[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-databricks-databricks-docs":3,"mdc-nvn7e4-key":30,"related-repo-databricks-databricks-docs":398,"related-org-databricks-databricks-docs":520},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":20,"repoUrl":21,"updatedAt":22,"license":23,"forks":24,"topics":25,"repo":26,"sourceUrl":28,"mdContent":29},"databricks-docs","search Databricks documentation","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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"databricks","Databricks","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fdatabricks.png",[12,16,19],{"name":13,"slug":14,"type":15},"Documentation","documentation","tag",{"name":17,"slug":18,"type":15},"Reference","reference",{"name":9,"slug":8,"type":15},204,"https:\u002F\u002Fgithub.com\u002Fdatabricks\u002Fdatabricks-agent-skills","2026-07-15T05:41:34.697746",null,60,[],{"repoUrl":21,"stars":20,"forks":24,"topics":27,"description":23},[],"https:\u002F\u002Fgithub.com\u002Fdatabricks\u002Fdatabricks-agent-skills\u002Ftree\u002FHEAD\u002Fplugins\u002Fdatabricks\u002Fcopilot\u002Fskills\u002Fdatabricks-docs","---\nname: databricks-docs\ndescription: \"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.\"\ncompatibility: Requires databricks CLI (>= v1.0.0)\nmetadata:\n  version: \"0.1.0\"\nparent: databricks-core\n---\n\n# Databricks Documentation Reference\n\nThis skill provides access to the complete Databricks documentation index via llms.txt - use it as a **reference resource** to supplement other skills.\n\n## Role of This Skill\n\nThis is a **reference skill**, not an action skill. Use it to:\n\n- Look up documentation when other skills don't cover a topic\n- Get authoritative guidance on Databricks concepts and APIs\n- Find detailed information to inform CLI commands and SDK usage\n- Discover features and capabilities you may not know about\n\n**Always prefer using CLI\u002FSDK for actions** and **load specific skills for workflows** (databricks-python-sdk, databricks-spark-declarative-pipelines, etc.). Use this skill when you need reference documentation.\n\n## How to Use\n\nFetch the llms.txt documentation index:\n\n**URL:** `https:\u002F\u002Fdocs.databricks.com\u002Fllms.txt`\n\nUse WebFetch to retrieve this index, then:\n\n1. Search for relevant sections\u002Flinks\n2. Fetch specific documentation pages for detailed guidance\n3. Apply what you learn using the appropriate CLI commands or SDK\n\n## Documentation Structure\n\nThe llms.txt file is organized by category:\n\n- **Overview & Getting Started** - Basic concepts and tutorials\n- **Data Engineering** - Lakeflow, Spark, Delta Lake, pipelines\n- **SQL & Analytics** - Warehouses, queries, dashboards\n- **AI\u002FML** - MLflow, model serving, GenAI\n- **Governance** - Unity Catalog, permissions, security\n- **Developer Tools** - SDKs, CLI, APIs, Terraform\n\n## Example: Complementing Other Skills\n\n**Scenario:** User wants to create a Delta Live Tables pipeline\n\n1. Load `databricks-spark-declarative-pipelines` skill for workflow patterns\n2. Use this skill to fetch docs if you need clarification on specific DLT features\n3. Use `databricks pipelines create` CLI command to create the pipeline\n\n**Scenario:** User asks about an unfamiliar Databricks feature\n\n1. Fetch llms.txt to find relevant documentation\n2. Read the specific docs to understand the feature\n3. Determine which skill\u002Ftools apply, then use them\n\n## Related Skills\n\n- **[databricks-python-sdk](..\u002Fdatabricks-python-sdk\u002FSKILL.md)** - SDK patterns for programmatic Databricks access\n- **databricks-pipelines** - DLT \u002F Lakeflow pipeline workflows\n- **[databricks-unity-catalog](..\u002Fdatabricks-unity-catalog\u002FSKILL.md)** - Governance and catalog management\n- **databricks-model-serving** - Serving endpoints and model deployment\n- **[databricks-mlflow-evaluation](..\u002Fdatabricks-mlflow-evaluation\u002FSKILL.md)** - MLflow 3 GenAI evaluation workflows\n",{"data":31,"body":36},{"name":4,"description":6,"compatibility":32,"metadata":33,"parent":35},"Requires databricks CLI (>= v1.0.0)",{"version":34},"0.1.0","databricks-core",{"type":37,"children":38},"root",[39,48,62,69,81,106,123,129,134,151,156,175,181,186,249,255,265,299,308,326,332],{"type":40,"tag":41,"props":42,"children":44},"element","h1",{"id":43},"databricks-documentation-reference",[45],{"type":46,"value":47},"text","Databricks Documentation Reference",{"type":40,"tag":49,"props":50,"children":51},"p",{},[52,54,60],{"type":46,"value":53},"This skill provides access to the complete Databricks documentation index via llms.txt - use it as a ",{"type":40,"tag":55,"props":56,"children":57},"strong",{},[58],{"type":46,"value":59},"reference resource",{"type":46,"value":61}," to supplement other skills.",{"type":40,"tag":63,"props":64,"children":66},"h2",{"id":65},"role-of-this-skill",[67],{"type":46,"value":68},"Role of This Skill",{"type":40,"tag":49,"props":70,"children":71},{},[72,74,79],{"type":46,"value":73},"This is a ",{"type":40,"tag":55,"props":75,"children":76},{},[77],{"type":46,"value":78},"reference skill",{"type":46,"value":80},", not an action skill. Use it to:",{"type":40,"tag":82,"props":83,"children":84},"ul",{},[85,91,96,101],{"type":40,"tag":86,"props":87,"children":88},"li",{},[89],{"type":46,"value":90},"Look up documentation when other skills don't cover a topic",{"type":40,"tag":86,"props":92,"children":93},{},[94],{"type":46,"value":95},"Get authoritative guidance on Databricks concepts and APIs",{"type":40,"tag":86,"props":97,"children":98},{},[99],{"type":46,"value":100},"Find detailed information to inform CLI commands and SDK usage",{"type":40,"tag":86,"props":102,"children":103},{},[104],{"type":46,"value":105},"Discover features and capabilities you may not know about",{"type":40,"tag":49,"props":107,"children":108},{},[109,114,116,121],{"type":40,"tag":55,"props":110,"children":111},{},[112],{"type":46,"value":113},"Always prefer using CLI\u002FSDK for actions",{"type":46,"value":115}," and ",{"type":40,"tag":55,"props":117,"children":118},{},[119],{"type":46,"value":120},"load specific skills for workflows",{"type":46,"value":122}," (databricks-python-sdk, databricks-spark-declarative-pipelines, etc.). Use this skill when you need reference documentation.",{"type":40,"tag":63,"props":124,"children":126},{"id":125},"how-to-use",[127],{"type":46,"value":128},"How to Use",{"type":40,"tag":49,"props":130,"children":131},{},[132],{"type":46,"value":133},"Fetch the llms.txt documentation index:",{"type":40,"tag":49,"props":135,"children":136},{},[137,142,144],{"type":40,"tag":55,"props":138,"children":139},{},[140],{"type":46,"value":141},"URL:",{"type":46,"value":143}," ",{"type":40,"tag":145,"props":146,"children":148},"code",{"className":147},[],[149],{"type":46,"value":150},"https:\u002F\u002Fdocs.databricks.com\u002Fllms.txt",{"type":40,"tag":49,"props":152,"children":153},{},[154],{"type":46,"value":155},"Use WebFetch to retrieve this index, then:",{"type":40,"tag":157,"props":158,"children":159},"ol",{},[160,165,170],{"type":40,"tag":86,"props":161,"children":162},{},[163],{"type":46,"value":164},"Search for relevant sections\u002Flinks",{"type":40,"tag":86,"props":166,"children":167},{},[168],{"type":46,"value":169},"Fetch specific documentation pages for detailed guidance",{"type":40,"tag":86,"props":171,"children":172},{},[173],{"type":46,"value":174},"Apply what you learn using the appropriate CLI commands or SDK",{"type":40,"tag":63,"props":176,"children":178},{"id":177},"documentation-structure",[179],{"type":46,"value":180},"Documentation Structure",{"type":40,"tag":49,"props":182,"children":183},{},[184],{"type":46,"value":185},"The llms.txt file is organized by category:",{"type":40,"tag":82,"props":187,"children":188},{},[189,199,209,219,229,239],{"type":40,"tag":86,"props":190,"children":191},{},[192,197],{"type":40,"tag":55,"props":193,"children":194},{},[195],{"type":46,"value":196},"Overview & Getting Started",{"type":46,"value":198}," - Basic concepts and tutorials",{"type":40,"tag":86,"props":200,"children":201},{},[202,207],{"type":40,"tag":55,"props":203,"children":204},{},[205],{"type":46,"value":206},"Data Engineering",{"type":46,"value":208}," - Lakeflow, Spark, Delta Lake, pipelines",{"type":40,"tag":86,"props":210,"children":211},{},[212,217],{"type":40,"tag":55,"props":213,"children":214},{},[215],{"type":46,"value":216},"SQL & Analytics",{"type":46,"value":218}," - Warehouses, queries, dashboards",{"type":40,"tag":86,"props":220,"children":221},{},[222,227],{"type":40,"tag":55,"props":223,"children":224},{},[225],{"type":46,"value":226},"AI\u002FML",{"type":46,"value":228}," - MLflow, model serving, GenAI",{"type":40,"tag":86,"props":230,"children":231},{},[232,237],{"type":40,"tag":55,"props":233,"children":234},{},[235],{"type":46,"value":236},"Governance",{"type":46,"value":238}," - Unity Catalog, permissions, security",{"type":40,"tag":86,"props":240,"children":241},{},[242,247],{"type":40,"tag":55,"props":243,"children":244},{},[245],{"type":46,"value":246},"Developer Tools",{"type":46,"value":248}," - SDKs, CLI, APIs, Terraform",{"type":40,"tag":63,"props":250,"children":252},{"id":251},"example-complementing-other-skills",[253],{"type":46,"value":254},"Example: Complementing Other Skills",{"type":40,"tag":49,"props":256,"children":257},{},[258,263],{"type":40,"tag":55,"props":259,"children":260},{},[261],{"type":46,"value":262},"Scenario:",{"type":46,"value":264}," User wants to create a Delta Live Tables pipeline",{"type":40,"tag":157,"props":266,"children":267},{},[268,281,286],{"type":40,"tag":86,"props":269,"children":270},{},[271,273,279],{"type":46,"value":272},"Load ",{"type":40,"tag":145,"props":274,"children":276},{"className":275},[],[277],{"type":46,"value":278},"databricks-spark-declarative-pipelines",{"type":46,"value":280}," skill for workflow patterns",{"type":40,"tag":86,"props":282,"children":283},{},[284],{"type":46,"value":285},"Use this skill to fetch docs if you need clarification on specific DLT features",{"type":40,"tag":86,"props":287,"children":288},{},[289,291,297],{"type":46,"value":290},"Use ",{"type":40,"tag":145,"props":292,"children":294},{"className":293},[],[295],{"type":46,"value":296},"databricks pipelines create",{"type":46,"value":298}," CLI command to create the pipeline",{"type":40,"tag":49,"props":300,"children":301},{},[302,306],{"type":40,"tag":55,"props":303,"children":304},{},[305],{"type":46,"value":262},{"type":46,"value":307}," User asks about an unfamiliar Databricks feature",{"type":40,"tag":157,"props":309,"children":310},{},[311,316,321],{"type":40,"tag":86,"props":312,"children":313},{},[314],{"type":46,"value":315},"Fetch llms.txt to find relevant documentation",{"type":40,"tag":86,"props":317,"children":318},{},[319],{"type":46,"value":320},"Read the specific docs to understand the feature",{"type":40,"tag":86,"props":322,"children":323},{},[324],{"type":46,"value":325},"Determine which skill\u002Ftools apply, then use them",{"type":40,"tag":63,"props":327,"children":329},{"id":328},"related-skills",[330],{"type":46,"value":331},"Related Skills",{"type":40,"tag":82,"props":333,"children":334},{},[335,350,360,374,384],{"type":40,"tag":86,"props":336,"children":337},{},[338,348],{"type":40,"tag":55,"props":339,"children":340},{},[341],{"type":40,"tag":342,"props":343,"children":345},"a",{"href":344},"..\u002Fdatabricks-python-sdk\u002FSKILL.md",[346],{"type":46,"value":347},"databricks-python-sdk",{"type":46,"value":349}," - SDK patterns for programmatic Databricks access",{"type":40,"tag":86,"props":351,"children":352},{},[353,358],{"type":40,"tag":55,"props":354,"children":355},{},[356],{"type":46,"value":357},"databricks-pipelines",{"type":46,"value":359}," - DLT \u002F Lakeflow pipeline workflows",{"type":40,"tag":86,"props":361,"children":362},{},[363,372],{"type":40,"tag":55,"props":364,"children":365},{},[366],{"type":40,"tag":342,"props":367,"children":369},{"href":368},"..\u002Fdatabricks-unity-catalog\u002FSKILL.md",[370],{"type":46,"value":371},"databricks-unity-catalog",{"type":46,"value":373}," - Governance and catalog management",{"type":40,"tag":86,"props":375,"children":376},{},[377,382],{"type":40,"tag":55,"props":378,"children":379},{},[380],{"type":46,"value":381},"databricks-model-serving",{"type":46,"value":383}," - Serving endpoints and model deployment",{"type":40,"tag":86,"props":385,"children":386},{},[387,396],{"type":40,"tag":55,"props":388,"children":389},{},[390],{"type":40,"tag":342,"props":391,"children":393},{"href":392},"..\u002Fdatabricks-mlflow-evaluation\u002FSKILL.md",[394],{"type":46,"value":395},"databricks-mlflow-evaluation",{"type":46,"value":397}," - MLflow 3 GenAI evaluation workflows",{"items":399,"total":519},[400,417,431,448,465,485,496],{"slug":401,"name":401,"fn":402,"description":403,"org":404,"tags":405,"stars":20,"repoUrl":21,"updatedAt":416},"databricks-agent-bricks","create Databricks Agent Bricks","Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[406,409,410,413],{"name":407,"slug":408,"type":15},"Agents","agents",{"name":9,"slug":8,"type":15},{"name":411,"slug":412,"type":15},"Knowledge Management","knowledge-management",{"name":414,"slug":415,"type":15},"Multi-Agent","multi-agent","2026-07-15T05:41:38.548954",{"slug":418,"name":418,"fn":419,"description":420,"org":421,"tags":422,"stars":20,"repoUrl":21,"updatedAt":430},"databricks-ai-functions","use Databricks built-in AI functions","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).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[423,426,427],{"name":424,"slug":425,"type":15},"Data Analysis","data-analysis",{"name":9,"slug":8,"type":15},{"name":428,"slug":429,"type":15},"LLM","llm","2026-07-31T05:53:33.562077",{"slug":432,"name":432,"fn":433,"description":434,"org":435,"tags":436,"stars":20,"repoUrl":21,"updatedAt":447},"databricks-ai-runtime","submit and manage Databricks GPU workloads","Databricks AI Runtime (`air`) CLI — the command-line tool for submitting and managing GPU training workloads on Databricks serverless compute. Use for: running `air` workloads, custom Docker image setup, environment configuration, and troubleshooting `air` jobs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[437,440,441,444],{"name":438,"slug":439,"type":15},"CLI","cli",{"name":9,"slug":8,"type":15},{"name":442,"slug":443,"type":15},"Docker","docker",{"name":445,"slug":446,"type":15},"Engineering","engineering","2026-07-12T08:04:55.843982",{"slug":449,"name":449,"fn":450,"description":451,"org":452,"tags":453,"stars":20,"repoUrl":21,"updatedAt":464},"databricks-aibi-dashboards","create Databricks AI\u002FBI dashboards","Create Databricks AI\u002FBI 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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[454,457,460,463],{"name":455,"slug":456,"type":15},"Analytics","analytics",{"name":458,"slug":459,"type":15},"Dashboards","dashboards",{"name":461,"slug":462,"type":15},"Data Visualization","data-visualization",{"name":9,"slug":8,"type":15},"2026-07-12T08:04:25.314591",{"slug":466,"name":466,"fn":467,"description":468,"org":469,"tags":470,"stars":20,"repoUrl":21,"updatedAt":484},"databricks-app-design","design UX for Databricks AppKit applications","Design the UX of custom-code Databricks Apps (AppKit\u002FReact) data screens — KPI\u002Foverview pages, reports, charts, tables, and Genie\u002Fchat data assistants — mapped to concrete AppKit components. Use when BUILDING or reviewing the UI of an AppKit\u002FReact app that displays data or answers data questions: choosing genre, layout, charts, KPIs, semantic color, required states (loading\u002Fempty\u002Ferror), IBCS notation, and AI-result trust (showing generated SQL\u002Fsources for Genie\u002Fchat). A plain \"create a dashboard\" request means a managed AI\u002FBI (Lakeview) dashboard → use databricks-aibi-dashboards, NOT this skill. Also NOT for non-data frontend (forms, settings, auth, marketing) or scaffolding\u002Fbuild\u002Fdeploy (→ databricks-apps). Complements databricks-apps; use it alongside whenever a custom app has a chart, table, KPI, report, or Genie\u002Fchat\u002FAI surface.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[471,472,475,478,481],{"name":9,"slug":8,"type":15},{"name":473,"slug":474,"type":15},"Design","design",{"name":476,"slug":477,"type":15},"Frontend","frontend",{"name":479,"slug":480,"type":15},"React","react",{"name":482,"slug":483,"type":15},"UI Components","ui-components","2026-07-12T08:04:02.02398",{"slug":486,"name":486,"fn":487,"description":488,"org":489,"tags":490,"stars":20,"repoUrl":21,"updatedAt":495},"databricks-apps","build applications on Databricks Apps","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\u002FBI (Lakeview) dashboard → use databricks-aibi-dashboards, not this skill. Evaluates data access patterns (analytics vs Lakebase synced tables) before scaffolding. Invoke BEFORE starting implementation.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[491,492,493,494],{"name":455,"slug":456,"type":15},{"name":458,"slug":459,"type":15},{"name":424,"slug":425,"type":15},{"name":9,"slug":8,"type":15},"2026-07-12T08:03:59.061458",{"slug":497,"name":497,"fn":498,"description":499,"org":500,"tags":501,"stars":20,"repoUrl":21,"updatedAt":518},"databricks-apps-python","build Python backends for Databricks Apps","Python backend for Databricks Apps — FastAPI (default), Flask, Dash, Streamlit, Gradio, Reflex. **Default for a new Databricks App is `databricks-apps` (AppKit — Node\u002FTypeScript\u002FReact) — reach for it first.** Use this skill only when the user asks for a Python backend, extends an existing Python app, or the team is Python-only. Covers OAuth auth, app resources, SQL warehouse and Lakebase connectivity, foundation-model \u002F Vector Search \u002F model-serving APIs (via `databricks-python-sdk`), and deployment via CLI or DABs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[502,503,506,509,512,515],{"name":9,"slug":8,"type":15},{"name":504,"slug":505,"type":15},"FastAPI","fastapi",{"name":507,"slug":508,"type":15},"Flask","flask",{"name":510,"slug":511,"type":15},"Gradio","gradio",{"name":513,"slug":514,"type":15},"Python","python",{"name":516,"slug":517,"type":15},"Streamlit","streamlit","2026-07-12T08:04:10.970845",31,{"items":521,"total":519},[522,529,535,542,549,557,564,573,584,601,615,628],{"slug":401,"name":401,"fn":402,"description":403,"org":523,"tags":524,"stars":20,"repoUrl":21,"updatedAt":416},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[525,526,527,528],{"name":407,"slug":408,"type":15},{"name":9,"slug":8,"type":15},{"name":411,"slug":412,"type":15},{"name":414,"slug":415,"type":15},{"slug":418,"name":418,"fn":419,"description":420,"org":530,"tags":531,"stars":20,"repoUrl":21,"updatedAt":430},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[532,533,534],{"name":424,"slug":425,"type":15},{"name":9,"slug":8,"type":15},{"name":428,"slug":429,"type":15},{"slug":432,"name":432,"fn":433,"description":434,"org":536,"tags":537,"stars":20,"repoUrl":21,"updatedAt":447},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[538,539,540,541],{"name":438,"slug":439,"type":15},{"name":9,"slug":8,"type":15},{"name":442,"slug":443,"type":15},{"name":445,"slug":446,"type":15},{"slug":449,"name":449,"fn":450,"description":451,"org":543,"tags":544,"stars":20,"repoUrl":21,"updatedAt":464},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[545,546,547,548],{"name":455,"slug":456,"type":15},{"name":458,"slug":459,"type":15},{"name":461,"slug":462,"type":15},{"name":9,"slug":8,"type":15},{"slug":466,"name":466,"fn":467,"description":468,"org":550,"tags":551,"stars":20,"repoUrl":21,"updatedAt":484},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[552,553,554,555,556],{"name":9,"slug":8,"type":15},{"name":473,"slug":474,"type":15},{"name":476,"slug":477,"type":15},{"name":479,"slug":480,"type":15},{"name":482,"slug":483,"type":15},{"slug":486,"name":486,"fn":487,"description":488,"org":558,"tags":559,"stars":20,"repoUrl":21,"updatedAt":495},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[560,561,562,563],{"name":455,"slug":456,"type":15},{"name":458,"slug":459,"type":15},{"name":424,"slug":425,"type":15},{"name":9,"slug":8,"type":15},{"slug":497,"name":497,"fn":498,"description":499,"org":565,"tags":566,"stars":20,"repoUrl":21,"updatedAt":518},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[567,568,569,570,571,572],{"name":9,"slug":8,"type":15},{"name":504,"slug":505,"type":15},{"name":507,"slug":508,"type":15},{"name":510,"slug":511,"type":15},{"name":513,"slug":514,"type":15},{"name":516,"slug":517,"type":15},{"slug":35,"name":35,"fn":574,"description":575,"org":576,"tags":577,"stars":20,"repoUrl":21,"updatedAt":583},"configure Databricks CLI and authentication","Databricks CLI operations and the parent\u002Fentry-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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[578,581,582],{"name":579,"slug":580,"type":15},"Authentication","authentication",{"name":438,"slug":439,"type":15},{"name":9,"slug":8,"type":15},"2026-07-18T05:11:05.45506",{"slug":585,"name":585,"fn":586,"description":587,"org":588,"tags":589,"stars":20,"repoUrl":21,"updatedAt":600},"databricks-dabs","manage Databricks Declarative Automation Bundles","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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[590,593,596,597],{"name":591,"slug":592,"type":15},"Automation","automation",{"name":594,"slug":595,"type":15},"Configuration","configuration",{"name":9,"slug":8,"type":15},{"name":598,"slug":599,"type":15},"Deployment","deployment","2026-07-15T05:41:35.930355",{"slug":602,"name":602,"fn":603,"description":604,"org":605,"tags":606,"stars":20,"repoUrl":21,"updatedAt":614},"databricks-data-discovery","discover and query Databricks data","Discover, explore, and query Databricks data via Genie — the CLI equivalent of the Genie One MCP. MUST be invoked whenever the user asks to find or locate data ('what tables are in X', 'where does X live', 'which catalog\u002Fschema has Y'), answer a natural-language question about the data, or write a SQL query.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[607,608,610,611],{"name":424,"slug":425,"type":15},{"name":206,"slug":609,"type":15},"data-engineering",{"name":9,"slug":8,"type":15},{"name":612,"slug":613,"type":15},"SQL","sql","2026-07-31T05:53:32.561877",{"slug":616,"name":616,"fn":617,"description":618,"org":619,"tags":620,"stars":20,"repoUrl":21,"updatedAt":627},"databricks-dbsql","query and script Databricks SQL warehouses","Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities. This skill MUST be invoked when the user mentions: \"DBSQL\", \"Databricks SQL\", \"SQL warehouse\", \"SQL scripting\", \"stored procedure\", \"CALL procedure\", \"materialized view\", \"CREATE MATERIALIZED VIEW\", \"pipe syntax\", \"|>\", \"geospatial\", \"H3\", \"ST_\", \"spatial SQL\", \"collation\", \"COLLATE\", \"ai_query\", \"ai_classify\", \"ai_extract\", \"ai_gen\", \"AI function\", \"http_request\", \"remote_query\", \"read_files\", \"Lakehouse Federation\", \"recursive CTE\", \"WITH RECURSIVE\", \"multi-statement transaction\", \"temp table\", \"temporary view\", \"pipe operator\". SHOULD also invoke when the user asks about SQL best practices, data modeling patterns, or advanced SQL features on Databricks.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[621,622,625,626],{"name":424,"slug":425,"type":15},{"name":623,"slug":624,"type":15},"Database","database",{"name":9,"slug":8,"type":15},{"name":612,"slug":613,"type":15},"2026-07-12T08:04:08.678282",{"slug":4,"name":4,"fn":5,"description":6,"org":629,"tags":630,"stars":20,"repoUrl":21,"updatedAt":22},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[631,632,633],{"name":9,"slug":8,"type":15},{"name":13,"slug":14,"type":15},{"name":17,"slug":18,"type":15}]