Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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${workspace.current_user.domain_friendly_name}; override production with a stable name, and persist an explicit local value when the default is invalid, collides, or must distinguish multiple non-production targets in one workspace. On older CLI versions, require an explicit app_name value insteadBefore validating any bundle that creates or changes an App, re-read the final bundle YAML and confirm all of the following structural requirements:
name: ${var.app_name}, while preserving an existing equivalent variable when present.${workspace.current_user.domain_friendly_name} for development, and the production target overrides it with a stable name. On older CLI versions, App name variables have no default and each developer must provide values.${workspace.current_user.short_name}, a bare ${bundle.target}, or a hardcoded value.Only after this check, run databricks bundle validate --strict --target <target> --output json and inspect each resolved resources.apps.<key>.name. Each name must contain only lowercase letters, digits, and hyphens and be at most 30 characters. If a resolved name is invalid, collides after normalization, or multiple non-production targets share a workspace, persist a shorter, distinct value in the uncommitted .databricks/bundle/<target>/variable-overrides.json file and validate again. Successful validation alone does not satisfy this contract because validation does not catch every invalid or non-namespaced App name.
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概要と使いどころ
Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).
日本語の概要は準備中です。原文の説明を表示しています。
Use Databricks built-in AI Functions (ai_classify, ai_extract, ai_summarize, ai_mask, ai_translate, ai_fix_grammar, ai_gen, ai_analyze_sentiment, ai_similarity, ai_parse_document, ai_prep_search, ai_query, ai_forecast) to add AI capabilities directly to SQL and PySpark pipelines without managing model endpoints. Also covers document parsing and building custom RAG pipelines (parse → prep_search → index → query).
日本語の概要は準備中です。原文の説明を表示しています。
Databricks AI Runtime, the `databricks air` CLI commands for submitting and managing GPU training workloads on Databricks serverless compute. Use for: writing and submitting `databricks air` workload YAML, passing hyperparameters and secrets, checking run status, listing/cancelling runs, streaming a run's logs and watching its progress, custom Docker image setup, and environment configuration.
日本語の概要は準備中です。原文の説明を表示しています。
Create Databricks AI/BI dashboards. Must use when creating, updating, or deploying Lakeview dashboards as Databricks Dashboard have a unique json structure. CRITICAL: You MUST test ALL SQL queries via CLI BEFORE deploying. Follow guidelines strictly.
日本語の概要は準備中です。原文の説明を表示しています。
Design the UX of custom-code Databricks Apps (AppKit/React) data screens — KPI/overview pages, reports, charts, tables, and Genie/chat data assistants — mapped to concrete AppKit components. Use when BUILDING or reviewing the UI of an AppKit/React app that displays data or answers data questions: choosing genre, layout, charts, KPIs, semantic color, required states (loading/empty/error), IBCS notation, and AI-result trust (showing generated SQL/sources for Genie/chat). A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, NOT this skill. Also NOT for non-data frontend (forms, settings, auth, marketing) or scaffolding/build/deploy (→ databricks-apps). Complements databricks-apps; use it alongside whenever a custom app has a chart, table, KPI, report, or Genie/chat/AI surface.
日本語の概要は準備中です。原文の説明を表示しています。
Build apps on Databricks Apps platform. Use when asked to create data apps, analytics tools, or custom interactive visualizations. A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, not this skill. Evaluates data access patterns (analytics vs Lakebase synced tables) before scaffolding. Invoke BEFORE starting implementation.
日本語の概要は準備中です。原文の説明を表示しています。