[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-databricks-databricks-agent-bricks":3,"mdc--omvrfv-key":33,"related-org-databricks-databricks-agent-bricks":2233,"related-repo-databricks-databricks-agent-bricks":2413},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":29,"sourceUrl":31,"mdContent":32},"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},"databricks","Databricks","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fdatabricks.png",[12,16,17,20],{"name":13,"slug":14,"type":15},"Knowledge Management","knowledge-management","tag",{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},"Agents","agents",{"name":21,"slug":22,"type":15},"Multi-Agent","multi-agent",204,"https:\u002F\u002Fgithub.com\u002Fdatabricks\u002Fdatabricks-agent-skills","2026-07-15T05:41:38.548954",null,60,[],{"repoUrl":24,"stars":23,"forks":27,"topics":30,"description":26},[],"https:\u002F\u002Fgithub.com\u002Fdatabricks\u002Fdatabricks-agent-skills\u002Ftree\u002FHEAD\u002Fplugins\u002Fdatabricks\u002Fcopilot\u002Fskills\u002Fdatabricks-agent-bricks","---\nname: databricks-agent-bricks\ndescription: \"Create Agent Bricks: Knowledge Assistants (KA) for document Q&A and Supervisor Agents for multi-agent orchestration (MAS).\"\ncompatibility: Requires databricks CLI (>= v1.0.0)\nmetadata:\n  version: \"0.1.0\"\nparent: databricks-core\n---\n\n# Agent Bricks\n\nAgent Bricks are pre-built AI tiles in Databricks that provide conversational interfaces. This skill covers **Knowledge Assistants** and **Supervisor Agents**.\n\n| Brick | Purpose | This Skill |\n|-------|---------|------------|\n| **Knowledge Assistant (KA)** | Document Q&A using RAG on PDFs\u002Ftext in Volumes | ✓ |\n| **Supervisor Agent** | Orchestrates multiple agents (KA, endpoints, UC functions, MCP) | ✓ |\n\n---\n\n## Knowledge Assistant\n\n```bash\n# Find volumes\ndatabricks volumes list CATALOG SCHEMA\ndatabricks experimental aitools tools query --warehouse WH \"LIST '\u002FVolumes\u002Fcatalog\u002Fschema\u002Fvolume\u002F'\"\n\n# Create KA\ndatabricks knowledge-assistants create-knowledge-assistant \"Name\" \"Description\"\n\n# Add knowledge source. With --json, pass ONLY the PARENT as a positional arg\n# and put display_name \u002F description \u002F source_type \u002F the source body (files|index|file_table)\n# inside the JSON. Mixing positional DISPLAY_NAME\u002FDESCRIPTION\u002FSOURCE_TYPE with --json errors.\ndatabricks knowledge-assistants create-knowledge-source \\\n  \"knowledge-assistants\u002F{ka_id}\" \\\n  --json '{\n    \"display_name\": \"Docs\",\n    \"description\": \"Documentation files\",\n    \"source_type\": \"files\",\n    \"files\": {\"path\": \"\u002FVolumes\u002Fcatalog\u002Fschema\u002Fvolume\u002F\"}\n  }'\n\n# Sync and check status\ndatabricks knowledge-assistants sync-knowledge-sources \"knowledge-assistants\u002F{ka_id}\"\ndatabricks knowledge-assistants get-knowledge-assistant \"knowledge-assistants\u002F{ka_id}\"\n\n# List\u002Fmanage\ndatabricks knowledge-assistants list-knowledge-assistants\ndatabricks knowledge-assistants delete-knowledge-assistant \"knowledge-assistants\u002F{ka_id}\"  # destructive & irreversible — confirm the id first\n```\n\n**Source types:** `files` (Volume path) or `index` (Vector Search: `index.index_name`, `index.text_col`, `index.doc_uri_col`)\n\n**Status:** `CREATING` (2-5 min) → `ONLINE` → `OFFLINE`\n\n---\n\n## Supervisor Agent\n\nNative CLI: `databricks supervisor-agents` (Beta, requires CLI ≥ v1.0.0). Resource paths look like `supervisor-agents\u002F{id}` — every command takes either that full path or a `PARENT` of that shape. `list-supervisor-agents` and `list-examples`\u002F`list-tools` return bare JSON arrays.\n\n```bash\n# Create the supervisor agent (display name positional, description\u002Finstructions as flags)\ndatabricks supervisor-agents create-supervisor-agent \"My Supervisor\" \\\n    --description \"Routes queries to specialized agents\" \\\n    --instructions \"Route data questions to analyst, document questions to docs_agent.\"\n# → returns {name: \"supervisor-agents\u002F\u003Cuuid>\", endpoint_name: \"mas-\u003Cshort>-endpoint\", ...}\n\n# List \u002F get \u002F find by name\ndatabricks supervisor-agents list-supervisor-agents\ndatabricks supervisor-agents get-supervisor-agent supervisor-agents\u002F\u003Cid>\ndatabricks supervisor-agents list-supervisor-agents | jq '.[] | select(.display_name == \"My Supervisor\")'\n\n# Update — UPDATE_MASK + new DISPLAY_NAME are positional; description\u002Finstructions optional flags\ndatabricks supervisor-agents update-supervisor-agent supervisor-agents\u002F\u003Cid> \\\n    \"display_name,description,instructions\" \"My Supervisor (v2)\" \\\n    --description \"...\" --instructions \"...\"\n\n# Delete (destructive & irreversible — confirm the id first)\ndatabricks supervisor-agents delete-supervisor-agent supervisor-agents\u002F\u003Cid>\n```\n\n### Tools (the agents the supervisor routes to)\n\nEach tool wires the supervisor to a downstream resource. `tool_type` lives in `--json` (the CLI rejects it as a positional when `--json` is used). Each type has a type-specific block (`genie_space`, `knowledge_assistant`, etc.) whose identifier field differs by type — see the table below.\n\n```bash\n# Attach a Genie space — find its space_id with `databricks genie list-spaces`\ndatabricks supervisor-agents create-tool supervisor-agents\u002F\u003Cid> analyst --json '{\n    \"tool_type\": \"genie_space\",\n    \"description\": \"SQL analytics on the analytics warehouse\",\n    \"genie_space\": {\"id\": \"\u003Cgenie_space_id>\"}\n}'\n\n# Attach a Knowledge Assistant — find ka_id with `databricks knowledge-assistants list-knowledge-assistants`\ndatabricks supervisor-agents create-tool supervisor-agents\u002F\u003Cid> docs_agent --json '{\n    \"tool_type\": \"knowledge_assistant\",\n    \"description\": \"Answers from product documentation\",\n    \"knowledge_assistant\": {\"knowledge_assistant_id\": \"\u003Cka_id>\"}\n}'\n\n# List \u002F get \u002F delete tools\ndatabricks supervisor-agents list-tools supervisor-agents\u002F\u003Cid>\ndatabricks supervisor-agents get-tool supervisor-agents\u002F\u003Cid>\u002Ftools\u002F\u003Ctool_id>\ndatabricks supervisor-agents delete-tool supervisor-agents\u002F\u003Cid>\u002Ftools\u002F\u003Ctool_id>\n```\n\n**Tool types** (`tool_type` value → type-specific block):\n\n| `tool_type` | Block | Use for |\n|---|---|---|\n| `genie_space` | `{\"id\": \"\u003Cspace_id>\"}` | Natural language → SQL via Genie |\n| `knowledge_assistant` | `{\"knowledge_assistant_id\": \"\u003Cka_id>\"}` | Document Q&A via a KA |\n| `uc_function` | `{\"name\": \"catalog.schema.func\"}` | UC SQL\u002FPython function |\n| `uc_connection` | `{\"name\": \"\u003Cconnection_name>\"}` | External MCP server via UC HTTP Connection |\n| `volume` | `{\"name\": \"\u003Cfull_volume_name>\"}` | UC Volume browsing |\n| `app` | `{\"name\": \"\u003Capp_name>\"}` | Databricks App |\n| Other types (`serving_endpoint`, `lakeview_dashboard`, `supervisor_agent`, `uc_table`, `vector_search_index`, `catalog`, `schema`, `web_search`) | Block name and field shape vary | Run `databricks supervisor-agents create-tool --help` and probe — these were not verified end-to-end here. |\n\n### Examples (training the supervisor)\n\nExamples must use `--json` — the positional `GUIDELINES` arg doesn't accept any encoding because guidelines is a `repeated string`.\n\n```bash\ndatabricks supervisor-agents create-example supervisor-agents\u002F\u003Cid> --json '{\n    \"question\": \"What were Q4 revenue numbers?\",\n    \"guidelines\": [\"Route to analyst Genie space\", \"Always group by region\"]\n}'\n\ndatabricks supervisor-agents list-examples supervisor-agents\u002F\u003Cid>\ndatabricks supervisor-agents get-example supervisor-agents\u002F\u003Cid>\u002Fexamples\u002F\u003Cex_id>\ndatabricks supervisor-agents delete-example supervisor-agents\u002F\u003Cid>\u002Fexamples\u002F\u003Cex_id>\n```\n\n**Endpoint readiness:** after `create-supervisor-agent`, the serving endpoint takes up to ~10 minutes to come online before it can answer queries. `get-supervisor-agent` returns the endpoint name immediately, but querying it is gated on the endpoint's own readiness — check via `databricks serving-endpoints get \u003Cendpoint_name>`.\n\n---\n\n## Reference\n\n| Topic | File |\n|-------|------|\n| KA source types, index, troubleshooting | [references\u002F1-knowledge-assistants.md](references\u002F1-knowledge-assistants.md) |\n| UC functions, MCP servers, examples | [references\u002F2-supervisor-agents.md](references\u002F2-supervisor-agents.md) |\n",{"data":34,"body":39},{"name":4,"description":6,"compatibility":35,"metadata":36,"parent":38},"Requires databricks CLI (>= v1.0.0)",{"version":37},"0.1.0","databricks-core",{"type":40,"children":41},"root",[42,51,72,146,150,157,621,670,701,704,709,761,1153,1160,1203,1575,1592,1858,1864,1891,2130,2163,2166,2172,2227],{"type":43,"tag":44,"props":45,"children":47},"element","h1",{"id":46},"agent-bricks",[48],{"type":49,"value":50},"text","Agent Bricks",{"type":43,"tag":52,"props":53,"children":54},"p",{},[55,57,63,65,70],{"type":49,"value":56},"Agent Bricks are pre-built AI tiles in Databricks that provide conversational interfaces. 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With --json, pass ONLY the PARENT as a positional arg\n# and put display_name \u002F description \u002F source_type \u002F the source body (files|index|file_table)\n# inside the JSON. Mixing positional DISPLAY_NAME\u002FDESCRIPTION\u002FSOURCE_TYPE with --json errors.\ndatabricks knowledge-assistants create-knowledge-source \\\n  \"knowledge-assistants\u002F{ka_id}\" \\\n  --json '{\n    \"display_name\": \"Docs\",\n    \"description\": \"Documentation files\",\n    \"source_type\": \"files\",\n    \"files\": {\"path\": \"\u002FVolumes\u002Fcatalog\u002Fschema\u002Fvolume\u002F\"}\n  }'\n\n# Sync and check status\ndatabricks knowledge-assistants sync-knowledge-sources \"knowledge-assistants\u002F{ka_id}\"\ndatabricks knowledge-assistants get-knowledge-assistant \"knowledge-assistants\u002F{ka_id}\"\n\n# List\u002Fmanage\ndatabricks knowledge-assistants list-knowledge-assistants\ndatabricks knowledge-assistants delete-knowledge-assistant \"knowledge-assistants\u002F{ka_id}\"  # destructive & irreversible — confirm the id 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Also covers document parsing and building custom RAG pipelines (parse → prep_search → index → query).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2248,2251,2252],{"name":2249,"slug":2250,"type":15},"Data Analysis","data-analysis",{"name":9,"slug":8,"type":15},{"name":2253,"slug":2254,"type":15},"LLM","llm","2026-07-31T05:53:33.562077",{"slug":2257,"name":2257,"fn":2258,"description":2259,"org":2260,"tags":2261,"stars":23,"repoUrl":24,"updatedAt":2272},"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},[2262,2265,2266,2269],{"name":2263,"slug":2264,"type":15},"CLI","cli",{"name":9,"slug":8,"type":15},{"name":2267,"slug":2268,"type":15},"Docker","docker",{"name":2270,"slug":2271,"type":15},"Engineering","engineering","2026-07-12T08:04:55.843982",{"slug":2274,"name":2274,"fn":2275,"description":2276,"org":2277,"tags":2278,"stars":23,"repoUrl":24,"updatedAt":2289},"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},[2279,2282,2285,2288],{"name":2280,"slug":2281,"type":15},"Analytics","analytics",{"name":2283,"slug":2284,"type":15},"Dashboards","dashboards",{"name":2286,"slug":2287,"type":15},"Data Visualization","data-visualization",{"name":9,"slug":8,"type":15},"2026-07-12T08:04:25.314591",{"slug":2291,"name":2291,"fn":2292,"description":2293,"org":2294,"tags":2295,"stars":23,"repoUrl":24,"updatedAt":2309},"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},[2296,2297,2300,2303,2306],{"name":9,"slug":8,"type":15},{"name":2298,"slug":2299,"type":15},"Design","design",{"name":2301,"slug":2302,"type":15},"Frontend","frontend",{"name":2304,"slug":2305,"type":15},"React","react",{"name":2307,"slug":2308,"type":15},"UI Components","ui-components","2026-07-12T08:04:02.02398",{"slug":2311,"name":2311,"fn":2312,"description":2313,"org":2314,"tags":2315,"stars":23,"repoUrl":24,"updatedAt":2320},"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},[2316,2317,2318,2319],{"name":2280,"slug":2281,"type":15},{"name":2283,"slug":2284,"type":15},{"name":2249,"slug":2250,"type":15},{"name":9,"slug":8,"type":15},"2026-07-12T08:03:59.061458",{"slug":2322,"name":2322,"fn":2323,"description":2324,"org":2325,"tags":2326,"stars":23,"repoUrl":24,"updatedAt":2343},"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},[2327,2328,2331,2334,2337,2340],{"name":9,"slug":8,"type":15},{"name":2329,"slug":2330,"type":15},"FastAPI","fastapi",{"name":2332,"slug":2333,"type":15},"Flask","flask",{"name":2335,"slug":2336,"type":15},"Gradio","gradio",{"name":2338,"slug":2339,"type":15},"Python","python",{"name":2341,"slug":2342,"type":15},"Streamlit","streamlit","2026-07-12T08:04:10.970845",{"slug":38,"name":38,"fn":2345,"description":2346,"org":2347,"tags":2348,"stars":23,"repoUrl":24,"updatedAt":2354},"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},[2349,2352,2353],{"name":2350,"slug":2351,"type":15},"Authentication","authentication",{"name":2263,"slug":2264,"type":15},{"name":9,"slug":8,"type":15},"2026-07-18T05:11:05.45506",{"slug":2356,"name":2356,"fn":2357,"description":2358,"org":2359,"tags":2360,"stars":23,"repoUrl":24,"updatedAt":2371},"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},[2361,2364,2367,2368],{"name":2362,"slug":2363,"type":15},"Automation","automation",{"name":2365,"slug":2366,"type":15},"Configuration","configuration",{"name":9,"slug":8,"type":15},{"name":2369,"slug":2370,"type":15},"Deployment","deployment","2026-07-15T05:41:35.930355",{"slug":2373,"name":2373,"fn":2374,"description":2375,"org":2376,"tags":2377,"stars":23,"repoUrl":24,"updatedAt":2386},"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},[2378,2379,2382,2383],{"name":2249,"slug":2250,"type":15},{"name":2380,"slug":2381,"type":15},"Data Engineering","data-engineering",{"name":9,"slug":8,"type":15},{"name":2384,"slug":2385,"type":15},"SQL","sql","2026-07-31T05:53:32.561877",{"slug":2388,"name":2388,"fn":2389,"description":2390,"org":2391,"tags":2392,"stars":23,"repoUrl":24,"updatedAt":2399},"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},[2393,2394,2397,2398],{"name":2249,"slug":2250,"type":15},{"name":2395,"slug":2396,"type":15},"Database","database",{"name":9,"slug":8,"type":15},{"name":2384,"slug":2385,"type":15},"2026-07-12T08:04:08.678282",{"slug":2401,"name":2401,"fn":2402,"description":2403,"org":2404,"tags":2405,"stars":23,"repoUrl":24,"updatedAt":2411},"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},[2406,2407,2410],{"name":9,"slug":8,"type":15},{"name":2408,"slug":2409,"type":15},"Documentation","documentation",{"name":2171,"slug":2168,"type":15},"2026-07-15T05:41:34.697746",31,{"items":2414,"total":2412},[2415,2422,2428,2435,2442,2450,2457],{"slug":4,"name":4,"fn":5,"description":6,"org":2416,"tags":2417,"stars":23,"repoUrl":24,"updatedAt":25},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2418,2419,2420,2421],{"name":18,"slug":19,"type":15},{"name":9,"slug":8,"type":15},{"name":13,"slug":14,"type":15},{"name":21,"slug":22,"type":15},{"slug":2243,"name":2243,"fn":2244,"description":2245,"org":2423,"tags":2424,"stars":23,"repoUrl":24,"updatedAt":2255},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2425,2426,2427],{"name":2249,"slug":2250,"type":15},{"name":9,"slug":8,"type":15},{"name":2253,"slug":2254,"type":15},{"slug":2257,"name":2257,"fn":2258,"description":2259,"org":2429,"tags":2430,"stars":23,"repoUrl":24,"updatedAt":2272},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2431,2432,2433,2434],{"name":2263,"slug":2264,"type":15},{"name":9,"slug":8,"type":15},{"name":2267,"slug":2268,"type":15},{"name":2270,"slug":2271,"type":15},{"slug":2274,"name":2274,"fn":2275,"description":2276,"org":2436,"tags":2437,"stars":23,"repoUrl":24,"updatedAt":2289},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2438,2439,2440,2441],{"name":2280,"slug":2281,"type":15},{"name":2283,"slug":2284,"type":15},{"name":2286,"slug":2287,"type":15},{"name":9,"slug":8,"type":15},{"slug":2291,"name":2291,"fn":2292,"description":2293,"org":2443,"tags":2444,"stars":23,"repoUrl":24,"updatedAt":2309},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2445,2446,2447,2448,2449],{"name":9,"slug":8,"type":15},{"name":2298,"slug":2299,"type":15},{"name":2301,"slug":2302,"type":15},{"name":2304,"slug":2305,"type":15},{"name":2307,"slug":2308,"type":15},{"slug":2311,"name":2311,"fn":2312,"description":2313,"org":2451,"tags":2452,"stars":23,"repoUrl":24,"updatedAt":2320},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2453,2454,2455,2456],{"name":2280,"slug":2281,"type":15},{"name":2283,"slug":2284,"type":15},{"name":2249,"slug":2250,"type":15},{"name":9,"slug":8,"type":15},{"slug":2322,"name":2322,"fn":2323,"description":2324,"org":2458,"tags":2459,"stars":23,"repoUrl":24,"updatedAt":2343},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[2460,2461,2462,2463,2464,2465],{"name":9,"slug":8,"type":15},{"name":2329,"slug":2330,"type":15},{"name":2332,"slug":2333,"type":15},{"name":2335,"slug":2336,"type":15},{"name":2338,"slug":2339,"type":15},{"name":2341,"slug":2342,"type":15}]