricks pipelines list --profile <PROFILE>
databricks serving-endpoints list --profile <PROFILE>
# ⚠️ Unity Catalog — POSITIONAL arguments (NOT flags!)
databricks catalogs list --profile <PROFILE>
# ✅ CORRECT: positional args
databricks schemas list <CATALOG> --profile <PROFILE>
databricks tables list <CATALOG> <SCHEMA> --profile <PROFILE>
databricks tables get <CATALOG>.<SCHEMA>.<TABLE> --profile <PROFILE>
# ❌ WRONG: these flags/commands DON'T EXIST
# databricks schemas list --catalog-name <CATALOG> ← WILL FAIL
# databricks tables list --catalog <CATALOG> ← WILL FAIL
# databricks sql-warehouses list ← doesn't exist, use `warehouses list`
# databricks execute-statement ← doesn't exist, use `experimental aitools tools query`
# databricks sql execute ← doesn't exist, use `experimental aitools tools query`
# When in doubt, check help:
# databricks schemas list --help
# get details
databricks apps get <NAME> --profile <PROFILE>
databricks jobs get --job-id <ID> --profile <PROFILE>
databricks clusters get --cluster-id <ID> --profile <PROFILE>
# bundles
databricks bundle init --profile <PROFILE>
databricks bundle validate --profile <PROFILE>
databricks bundle deploy -t <TARGET> --profile <PROFILE>
databricks bundle run <RESOURCE> -t <TARGET> --profile <PROFILE>
Troubleshooting
| Error | Solution |
|-------|----------|
| cannot configure default credentials | Use --profile flag or authenticate first |
| configuration does not support OAuth tokens | The command requires OAuth (e.g., databricks apps logs). Re-authenticate with databricks auth login --host <URL> --profile <PROFILE>. See CLI Authentication. |
| PERMISSION_DENIED | Check workspace/UC permissions |
| RESOURCE_DOES_NOT_EXIST | Verify resource name/id and profile |
Required Reading by Task
| Task | READ BEFORE proceeding |
|------|------------------------|
| First time setup | CLI Installation |
| Auth issues / new workspace | CLI Authentication |
| Exploring tables/schemas | Manual Data Exploration (or databricks-data-discovery if installed) |
| Deploying jobs/pipelines | Use /databricks-dabs |
Reference Guides
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
