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support",[],[703,706,707,708],{"slug":704,"name":705},"https","HTTPS",{"slug":5,"name":6},{"slug":342,"name":343},{"slug":53,"name":54},"2026-07-07T06:53:55.16351",{"name":711,"fullName":712,"repoUrl":713,"skillCount":158,"stars":157,"forks":289,"description":714,"topics":715,"topTags":716,"topTagCount":289,"lastUpdatedAt":720},"amplifier-app-openclaw","microsoft\u002Famplifier-app-openclaw","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Famplifier-app-openclaw","OpenClaw skill for the Amplifier project",[],[717,718,719],{"slug":44,"name":45},{"slug":300,"name":301},{"slug":369,"name":370},"2026-04-06T18:38:33.007318",{"name":722,"fullName":723,"repoUrl":724,"skillCount":158,"stars":288,"forks":312,"description":725,"topics":726,"topTags":727,"topTagCount":289,"lastUpdatedAt":733},"amplifier-bundle-digital-twin-universe","microsoft\u002Famplifier-bundle-digital-twin-universe","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Famplifier-bundle-digital-twin-universe","Digital Twin Universe bundle for the Amplifier project",[],[728,729,732],{"slug":41,"name":42},{"slug":730,"name":731},"qa","QA",{"slug":478,"name":479},"2026-07-28T05:36:52.215479",{"name":735,"fullName":736,"repoUrl":737,"skillCount":158,"stars":158,"forks":312,"description":738,"topics":739,"topTags":740,"topTagCount":312,"lastUpdatedAt":747},"amplifier-bundle-gitea","microsoft\u002Famplifier-bundle-gitea","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Famplifier-bundle-gitea","Gitea bundle for the Amplifier project",[],[741,744],{"slug":742,"name":743},"docker","Docker",{"slug":745,"name":746},"git","Git","2026-04-06T18:37:56.309463",{"name":749,"fullName":750,"repoUrl":751,"skillCount":158,"stars":288,"forks":752,"description":753,"topics":754,"topTags":755,"topTagCount":289,"lastUpdatedAt":759},"amplifier-bundle-recipes","microsoft\u002Famplifier-bundle-recipes","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Famplifier-bundle-recipes",12,"Recipes bundle for the Amplifier project",[],[756,757,758],{"slug":300,"name":301},{"slug":317,"name":318},{"slug":636,"name":637},"2026-04-06T18:38:23.129253",{"name":761,"fullName":762,"repoUrl":763,"skillCount":158,"stars":312,"forks":328,"description":764,"topics":765,"topTags":766,"topTagCount":290,"lastUpdatedAt":771},"amplifier-bundle-routing-matrix","microsoft\u002Famplifier-bundle-routing-matrix","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Famplifier-bundle-routing-matrix","Routing Matrix bundle for the Amplifier project",[],[767,768,769,770],{"slug":44,"name":45},{"slug":101,"name":102},{"slug":452,"name":453},{"slug":5,"name":6},"2026-07-24T05:42:25.781133",{"name":773,"fullName":774,"repoUrl":775,"skillCount":158,"stars":776,"forks":777,"description":773,"topics":778,"topTags":782,"topTagCount":290,"lastUpdatedAt":788},"ApplicationInsights-dotnet","microsoft\u002FApplicationInsights-dotnet","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FApplicationInsights-dotnet",607,298,[531,29,779,780,600,536,67,781],"distributed-tracing","logging","telemetry",[783,785,786,787],{"slug":784,"name":33},"dotnet",{"slug":531,"name":532},{"slug":29,"name":30},{"slug":536,"name":537},"2026-04-06T18:37:55.007524",{"name":790,"fullName":791,"repoUrl":792,"skillCount":158,"stars":158,"forks":267,"description":793,"topics":794,"topTags":795,"topTagCount":289,"lastUpdatedAt":55},"azcapman","microsoft\u002Fazcapman","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazcapman","This repository contains Azure quota and capacity management references for SaaS ISVs that operate workloads in subscriptions owned or controlled by the ISV (Enterprise Agreement or Microsoft Customer Agreement), not in customer-owned subscriptions.",[],[796,797,798],{"slug":93,"name":94},{"slug":29,"name":30},{"slug":799,"name":800},"capacity-planning","Capacity Planning",{"name":802,"fullName":803,"repoUrl":804,"skillCount":158,"stars":805,"forks":182,"description":806,"topics":807,"topTags":808,"topTagCount":290,"lastUpdatedAt":815},"azure-devops-skills","microsoft\u002Fazure-devops-skills","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-devops-skills",31,"Sample skills and prompt patterns demonstrating how to use the Azure DevOps MCP Server with GitHub Copilot and agent-based workflows",[],[809,810,813,814],{"slug":348,"name":349},{"slug":811,"name":812},"ci-cd","CI\u002FCD",{"slug":304,"name":305},{"slug":5,"name":6},"2026-07-18T05:16:55.20176",{"name":817,"fullName":818,"repoUrl":819,"skillCount":158,"stars":820,"forks":821,"description":822,"topics":823,"topTags":832,"topTagCount":289,"lastUpdatedAt":838},"Build-CLI","microsoft\u002FBuild-CLI","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FBuild-CLI",289,84,"Experience Microsoft Build, directly from your terminal, with GitHub Copilot CLI and the Microsoft Build CLI.",[824,146,647,825,826,511,66,827,828,829,830,831],"agent-tools","copilot-extension","developer-events","microsoft-build","microsoft-ignite","nodejs","session-catalog","typescript",[833,834,837],{"slug":146,"name":147},{"slug":835,"name":836},"meetings","Meetings",{"slug":5,"name":6},"2026-07-07T06:53:51.252768",{"name":840,"fullName":841,"repoUrl":842,"skillCount":158,"stars":248,"forks":312,"description":843,"topics":844,"topTags":853,"topTagCount":205,"lastUpdatedAt":862},"copilot-brag-sheet","microsoft\u002Fcopilot-brag-sheet","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fcopilot-brag-sheet","Auto-track every Copilot CLI coding session into a structured work impact log. Zero deps, local-first, cross-platform.",[845,846,847,235,647,825,848,509,511,849,850,66,851,219,852],"agent-skill","brag-sheet","claude-code","developer-productivity","impact-log","local-first","performance-review","work-tracker",[854,855,856,858,859],{"slug":235,"name":236},{"slug":5,"name":6},{"slug":851,"name":857},"Performance Review",{"slug":219,"name":220},{"slug":860,"name":861},"writing","Writing","2026-07-07T06:54:32.938633",{"name":864,"fullName":865,"repoUrl":866,"skillCount":158,"stars":867,"forks":868,"description":869,"topics":870,"topTags":872,"topTagCount":289,"lastUpdatedAt":879},"create-playwright","microsoft\u002Fcreate-playwright","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fcreate-playwright",61,50,"\"npm init playwright\" implementation",[871],"playwright",[873,876,878],{"slug":874,"name":875},"browser-automation","Browser Automation",{"slug":871,"name":877},"Playwright",{"slug":478,"name":479},"2026-04-06T18:32:43.891046",{"name":881,"fullName":882,"repoUrl":883,"skillCount":158,"stars":884,"forks":885,"description":886,"topics":887,"topTags":896,"topTagCount":290,"lastUpdatedAt":906},"DirectXTK12","microsoft\u002FDirectXTK12","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FDirectXTK12",1738,463,"The DirectX Tool Kit (aka DirectXTK12) is a collection of helper classes for writing DirectX 12 code in C++",[888,582,889,890,891,892,5,893,894,895],"cpp-library","directx","directx-12","directxtk","graphics","shaders","uwp","xbox",[897,900,903,905],{"slug":898,"name":899},"c","C#",{"slug":901,"name":902},"game-development","Game Development",{"slug":892,"name":904},"Graphics",{"slug":5,"name":6},"2026-07-03T16:32:07.674268",{"name":908,"fullName":909,"repoUrl":910,"skillCount":158,"stars":911,"forks":288,"description":912,"topics":913,"topTags":921,"topTagCount":290,"lastUpdatedAt":932},"ResearchStudio","microsoft\u002FResearchStudio","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FResearchStudio",122,"ResearchStudio: Our AI co-author, from research problem to final publication.",[914,915,916,917,918,919,920],"blog-generation","idea-generation","poster-generation","presentation","researchstudio-idea","researchstudio-reel","video-generation",[922,925,926,929],{"slug":923,"name":924},"ideation","Ideation",{"slug":5,"name":6},{"slug":927,"name":928},"research","Research",{"slug":930,"name":931},"strategy","Strategy","2026-07-31T05:55:12.079424",{"name":934,"fullName":935,"repoUrl":936,"skillCount":158,"stars":937,"forks":938,"description":939,"topics":940,"topTags":954,"topTagCount":205,"lastUpdatedAt":965},"rushstack","microsoft\u002Frushstack","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frushstack",6484,700,"Monorepo for tools developed by the Rush Stack community",[941,942,943,944,945,946,947,948,949,829,950,951,934,952,953,831],"api","api-extractor","build","bulk-suppressions","eslint","hacktoberfest","heft","lockfile-explorer","monorepo","orchestrator","rush","toolchain","tsdoc",[955,956,959,960,963],{"slug":50,"name":51},{"slug":957,"name":958},"local-development","Local Development",{"slug":5,"name":6},{"slug":961,"name":962},"project-management","Project Management",{"slug":951,"name":964},"Rush","2026-04-06T18:34:44.965032",{"name":967,"fullName":968,"repoUrl":969,"skillCount":158,"stars":970,"forks":971,"description":972,"topics":973,"topTags":974,"topTagCount":205,"lastUpdatedAt":980},"sarif-sdk","microsoft\u002Fsarif-sdk","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fsarif-sdk",224,105,".NET code and supporting files for working with the 'Static Analysis Results Interchange Format' (SARIF, see https:\u002F\u002Fgithub.com\u002Foasis-tcs\u002Fsarif-spec)",[],[975,976,977,978,979],{"slug":811,"name":812},{"slug":257,"name":258},{"slug":212,"name":213},{"slug":5,"name":6},{"slug":53,"name":54},"2026-07-03T16:31:31.41083",{"name":982,"fullName":983,"repoUrl":984,"skillCount":158,"stars":985,"forks":607,"description":986,"topics":987,"topTags":988,"topTagCount":290,"lastUpdatedAt":995},"SharePoint-Embedded-Samples","microsoft\u002FSharePoint-Embedded-Samples","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FSharePoint-Embedded-Samples",103,"Official samples and developer tools for building on SharePoint Embedded, the document storage API on Microsoft 365. Includes React, TypeScript, and ASP.NET Core boilerplates, an MCP server for AI coding agents, Copilot and Power Platform assets, Postman and Bruno collections, and admin scripts.",[],[989,990,991,992],{"slug":690,"name":691},{"slug":5,"name":6},{"slug":238,"name":239},{"slug":993,"name":994},"sharepoint","SharePoint","2026-07-07T06:54:26.510402",{"name":997,"fullName":998,"repoUrl":999,"skillCount":158,"stars":1000,"forks":261,"description":1001,"topics":1002,"topTags":1009,"topTagCount":289,"lastUpdatedAt":1013},"shell-use","microsoft\u002Fshell-use","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fshell-use",194,"💻 Make the terminal \u002F shell accessible for AI agents. Automate tasks with ease.",[506,428,1003,146,365,1004,452,1005,1006,997,1007,478,1008],"bash","fish","powershell","pwsh","terminal","tui",[1010,1011,1012],{"slug":146,"name":147},{"slug":50,"name":51},{"slug":5,"name":6},"2026-07-07T06:54:23.890194",{"name":1015,"fullName":1016,"repoUrl":1017,"skillCount":158,"stars":157,"forks":312,"description":1018,"topics":1019,"topTags":1020,"topTagCount":289,"lastUpdatedAt":1026},"teams-platform-skills","microsoft\u002Fteams-platform-skills","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fteams-platform-skills","Skills and tools related to Teams extensibility platform",[],[1021,1022,1025],{"slug":257,"name":258},{"slug":1023,"name":1024},"microsoft-teams","Microsoft Teams",{"slug":38,"name":39},"2026-04-06T18:37:58.898098",{"name":1028,"fullName":1029,"repoUrl":1030,"skillCount":158,"stars":1031,"forks":9,"description":1032,"topics":1033,"topTags":1034,"topTagCount":290,"lastUpdatedAt":1041},"teams-sdk","microsoft\u002Fteams-sdk","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fteams-sdk",716,"SDK focused on building AI based applications and extensions for Microsoft Teams and other Bot Framework channels",[],[1035,1036,1039,1040],{"slug":345,"name":346},{"slug":1037,"name":1038},"communications","Communications",{"slug":238,"name":239},{"slug":1023,"name":1024},"2026-05-13T06:13:10.260133",{"name":1043,"fullName":1044,"repoUrl":1045,"skillCount":158,"stars":1046,"forks":805,"description":1047,"topics":1048,"topTags":1049,"topTagCount":290,"lastUpdatedAt":1054},"vscode-chat-customizations-evaluation","microsoft\u002Fvscode-chat-customizations-evaluation","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fvscode-chat-customizations-evaluation",127,"A repository to evaluate the chat customizations",[],[1050,1051,1052,1053],{"slug":257,"name":258},{"slug":304,"name":305},{"slug":406,"name":407},{"slug":5,"name":6},"2026-07-07T06:54:36.829542",{"name":1056,"fullName":1057,"repoUrl":1058,"skillCount":158,"stars":1059,"forks":821,"description":1060,"topics":1061,"topTags":1066,"topTagCount":205,"lastUpdatedAt":1074},"vscode-cosmosdb","microsoft\u002Fvscode-cosmosdb","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fvscode-cosmosdb",198,"Azure Cosmos DB extension for VS Code",[1062,1063,5,1064,1065],"azure-cosmos-db","cosmos-db","nosql","vscode",[1067,1068,1070,1071,1073],{"slug":29,"name":30},{"slug":1063,"name":1069},"Cosmos DB",{"slug":76,"name":77},{"slug":1064,"name":1072},"NoSQL",{"slug":539,"name":540},"2026-04-06T18:38:20.527233",{"name":1076,"fullName":1077,"repoUrl":1078,"skillCount":158,"stars":1079,"forks":1080,"description":1081,"topics":1082,"topTags":1085,"topTagCount":205,"lastUpdatedAt":1095},"vscode-java-dependency","microsoft\u002Fvscode-java-dependency","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fvscode-java-dependency",197,102,"Manage Java projects in Visual Studio Code.",[79,1083,961,1084],"language-support","vscode-extension",[1086,1087,1088,1091,1092],{"slug":257,"name":258},{"slug":304,"name":305},{"slug":1089,"name":1090},"gradle","Gradle",{"slug":79,"name":80},{"slug":1093,"name":1094},"maven","Maven","2026-04-06T18:35:09.918427",{"items":1097,"total":23},[1098,1109,1126,1140,1154,1168,1182,1193,1209,1222,1234,1249,1260,1270,1284,1296,1310,1322,1334],{"slug":1099,"name":1099,"fn":1100,"description":1101,"org":1102,"tags":1103,"stars":135,"repoUrl":134,"updatedAt":1108},"check-updates","check for Fabric skill marketplace updates","Check an installed skills-for-fabric plugin bundle or git clone for updates, show the matching changelog, and provide host-appropriate update guidance. Use when the user wants to: (1) check for skill updates, (2) see what changed, (3) verify the installed version. Triggers: \"check for updates\", \"am I up to date\", \"what version\", \"update skills\", \"show changelog\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1104,1106,1107],{"name":6,"slug":5,"type":1105},"tag",{"name":48,"slug":47,"type":1105},{"name":343,"slug":342,"type":1105},"2026-07-24T05:41:25.892114",{"slug":1110,"name":1110,"fn":1111,"description":1112,"org":1113,"tags":1114,"stars":135,"repoUrl":134,"updatedAt":1125},"databricks-migration","migrate Databricks notebooks to Microsoft Fabric","Port Databricks notebooks and jobs to Microsoft Fabric. Provides an exhaustive dbutils to notebookutils substitution table: fs operations (runtime mounts or OneLake Shortcuts), secret scope to Key Vault URL conversion, notebook run and exit, widget replacement with parameter-tagged cells, and library install replacement with Fabric Environments. Covers Unity Catalog three-level namespace reduction to Lakehouse two-level schemas, DBFS path conversion to OneLake, Databricks Jobs to Spark Job Definitions, MLflow tracking URI removal, and Photon to Native Execution Engine substitution. Use when the user wants to: (1) replace dbutils with notebookutils, (2) collapse Unity Catalog namespaces to Lakehouse schemas, (3) convert Databricks Jobs or Delta Live Tables. Triggers: \"migrate from databricks\", \"databricks to fabric\", \"dbutils to notebookutils\", \"dbutils fabric\", \"unity catalog migration\", \"dbfs to onelake\", \"databricks notebook migration\", \"delta live tables fabric\", \"photon native execution\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1115,1116,1119,1120,1121,1122],{"name":144,"slug":143,"type":1105},{"name":1117,"slug":1118,"type":1105},"Databricks","databricks",{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":39,"slug":38,"type":1105},{"name":1123,"slug":1124,"type":1105},"Notebooks","notebooks","2026-07-24T05:41:22.914341",{"slug":1127,"name":1127,"fn":1128,"description":1129,"org":1130,"tags":1131,"stars":135,"repoUrl":134,"updatedAt":1139},"dataflows-authoring-cli","manage Microsoft Fabric Dataflows via CLI","Create, update, delete, and refresh Fabric Dataflows Gen2 with write-side CLI via Fabric APIs. Build mashup.pq and queryMetadata.json, preview candidate M with executeQuery\u002FcustomMashupDocument, bind connections, and configure output destinations. For saved query execution or refresh-status reads, use `dataflows-consumption-cli`. If a request explicitly insists on the Dataflows consumption or read-only path for a mutation, do not route here; let consumption refuse before any separately confirmed authoring handoff. Triggers: \"create dataflow\", \"update dataflow\", \"delete dataflow\", \"trigger dataflow refresh\", \"preview Power Query M\", \"preview before save\", \"customMashupDocument\", \"create Fabric data source connection\", \"create SQL Server source REST\", \"POST \u002Fv1\u002Fconnections\", \"supportedConnectionTypes\", \"passwordReference\", \"bind connection\", \"dataflow output destination\", \"dataflow write to lakehouse\", \"dataflow write to warehouse\", \"dataflow write to ADX\", \"DataDestinations annotation\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1132,1133,1134,1135,1136],{"name":147,"slug":146,"type":1105},{"name":144,"slug":143,"type":1105},{"name":553,"slug":552,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1137,"slug":1138,"type":1105},"REST API","rest-api","2026-07-31T05:54:59.059517",{"slug":1141,"name":1141,"fn":1142,"description":1143,"org":1144,"tags":1145,"stars":135,"repoUrl":134,"updatedAt":1153},"e2e-medallion-architecture","implement Medallion Architecture in Microsoft Fabric","Plan and implement end-to-end Microsoft Fabric data platforms and Medallion Architecture (Bronze\u002FSilver\u002FGold) lakehouse patterns using PySpark, Delta Lake, Lakehouse\u002FWarehouse items, Fabric Pipelines, and semantic-model handoff. Use when the user wants to: (1) design a Bronze\u002FSilver\u002FGold data lakehouse, (2) plan an ingestion-to-semantic-model Fabric data platform, (3) set up multi-layer workspaces with lakehouses for each tier, (4) build ingestion-to-analytics pipelines with data quality enforcement, (5) orchestrate Bronze-to-Silver-to-Gold flows via notebooks. For natural-language business questions over existing Power BI report data, use `fabriciq`. Triggers: \"medallion architecture\", \"bronze silver gold\", \"lakehouse layers\", \"e2e data pipeline\", \"end-to-end lakehouse\", \"data lakehouse pattern\", \"multi-layer lakehouse\", \"build medallion\", \"setup medallion\", \"end-to-end Fabric data platform\", \"bronze silver gold platform\", \"ingestion semantic model platform\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1146,1147,1148,1149,1150],{"name":102,"slug":101,"type":1105},{"name":144,"slug":143,"type":1105},{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1151,"slug":1152,"type":1105},"PySpark","pyspark","2026-07-31T05:54:57.038396",{"slug":1155,"name":1155,"fn":1156,"description":1157,"org":1158,"tags":1159,"stars":135,"repoUrl":134,"updatedAt":1167},"eventhouse-authoring-cli","manage Fabric Eventhouse and KQL databases","Execute KQL management commands (table management, ingestion, policies, functions, materialized views) against Fabric Eventhouse and KQL Databases via CLI. Use when the user wants to:\n  1. Create or alter KQL tables, columns, or functions\n  2. Ingest data into an Eventhouse (inline, from storage, streaming)\n  3. Configure retention, caching, or partitioning policies\n  4. Create or manage materialized views and update policies\n  5. Manage data mappings for ingestion pipelines\n  6. Deploy KQL schema via scripts\nTriggers: \"create kql table\", \"kql ingestion\", \"ingest into eventhouse\", \"kql function\", \"materialized view\", \"kql retention policy\", \"eventhouse schema\", \"kql authoring\", \"create eventhouse table\", \"kql mapping\"\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1160,1161,1164,1165,1166],{"name":77,"slug":76,"type":1105},{"name":1162,"slug":1163,"type":1105},"KQL","kql",{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":343,"slug":342,"type":1105},"2026-04-06T18:36:51.340409",{"slug":1169,"name":1169,"fn":1170,"description":1171,"org":1172,"tags":1173,"stars":135,"repoUrl":134,"updatedAt":1181},"eventhouse-consumption-cli","query Fabric Eventhouse with KQL","Run KQL queries against Fabric Eventhouse for real-time intelligence and time-series analytics using `az rest` against the Kusto REST API. Covers KQL operators (where, summarize, join, render), Eventhouse schema discovery (.show tables), time-series patterns with bin(), and ingestion monitoring. Use when the user wants to:\n  1. Run read-only KQL queries against an Eventhouse or KQL Database\n  2. Discover Eventhouse table schema and metadata\n  3. Analyse real-time or time-series data with KQL operators\n  4. Monitor ingestion health and active KQL queries\n  5. Export KQL results to JSON\nTriggers: \"kql query\", \"kusto query\", \"eventhouse query\", \"kql database\", \"real-time intelligence\", \"time-series kql\", \"query eventhouse\", \"explore eventhouse\", \"show tables kql\"\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1174,1175,1176,1177,1178],{"name":150,"slug":149,"type":1105},{"name":1162,"slug":1163,"type":1105},{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1179,"slug":1180,"type":1105},"Real-Time Intelligence","real-time-intelligence","2026-04-06T18:36:45.018807",{"slug":1183,"name":1183,"fn":1184,"description":1185,"org":1186,"tags":1187,"stars":135,"repoUrl":134,"updatedAt":1192},"eventstream-consumption-cli","monitor Fabric Eventstream ingestion pipelines","List, inspect, and monitor Fabric Eventstream real-time ingestion pipelines via the Items REST API. Discover Eventstreams across workspaces, decode base64 graph topologies tracing event flow from source through operators to destination nodes. Validate connection IDs, wiring, retention policies (1-90 days), and throughput levels. Retrieve Custom Endpoint Kafka credentials via Topology API. **Invoke this skill** to: (1) list Eventstreams, (2) inspect Eventstream topology showing sources and destinations, (3) validate Eventstream configurations, (4) check Eventstream retention policy and throughput level, (5) get connection strings. Triggers: \"list eventstreams\", \"inspect eventstream\", \"describe eventstream topology\", \"eventstream operator nodes\", \"eventstream sources and destinations\", \"eventstream health\", \"eventstream status\", \"eventstream configuration\", \"eventstream retention\", \"eventstream throughput level\", \"eventstream connection string\", \"custom endpoint credentials\", \"check eventstream\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1188,1189,1190,1191],{"name":147,"slug":146,"type":1105},{"name":144,"slug":143,"type":1105},{"name":48,"slug":47,"type":1105},{"name":601,"slug":600,"type":1105},"2026-07-31T05:55:03.045486",{"slug":1194,"name":1194,"fn":1195,"description":1196,"org":1197,"tags":1198,"stars":135,"repoUrl":134,"updatedAt":1208},"fabriciq","query Power BI reports with FabricIQ","Answer natural-language business questions over existing Power BI reports and dashboards through the FabricIQ MCP endpoint. Orchestrates artifact discovery, schema inspection, entity resolution, DAX generation, and query execution to return plain-language answers. Use when the user asks what, which, compare, rank, explain, or summarize questions about Power BI report or dashboard content. Triggers: \"ask power bi\", \"PBI question\", \"discover my Power BI report\", \"report data\", \"dashboard data\", \"what are the top\", \"show me the power bi data\", \"which products sold\", \"compare sales in report\", \"which customers churned\", \"ask the Power BI report\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1199,1200,1203,1204,1205],{"name":150,"slug":149,"type":1105},{"name":1201,"slug":1202,"type":1105},"Dashboards","dashboards",{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1206,"slug":1207,"type":1105},"Power BI","power-bi","2026-07-31T05:55:01.050708",{"slug":1210,"name":1210,"fn":1211,"description":1212,"org":1213,"tags":1214,"stars":135,"repoUrl":134,"updatedAt":1221},"fabriciq-ontology-consumption-cli","explore and summarize Fabric IQ ontologies","Explore Fabric IQ Ontology (preview) items (read-only) from the CLI to ground an agent before it queries data. Explore, describe, and summarize what an ontology exposes — its entity types, keys, relationships, and the bindings that map each concept onto a lakehouse or Eventhouse source — then route the underlying data query to the matching per-datasource consumption skill (eventhouse-consumption-cli, spark-consumption-cli, sqldw-consumption-cli). Read-only discovery via Get Item Definition; never writes to or alters an ontology. Use to explore or summarize an ontology, describe its schema and data lineage, build agent grounding context, or run an ontology-backed query over the source records. Triggers: \"query fabric ontology\", \"explore fabric ontology\", \"list ontology entities\", \"enumerate ontology entity types\", \"describe ontology\", \"ontology grounding context\", \"ground query with ontology\", \"query ontology entity data\", \"fabric iq ontology consumption\", \"ontology-backed query\", \"ontology entity bindings\"\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1215,1216,1217,1218],{"name":147,"slug":146,"type":1105},{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1219,"slug":1220,"type":1105},"Ontology","ontology","2026-07-07T06:52:56.792055",{"slug":1223,"name":1223,"fn":1224,"description":1225,"org":1226,"tags":1227,"stars":135,"repoUrl":134,"updatedAt":1233},"mlv-operations-cli","manage Microsoft Fabric lake view refresh schedules","Manage refresh schedules and job execution for an EXISTING Microsoft Fabric Materialized Lake View (MLV) via REST APIs: create, update, and delete refresh schedules (interval-based: hourly, daily, weekly), trigger on-demand refreshes, monitor job status, and cancel running jobs. Uses human-in-the-loop confirmations for safety. This skill does NOT author or create the MLV definition: writing the CREATE MATERIALIZED LAKE VIEW \u002F CREATE OR REPLACE SQL is `spark-authoring-cli`, not this skill. Note: MLV discovery (list MLVs, lineage, data quality) requires UI as REST APIs are not yet available. Triggers: \"schedule MLV refresh\", \"manage MLV refresh\", \"MLV refresh schedule\", \"schedule materialized lake view refresh\", \"automate MLV refresh\", \"trigger MLV refresh\", \"monitor MLV refresh\", \"MLV job status\", \"cancel MLV refresh\", \"refresh schedule\", \"MLV automation\", \"refresh my materialized views\"\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1228,1229,1230,1231,1232],{"name":144,"slug":143,"type":1105},{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":343,"slug":342,"type":1105},{"name":1137,"slug":1138,"type":1105},"2026-07-18T05:14:48.156161",{"slug":1235,"name":1235,"fn":1236,"description":1237,"org":1238,"tags":1239,"stars":135,"repoUrl":134,"updatedAt":1248},"powerbi-report-management","manage Power BI reports in Microsoft Fabric","Manage Power BI report workspace items and PBIR definitions in Microsoft Fabric via `az rest` CLI against the Fabric REST API. Use when the user wants to: (1) upload or publish a PBIR\u002Freport definition to Fabric, (2) get or download report definitions, (3) update report item definitions or properties, (4) list workspace reports, (5) delete reports. For editing PBIR files, pages, visuals, filters, themes, or formatting, use `powerbi-report-authoring`. For business questions over report data, use `fabriciq`. Triggers: upload PBIR report definition, upload Power BI report, download PBIR definition, publish PBIR definition, publish Power BI report to Fabric, manage Power BI reports, list workspace reports.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1240,1243,1244,1245],{"name":1241,"slug":1242,"type":1105},"Management","management",{"name":48,"slug":47,"type":1105},{"name":1206,"slug":1207,"type":1105},{"name":1246,"slug":1247,"type":1105},"Reporting","reporting","2026-07-07T06:53:36.626857",{"slug":1250,"name":1250,"fn":1251,"description":1252,"org":1253,"tags":1254,"stars":135,"repoUrl":134,"updatedAt":1259},"search-consumption-cli","search Microsoft Fabric catalog items","Search the Microsoft Fabric catalog across workspaces using the Fabric Catalog Search API. Use when the user wants to: (1) find an item by display name when the workspace is unknown, (2) list or discover items of a specific type across the tenant, (3) identify which workspace contains an item, (4) return item\u002Fworkspace IDs for downstream API calls. Dataflow Gen1\u002FGen2 items are not supported. For data queries after the item is known, use the workload-specific consumption skill (`sqldw-consumption-cli`, `spark-consumption-cli`, `eventhouse-consumption-cli`, or `fabriciq`). Triggers: \"catalog search\", \"fabric catalog search\", \"catalog lookup\", \"cross workspace catalog\", \"tenant catalog discovery\", \"tenant catalog inventory\", \"tenant catalog identifiers\", \"workspace catalog discovery\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1255,1256,1257,1258],{"name":147,"slug":146,"type":1105},{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":242,"slug":241,"type":1105},"2026-07-18T05:14:50.110876",{"slug":1261,"name":1261,"fn":1262,"description":1263,"org":1264,"tags":1265,"stars":135,"repoUrl":134,"updatedAt":153},"semantic-model-authoring","author and manage Power BI semantic models","Author and inspect Power BI semantic models and their metadata: list tables, columns, measures, relationships; create, edit, deploy, refresh, and manage models; optimize DAX; build Import, DirectQuery, and Direct Lake models; configure data sources, permissions, connections; and prepare for AI\u002FCopilot. Load this skill before acting on any semantic model authoring, metadata, or read-only inspection request: it picks the correct tool and method for the environment and permissions. Authoring-scoped: does not answer natural-language or data questions about a model's data. Does NOT author report visuals, manage workspaces, or manage RLS\u002FOLS roles. Triggers: \"create or edit a semantic model\", \"create or edit a DAX measure\", \"discover semantic model metadata\", \"list tables, columns, or measures in a semantic model\", \"refresh semantic model\", \"deploy semantic model to Fabric\",  \"prepare semantic model for AI\u002FCopilot\", \"set semantic model permissions\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1266,1267,1268,1269],{"name":297,"slug":296,"type":1105},{"name":279,"slug":278,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1206,"slug":1207,"type":1105},{"slug":1271,"name":1271,"fn":1272,"description":1273,"org":1274,"tags":1275,"stars":135,"repoUrl":134,"updatedAt":1283},"spark-authoring-cli","develop Microsoft Fabric Spark workflows","Author Fabric notebook cell code; run a notebook by name and report its status; and author\u002Fcreate Materialized Lake View (MLV) definitions (CREATE MATERIALIZED LAKE VIEW). Use for writing notebook cell code (PySpark, Scala, SparkR, %%sql, %%configure) — a %%sql cell that queries a lakehouse is authoring, not a T-SQL query — and running a notebook via the Jobs API (RunNotebook), including on the success path. Not for Livy sessions or ad-hoc calculations (use `spark-consumption-cli`); to refresh\u002Fschedule an EXISTING MLV, use `mlv-operations-cli`; for plain T-SQL, use `sqldw-consumption-cli`; for a FAILED notebook\u002Fjob, use `spark-operations-cli`. Triggers: \"write notebook code\", \"notebook cell code\", \"%%sql cell\", \"run the notebook named\", \"run notebook\", \"execute notebook\", \"notebookutils\", \"PySpark notebook\", \"%%configure\", \"create a materialized lake view\", \"create MLV\", \"materialized lake view\", \"MLV\", \"CREATE MATERIALIZED LAKE VIEW\", \"MLV incremental refresh\"\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1276,1277,1278,1279,1280],{"name":147,"slug":146,"type":1105},{"name":144,"slug":143,"type":1105},{"name":553,"slug":552,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1281,"slug":1282,"type":1105},"Spark","spark","2026-07-31T05:55:05.048008",{"slug":1285,"name":1285,"fn":1286,"description":1287,"org":1288,"tags":1289,"stars":135,"repoUrl":134,"updatedAt":1295},"spark-consumption-cli","analyze lakehouse data with PySpark and Spark SQL","Interactive ad-hoc Spark analysis through Fabric Lakehouse Livy API sessions ONLY. This skill NEVER authors or runs a notebook: any notebook cell (%%sql\u002F%%configure) or a notebook-run-by-name (and reporting its run status) is `spark-authoring-cli`, not this skill. Scope: create a Livy session, execute PySpark, inspect output, and compute quick calculations over lakehouse data (DataFrames, cross-lakehouse joins, Delta time-travel, unstructured\u002FJSON). For Spark failure triage use `spark-operations-cli`; for plain T-SQL Lakehouse\u002FWarehouse queries use `sqldw-consumption-cli`. Triggers: \"create Livy session\", \"run Livy calculation\", \"Livy session calculation\", \"interactive Livy session\", \"PySpark\", \"analyze with PySpark\", \"Spark DataFrame\", \"lakehouse with Python\", \"PySpark data quality\", \"Delta time-travel with Spark\", \"join tables across Lakehouses\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1290,1291,1292,1293,1294],{"name":150,"slug":149,"type":1105},{"name":144,"slug":143,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1151,"slug":1152,"type":1105},{"name":1281,"slug":1282,"type":1105},"2026-07-18T05:14:52.104846",{"slug":1297,"name":1297,"fn":1298,"description":1299,"org":1300,"tags":1301,"stars":135,"repoUrl":134,"updatedAt":1309},"sqldw-authoring-cli","author T-SQL for Microsoft Fabric Data Warehouse","Execute authoring T-SQL (DDL, DML, data ingestion, transactions, schema changes) against Microsoft Fabric Data Warehouse and SQL endpoints via the MCP `fabric-sqlendpoint-execute_query` tool. Use when the user wants to: (1) create\u002Falter\u002Fdrop tables, (2) insert\u002Fupdate\u002Fdelete\u002Fmerge data, (3) run COPY INTO or OPENROWSET ingestion, (4) manage transactions or stored procedures, (5) perform schema evolution, (6) use time travel or snapshots, (7) generate ETL\u002FELT workflows, (8) create views\u002Ffunctions\u002Fprocedures on Lakehouse SQLEP. Triggers: \"create table in warehouse\", \"insert data via T-SQL\", \"load from ADLS\", \"COPY INTO\", \"run ETL with T-SQL\", \"alter warehouse table\", \"upsert with T-SQL\", \"merge into warehouse\", \"create T-SQL procedure\", \"warehouse time travel\", \"recover deleted warehouse data\", \"create warehouse schema\", \"deploy warehouse\", \"transaction conflict\", \"snapshot isolation error\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1302,1303,1304,1305,1306],{"name":147,"slug":146,"type":1105},{"name":144,"slug":143,"type":1105},{"name":77,"slug":76,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1307,"slug":1308,"type":1105},"SQL","sql","2026-07-31T05:55:00.045464",{"slug":1311,"name":1311,"fn":1312,"description":1313,"org":1314,"tags":1315,"stars":135,"repoUrl":134,"updatedAt":1321},"sqldw-consumption-cli","query Fabric Data Warehouse with T-SQL","Execute read-only T-SQL queries against Fabric Data Warehouse, Lakehouse SQL Endpoints, and Mirrored Databases via the MCP `fabric-sqlendpoint-execute_query` tool. Default skill for any lakehouse data query (row counts, SELECT, filtering, aggregation) unless the user explicitly requests PySpark or Spark DataFrames. Use when the user wants to: (1) query warehouse\u002Flakehouse data, (2) count rows or explore lakehouse tables, (3) discover schemas\u002Fcolumns, (4) generate T-SQL scripts, (5) monitor SQL performance, (6) export results to CSV\u002FJSON. For a Fabric notebook cell (%%sql or other notebook magics), use `spark-authoring-cli`, not this skill. Triggers: \"warehouse\", \"SQL query\", \"T-SQL\", \"query warehouse\", \"show warehouse tables\", \"show lakehouse tables\", \"query lakehouse\", \"lakehouse table\", \"how many rows\", \"count rows\", \"SQL endpoint\", \"describe warehouse schema\", \"generate T-SQL script\", \"warehouse performance\", \"export SQL data\", \"connect to warehouse\", \"lakehouse data\", \"explore lakehouse\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1316,1317,1318,1319,1320],{"name":150,"slug":149,"type":1105},{"name":77,"slug":76,"type":1105},{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":1307,"slug":1308,"type":1105},"2026-07-31T05:55:04.037438",{"slug":1323,"name":1323,"fn":1324,"description":1325,"org":1326,"tags":1327,"stars":135,"repoUrl":134,"updatedAt":1333},"sqldw-operations-cli","analyze Fabric Data Warehouse performance","Analyze Fabric Data Warehouse performance via the MCP execute_query tool and queryinsights views. Diagnose slow queries, SQL pool pressure, cache coldness, and recommend clustering keys. Triggers: \"DW slow query analysis\", \"slowest queries warehouse\", \"queryinsights long running\", \"warehouse CPU resource consumers\", \"SQL pool pressure window\", \"pressure events warehouse\", \"DW cache warmth cold start\", \"cache warmth analysis\", \"warehouse cluster key recommendation\", \"cluster tables performance\", \"DW performance baseline comparison\", \"performance degraded warehouse\", \"warehouse user query patterns\", \"queryinsights diagnostics\", \"DW optimization MCP\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1328,1329,1330,1331,1332],{"name":297,"slug":296,"type":1105},{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":540,"slug":539,"type":1105},{"name":1307,"slug":1308,"type":1105},"2026-07-31T05:55:02.054771",{"slug":1335,"name":1335,"fn":1336,"description":1337,"org":1338,"tags":1339,"stars":135,"repoUrl":134,"updatedAt":1345},"synapse-migration","migrate Azure Synapse Spark workloads to Fabric","Port Azure Synapse Analytics Spark workloads to Microsoft Fabric. Translates mssparkutils calls to notebookutils (including the env→runtime namespace change), replaces Linked Services with Fabric Data Connections and OneLake Shortcuts. Covers Spark Pools, Lake Databases, Notebooks, and Spark Job Definitions. Use when the user wants to: (1) port Synapse Spark notebooks to Fabric Lakehouse or Spark Job Definitions, (2) replace mssparkutils or Linked Services in Synapse code. Triggers: \"migrate from synapse\", \"synapse to fabric\", \"mssparkutils to notebookutils\", \"synapse linked service replacement\", \"port synapse notebooks\", \"synapse workspace migration\".\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":5},[1340,1341,1342,1343,1344],{"name":30,"slug":29,"type":1105},{"name":144,"slug":143,"type":1105},{"name":6,"slug":5,"type":1105},{"name":48,"slug":47,"type":1105},{"name":39,"slug":38,"type":1105},"2026-07-31T05:54:58.050788"]