菜单
Create, configure, validate, deploy, run, and manage Declarative Automation Bundles (DABs, formerly Databricks Asset Bundles). Use when working with Databricks resources via DABs including dashboards, jobs, pipelines, alerts, volumes, and apps.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Run the full cold-start end-to-end deploy test in an isolated git worktree with always-safe teardown. Use when: (1) verifying the one-shot `make deploy` works on a FRESH workspace/catalog (cold-start), (2) the user says 'integration test', 'cold-start test', 'test the deploy end to end', or 'does deploy still work on a new workspace', (3) validating a change to deploy.sh / databricks.yml / the seed before opening a PR. PROJECT-AUTHORED (not a vendored skill).
Keep this repo's architecture diagrams and prose docs in sync with the code as it evolves. Use this whenever the user asks to update/refresh the architecture diagrams, sync docs with the code, audit docs for staleness, or check that docs/architecture.md still matches the implementation — and proactively after any significant change (a new graph node, tool, Lakebase schema, data-pipeline step, auth change, or frontend swap), since the diagrams and READMEs drift silently. Covers refreshing the four Mermaid diagrams in docs/architecture.md, reconciling the known stale-doc patterns, and verifying with greps + Mermaid validity.
Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving tool selection accuracy, answer quality, reducing costs, or fixing issues where the agent gives wrong/incomplete responses. Evaluates agents systematically using MLflow evaluation with datasets, scorers, and tracing. IMPORTANT - Always also load the instrumenting-with-mlflow-tracing skill before starting any work. Covers end-to-end evaluation workflow or individual components (tracing setup, dataset creation, scorer definition, evaluation execution).
Build apps on Databricks Apps platform. Use when asked to create dashboards, data apps, analytics tools, or visualizations. Evaluates data access patterns (analytics vs Lakebase synced tables) before scaffolding. Invoke BEFORE starting implementation.
Databricks CLI operations: auth, profiles, data exploration, and bundles. Contains up-to-date guidelines for Databricks-related CLI tasks.
Databricks Lakebase Postgres: projects, scaling, connectivity, Lakebase synced tables, and Data API. Use when asked about Lakebase databases, OLTP storage, or connecting apps to Postgres on Databricks.
| name | databricks-dabs |
| description | Create, configure, validate, deploy, run, and manage Declarative Automation Bundles (DABs, formerly Databricks Asset Bundles). Use when working with Databricks resources via DABs including dashboards, jobs, pipelines, alerts, volumes, and apps. |
Use this skill for any bundle-related request including creating, configuring, validating, deploying, running, and managing Databricks resources through DABs.
The following reference files provide detailed guidance for specific bundle tasks:
Load this skill for any request involving:
bundle validate --strict --target <target> after any change<name>.<resource_type>.yml format