[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-dbt-labs-agents-schema-search":3,"mdc--u7hvmh-key":37,"related-org-dbt-labs-agents-schema-search":122,"related-repo-dbt-labs-agents-schema-search":290},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":27,"repoUrl":28,"updatedAt":29,"license":30,"forks":31,"topics":32,"repo":33,"sourceUrl":35,"mdContent":36},"agents-schema-search","search and query data warehouse metadata","Use when answering questions about data in a warehouse (BigQuery, Snowflake, etc.) and you have direct SQL access (CLI, driver, or console). Discover metadata and run knowledge search through the warehouse-native AGENTS schema instead of INFORMATION_SCHEMA.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"dbt-labs","dbt Labs","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fdbt-labs.png",[12,16,19,21,24],{"name":13,"slug":14,"type":15},"Data Warehouse","data-warehouse","tag",{"name":17,"slug":18,"type":15},"Database","database",{"name":20,"slug":20,"type":15},"dbt",{"name":22,"slug":23,"type":15},"Search","search",{"name":25,"slug":26,"type":15},"SQL","sql",32,"https:\u002F\u002Fgithub.com\u002Fdbt-labs\u002Fagents_schema","2026-07-21T06:07:35.165407",null,2,[],{"repoUrl":28,"stars":27,"forks":31,"topics":34,"description":30},[],"https:\u002F\u002Fgithub.com\u002Fdbt-labs\u002Fagents_schema\u002Ftree\u002FHEAD\u002Fplugins\u002Fagents-schema\u002Fskills\u002Fagents-schema-search","---\nname: agents-schema-search\ndescription: >\n  Use when answering questions about data in a warehouse (BigQuery, Snowflake, etc.) and you have direct SQL access (CLI, driver, or console). Discover metadata and run knowledge search through the warehouse-native AGENTS schema instead of INFORMATION_SCHEMA.\n---\n\n# Answering warehouse-data questions via the AGENTS schema\n\nBefore answering a warehouse-data question, read the warehouse AGENTS schema.\n\nAGENTS.ROOT is the entry point for the warehouse-native Agents Schema. It tells\nAI agents which providers have published metadata and how to use their\nprovider-specific tables.\n\nUse AGENTS as the warehouse metadata and discovery surface. Treat it like an\nagent-oriented alternative to INFORMATION_SCHEMA: inspect AGENTS.ROOT and the\nprovider-specific AGENTS.* tables instead of querying INFORMATION_SCHEMA\ndirectly. Only fall back to INFORMATION_SCHEMA when the AGENTS content\nexplicitly says to verify live metadata, or when required metadata is missing\nfrom AGENTS.\n\nUse your connection's SQL dialect (e.g. GoogleSQL on BigQuery), and quote\nschema and table identifiers using that dialect. Run read-only SELECT\nstatements only.\n\nRequired first query:\n\n```sql\nSELECT * FROM AGENTS.ROOT ORDER BY provider, key;\n```\n\nThen follow the provider guidance returned in the `content` column.\n\nIf no rows are returned, or the AGENTS schema or the AGENTS.ROOT table is not\nfound, tell the user that their AGENTS schema is not set up yet.\n",{"data":38,"body":39},{"name":4,"description":6},{"type":40,"children":41},"root",[42,51,57,62,67,72,77,98,111,116],{"type":43,"tag":44,"props":45,"children":47},"element","h1",{"id":46},"answering-warehouse-data-questions-via-the-agents-schema",[48],{"type":49,"value":50},"text","Answering warehouse-data questions via the AGENTS schema",{"type":43,"tag":52,"props":53,"children":54},"p",{},[55],{"type":49,"value":56},"Before answering a warehouse-data question, read the warehouse AGENTS schema.",{"type":43,"tag":52,"props":58,"children":59},{},[60],{"type":49,"value":61},"AGENTS.ROOT is the entry point for the warehouse-native Agents Schema. It tells\nAI agents which providers have published metadata and how to use their\nprovider-specific tables.",{"type":43,"tag":52,"props":63,"children":64},{},[65],{"type":49,"value":66},"Use AGENTS as the warehouse metadata and discovery surface. Treat it like an\nagent-oriented alternative to INFORMATION_SCHEMA: inspect AGENTS.ROOT and the\nprovider-specific AGENTS.* tables instead of querying INFORMATION_SCHEMA\ndirectly. Only fall back to INFORMATION_SCHEMA when the AGENTS content\nexplicitly says to verify live metadata, or when required metadata is missing\nfrom AGENTS.",{"type":43,"tag":52,"props":68,"children":69},{},[70],{"type":49,"value":71},"Use your connection's SQL dialect (e.g. GoogleSQL on BigQuery), and quote\nschema and table identifiers using that dialect. Run read-only SELECT\nstatements only.",{"type":43,"tag":52,"props":73,"children":74},{},[75],{"type":49,"value":76},"Required first query:",{"type":43,"tag":78,"props":79,"children":83},"pre",{"className":80,"code":81,"language":26,"meta":82,"style":82},"language-sql shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","SELECT * FROM AGENTS.ROOT ORDER BY provider, key;\n","",[84],{"type":43,"tag":85,"props":86,"children":87},"code",{"__ignoreMap":82},[88],{"type":43,"tag":89,"props":90,"children":93},"span",{"class":91,"line":92},"line",1,[94],{"type":43,"tag":89,"props":95,"children":96},{},[97],{"type":49,"value":81},{"type":43,"tag":52,"props":99,"children":100},{},[101,103,109],{"type":49,"value":102},"Then follow the provider guidance returned in the ",{"type":43,"tag":85,"props":104,"children":106},{"className":105},[],[107],{"type":49,"value":108},"content",{"type":49,"value":110}," column.",{"type":43,"tag":52,"props":112,"children":113},{},[114],{"type":49,"value":115},"If no rows are returned, or the AGENTS schema or the AGENTS.ROOT table is not\nfound, tell the user that their AGENTS schema is not set up yet.",{"type":43,"tag":117,"props":118,"children":119},"style",{},[120],{"type":49,"value":121},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":123,"total":289},[124,140,158,171,185,202,214,229,241,253,265,276],{"slug":125,"name":125,"fn":126,"description":127,"org":128,"tags":129,"stars":137,"repoUrl":138,"updatedAt":139},"adding-dbt-unit-test","add dbt unit tests","Creates unit test YAML definitions that mock upstream model inputs and validate expected outputs. Use when adding unit tests for a dbt model or practicing test-driven development (TDD) in dbt.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[130,131,134],{"name":20,"slug":20,"type":15},{"name":132,"slug":133,"type":15},"Testing","testing",{"name":135,"slug":136,"type":15},"YAML","yaml",623,"https:\u002F\u002Fgithub.com\u002Fdbt-labs\u002Fdbt-agent-skills","2026-04-06T18:09:14.01391",{"slug":141,"name":141,"fn":142,"description":143,"org":144,"tags":145,"stars":137,"repoUrl":138,"updatedAt":157},"answering-natural-language-questions-with-dbt","answer business questions using dbt Semantic Layer","Writes and executes SQL queries against the data warehouse using dbt's Semantic Layer or ad-hoc SQL to answer business questions. Use when a user asks about analytics, metrics, KPIs, or data (e.g., \"What were total sales last quarter?\", \"Show me top customers by revenue\"). NOT for validating, testing, or building dbt models during development.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[146,149,152,153,156],{"name":147,"slug":148,"type":15},"Analytics","analytics",{"name":150,"slug":151,"type":15},"Data Analysis","data-analysis",{"name":20,"slug":20,"type":15},{"name":154,"slug":155,"type":15},"Metrics","metrics",{"name":25,"slug":26,"type":15},"2026-04-06T18:09:07.651959",{"slug":159,"name":159,"fn":160,"description":161,"org":162,"tags":163,"stars":137,"repoUrl":138,"updatedAt":170},"building-dbt-semantic-layer","build dbt Semantic Layer components","Use when creating or modifying dbt Semantic Layer components — semantic models, metrics, dimensions, entities, measures, or time spines. Covers MetricFlow configuration, metric types (simple, derived, cumulative, ratio, conversion), and validation for both latest and legacy YAML specs.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[164,165,168,169],{"name":147,"slug":148,"type":15},{"name":166,"slug":167,"type":15},"Data Engineering","data-engineering",{"name":20,"slug":20,"type":15},{"name":154,"slug":155,"type":15},"2026-07-18T05:12:20.387564",{"slug":172,"name":172,"fn":173,"description":174,"org":175,"tags":176,"stars":137,"repoUrl":138,"updatedAt":184},"configuring-dbt-mcp-server","configure dbt MCP server","Generates MCP server configuration JSON, resolves authentication setup, and validates server connectivity for dbt. Use when setting up, configuring, or troubleshooting the dbt MCP server for AI tools like Claude Desktop, Claude Code, Cursor, or VS Code.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[177,180,181],{"name":178,"slug":179,"type":15},"Agent Context","agent-context",{"name":20,"slug":20,"type":15},{"name":182,"slug":183,"type":15},"MCP","mcp","2026-04-06T18:09:12.757804",{"slug":186,"name":186,"fn":187,"description":188,"org":189,"tags":190,"stars":137,"repoUrl":138,"updatedAt":201},"creating-mermaid-dbt-dag","generate Mermaid diagrams of dbt model lineage","Generates a Mermaid flowchart diagram of dbt model lineage using MCP tools, manifest.json, or direct code parsing as fallbacks. Use when visualizing dbt model lineage and dependencies as a Mermaid diagram in markdown format.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[191,194,195,198],{"name":192,"slug":193,"type":15},"Data Pipeline","data-pipeline",{"name":20,"slug":20,"type":15},{"name":196,"slug":197,"type":15},"Diagrams","diagrams",{"name":199,"slug":200,"type":15},"Documentation","documentation","2026-04-06T18:09:15.270247",{"slug":203,"name":203,"fn":204,"description":205,"org":206,"tags":207,"stars":137,"repoUrl":138,"updatedAt":213},"fetching-dbt-docs","search dbt documentation","Retrieves and searches dbt documentation pages in LLM-friendly markdown format. Use when fetching dbt documentation, looking up dbt features, or answering questions about dbt Cloud, dbt Core, or the dbt Semantic Layer.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[208,209,210],{"name":20,"slug":20,"type":15},{"name":199,"slug":200,"type":15},{"name":211,"slug":212,"type":15},"Reference","reference","2026-04-06T18:09:06.36975",{"slug":215,"name":215,"fn":216,"description":217,"org":218,"tags":219,"stars":137,"repoUrl":138,"updatedAt":228},"migrating-dbt-core-to-fusion","triage dbt-core to Fusion migration errors","Use when a user needs help triaging dbt-core to Fusion migration errors. Runs dbt-autofix first, then classifies remaining errors into actionable categories (auto-fixable, guided fixes, needs input, blocked).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[220,221,222,225],{"name":166,"slug":167,"type":15},{"name":20,"slug":20,"type":15},{"name":223,"slug":224,"type":15},"Migration","migration",{"name":226,"slug":227,"type":15},"Triage","triage","2026-04-06T18:09:01.250175",{"slug":230,"name":230,"fn":231,"description":232,"org":233,"tags":234,"stars":137,"repoUrl":138,"updatedAt":240},"migrating-dbt-project-across-platforms","migrate dbt projects across data platforms","Use when migrating a dbt project from one data platform or data warehouse to another (e.g., Snowflake to Databricks, Databricks to Snowflake) using dbt Fusion's real-time compilation to identify and fix SQL dialect differences.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[235,236,237,238,239],{"name":166,"slug":167,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":20,"type":15},{"name":223,"slug":224,"type":15},{"name":25,"slug":26,"type":15},"2026-04-06T18:09:02.513828",{"slug":242,"name":242,"fn":243,"description":244,"org":245,"tags":246,"stars":137,"repoUrl":138,"updatedAt":252},"running-dbt-commands","run dbt CLI commands","Formats and executes dbt CLI commands, selects the correct dbt executable, and structures command parameters. Use when running models, tests, builds, compiles, or show queries via dbt CLI. Use when unsure which dbt executable to use or how to format command parameters.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[247,250,251],{"name":248,"slug":249,"type":15},"CLI","cli",{"name":166,"slug":167,"type":15},{"name":20,"slug":20,"type":15},"2026-04-06T18:09:03.791122",{"slug":254,"name":254,"fn":255,"description":256,"org":257,"tags":258,"stars":137,"repoUrl":138,"updatedAt":264},"troubleshooting-dbt-job-errors","troubleshoot dbt job errors","Diagnoses dbt Cloud\u002Fplatform job failures by analyzing run logs, querying the Admin API, reviewing git history, and investigating data issues. Use when a dbt Cloud\u002Fplatform job fails and you need to diagnose the root cause, especially when error messages are unclear or when intermittent failures occur. Do not use for local dbt development errors.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[259,260,261],{"name":192,"slug":193,"type":15},{"name":20,"slug":20,"type":15},{"name":262,"slug":263,"type":15},"Debugging","debugging","2026-04-06T18:09:05.065669",{"slug":266,"name":266,"fn":267,"description":268,"org":269,"tags":270,"stars":137,"repoUrl":138,"updatedAt":275},"using-dbt-for-analytics-engineering","build dbt models and tests","Builds and modifies dbt models, writes SQL transformations using ref() and source(), creates tests, and validates results with dbt show. Use when doing any dbt work - building or modifying models, debugging errors, exploring unfamiliar data sources, writing tests, or evaluating impact of changes.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[271,272,273,274],{"name":147,"slug":148,"type":15},{"name":166,"slug":167,"type":15},{"name":20,"slug":20,"type":15},{"name":25,"slug":26,"type":15},"2026-04-06T18:09:11.455851",{"slug":277,"name":277,"fn":278,"description":279,"org":280,"tags":281,"stars":137,"repoUrl":138,"updatedAt":288},"using-dbt-state","configure and optimize dbt state","Use when a user is enabling, configuring, optimizing, or debugging dbt State (the server-backed reuse mechanism that clones or skips nodes instead of rebuilding them). Use when they conflate dbt State with the `state:modified` selector or `--state` deferral. Use when asked about models rebuilding unexpectedly, views with `select *` rebuilding, volatile SQL (`current_timestamp()`, `random()`) rebuilding or not, cross-developer cloning, lag_tolerance.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[282,283,284,285],{"name":166,"slug":167,"type":15},{"name":192,"slug":193,"type":15},{"name":20,"slug":20,"type":15},{"name":286,"slug":287,"type":15},"Performance","performance","2026-06-25T07:12:16.623154",16,{"items":291,"total":31},[292,300],{"slug":4,"name":4,"fn":5,"description":6,"org":293,"tags":294,"stars":27,"repoUrl":28,"updatedAt":29},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[295,296,297,298,299],{"name":13,"slug":14,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":20,"type":15},{"name":22,"slug":23,"type":15},{"name":25,"slug":26,"type":15},{"slug":301,"name":301,"fn":302,"description":303,"org":304,"tags":305,"stars":27,"repoUrl":28,"updatedAt":313},"connect-warehouse","connect data warehouses to Codex","Connect an AI coding agent to Snowflake, BigQuery, or Databricks so it can run SQL. Use when warehouse access is missing, authentication or connection selection is required, or before using a warehouse-data skill such as agents-schema-search.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[306,307,308,309,312],{"name":13,"slug":14,"type":15},{"name":17,"slug":18,"type":15},{"name":20,"slug":20,"type":15},{"name":310,"slug":311,"type":15},"Snowflake","snowflake",{"name":25,"slug":26,"type":15},"2026-07-24T05:37:00.235482"]