databricks-agent-brick…
Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).
Previews, provisions, or diagnoses a uv-managed local Python .venv with `databricks environments setup-local`. Use when the user wants to set up or fix one for Databricks Connect, cluster or serverless compute, `--job-task`, or a bundle target, or when setup-local fails.
$ npx -y skills add databricks/databricks-agent-skills --skill databricks-setup-local --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/databricks-setup-localContext preview
The summary Claude sees to decide when to auto-load this skill.
Previews, provisions, or diagnoses a uv-managed local Python .venv with `databricks environments setup-local`. Use when the user wants to set up or fix one for Databricks Connect, cluster or serverless compute, `--job-task`, or a bundle target, or when setup-local fails.
name: databricks-setup-local description: "Previews, provisions, or diagnoses a uv-managed local Python .venv with `databricks environments setup-local`. Use when the user wants to set up or fix one for Databricks Connect, cluster or serverless compute, `--job-task`, or a bundle target, or when setup-local fails." compatibility: Requires databricks CLI (>= v1.12.0) and uv metadata: version: "0.1.0" parent: databricks-core
**REQUIRED FIRST:** Use `databricks-core` for CLI, authentication, and profile selection. Never use a default profile. For an existing environment, use `databricks-execution-compute`.
databricks version # must be >= v1.12.0 databricks auth describe --profile <PROFILE>
Prefer the latest stable CLI; no online lookup is required. Compare the full semantic version: v0.299.1 is older than v1.12.0. If missing or older, or `setup-local` is absent from help, reports `unknown command`, or rejects a documented flag, stop. Use `databricks-core` to upgrade with approval and verify; never recreate `setup-local` manually.
Use the selected profile for every workspace command. Do not convert another package manager without approval.
Confirm the root containing (or intended to contain) `pyproject.toml`, `.venv`, and `uv.lock`; ask if multiple roots are plausible. Use it for preview and apply. It must be greenfield or `uv`-managed, but need not be writable for preview.
Choose exactly one branch:
Never combine compute flags. If no branch resolves, ask the user.
Dry-run first; it writes and installs nothing:
databricks environments setup-local --profile <PROFILE> <TARGET_ARGS> --dry-run --output json
For bundles, `<TARGET_ARGS>` is empty or `--target <BUNDLE_TARGET>`. Default to normal mode. Use `--constraints-only` only when the user explicitly does not want this command managing `databricks-connect`. See [JSON output](references/json-output.md) and [examples](references/examples.md).
Before apply, verify the directory is writable and run `uv --version`. Ask before installing `uv`; never silently set `DATABRICKS_LOCALENV_AUTO_INSTALL_UV=1` or run a remote installer.
Show the target, versions, warnings, `plan.diff`, and directory. Explain that apply may:
For `--serverless-version N` in a bundle, also disclose the post-apply job YAML synchronization described below so approval covers both mutations.
Apply only after the user requested provisioning or approves that plan for the named directory. Preserve the directory, profile, target, and mode.
If the directory, profile, target, mode, or project files change after preview, rerun `--dry-run`, show the new plan, and obtain approval again. Treat its resolved Python, `databricks-connect`, and managed constraints as authoritative; do not substitute guessed versions. Reconcile user-owned dependency conflicts separately, with approval.
Skills for AI coding assistants (Claude Code, Cursor, etc.) that provide Databricks-specific guidance.
Repo: databricks/databricks-agent-skills
Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).
Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment,…
Create Databricks AI/BI dashboards. Must use when creating, updating, or deploying Lakeview dashboards as Databricks Dashboard have a unique json structure.…
Design the UX of custom-code Databricks Apps (AppKit/React) data screens — KPI/overview pages, reports, charts, tables, and Genie/chat data assistants — mapped…
Python backend for Databricks Apps — FastAPI (default), Flask, Dash, Streamlit, Gradio, Reflex. **Default for a new Databricks App is `databricks-apps` (AppKit…
Build apps on Databricks Apps platform. Use when asked to create data apps, analytics tools, or custom interactive visualizations. A plain \"create a…