Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).
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databricks/databricks-agent-skills3522026년 10월 18일 업데이트
무료GitHub에 공개
databricks-docs
Databricks documentation reference via llms.txt index. Use when other skills do not cover a topic, looking up unfamiliar Databricks features, or needing authoritative docs on APIs, configurations, or platform capabilities.
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설치 방법 보기포함된 파일(4)
- SKILL.md2.8 KB
- agents/openai.yaml328 B
- assets/databricks.png15.0 KB
- assets/databricks.svg582 B
SKILL.md(원문)
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Databricks Documentation Reference
This skill provides access to the complete Databricks documentation index via llms.txt - use it as a reference resource to supplement other skills.
Role of This Skill
This is a reference skill, not an action skill. Use it to:
- Look up documentation when other skills don't cover a topic
- Get authoritative guidance on Databricks concepts and APIs
- Find detailed information to inform CLI commands and SDK usage
- Discover features and capabilities you may not know about
Always prefer using CLI/SDK for actions and load specific skills for workflows (databricks-python-sdk, databricks-spark-declarative-pipelines, etc.). Use this skill when you need reference documentation.
How to Use
Fetch the llms.txt documentation index:
URL: https://docs.databricks.com/llms.txt
Use WebFetch to retrieve this index, then:
- Search for relevant sections/links
- Fetch specific documentation pages for detailed guidance
- Apply what you learn using the appropriate CLI commands or SDK
Documentation Structure
The llms.txt file is organized by category:
- Overview & Getting Started - Basic concepts and tutorials
- Data Engineering - Lakeflow, Spark, Delta Lake, pipelines
- SQL & Analytics - Warehouses, queries, dashboards
- AI/ML - MLflow, model serving, GenAI
- Governance - Unity Catalog, permissions, security
- Developer Tools - SDKs, CLI, APIs, Terraform
Example: Complementing Other Skills
Scenario: User wants to create a Delta Live Tables pipeline
- Load
databricks-spark-declarative-pipelinesskill for workflow patterns - Use this skill to fetch docs if you need clarification on specific DLT features
- Use
databricks pipelines createCLI command to create the pipeline
Scenario: User asks about an unfamiliar Databricks feature
- Fetch llms.txt to find relevant documentation
- Read the specific docs to understand the feature
- Determine which skill/tools apply, then use them
Related Skills
- databricks-python-sdk - SDK patterns for programmatic Databricks access
- databricks-pipelines - DLT / Lakeflow pipeline workflows
- databricks-unity-catalog - Governance and catalog management
- databricks-model-serving - Serving endpoints and model deployment
- databricks-mlflow-evaluation - MLflow 3 GenAI evaluation workflows
리뷰
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댓글
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같은 저장소의 스킬
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).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
databricks/databricks-agent-skills3522026년 10월 18일 업데이트
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.
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databricks/databricks-agent-skills3522026년 10월 18일 업데이트
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.
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databricks/databricks-agent-skills3522026년 10월 18일 업데이트
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.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
databricks/databricks-agent-skills3522026년 10월 18일 업데이트
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.
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databricks/databricks-agent-skills3522026년 10월 18일 업데이트