[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M699XG7CK7RJE2ADXDZRHTC0":3,"skill-same:01M699XG7CK7RJE2ADXDZRHTC0":55},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":21,"linkOnly":22,"markdownContent":23,"markdownBody":24,"frontMatter":25,"refName":26,"commitSha":27,"skillDirectory":28,"forksCount":29,"repositoryHtmlUrl":30,"repositoryHomepageUrl":6,"ownerHtmlUrl":31,"ownerBlogUrl":32,"ownerDescription":33,"updatedAt":34,"install":35,"resources":48},"01M699XG7CK7RJE2ADXDZRHTC0","schema-discovery",null,"Explore Power BI semantic model schemas using DAX INFO functions. Progressive metadata discovery strategy, scope estimation, and narrowing techniques for tables, columns, measures, and relationships.","microsoft\u002Frayfin","microsoft","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6154722?v=4","01M698VYDXZ6JW5WH3CRV650R8","Microsoft","01M699VK9NEV8GH0Y5JKT1G8XG",657,"MIT","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin\u002Fblob\u002Fmain\u002Fsamples\u002Fdata-app\u002F.agents\u002Fskills\u002Fschema-discovery\u002FSKILL.md",[],[19,20],"schema discovery","dax","2026-11-10 10:12:30",false,"---\nname: schema-discovery\ndescription: >\n  Explore Power BI semantic model schemas using DAX INFO functions.\n  Progressive metadata discovery strategy, scope estimation, and\n  narrowing techniques for tables, columns, measures, and relationships.\n---\n\n# Schema Discovery\n\n## Table of Contents\n\n| Task | Reference | Notes |\n|---|---|---|\n| Must\u002FPrefer\u002FAvoid | [SKILL.md: Must\u002FPrefer\u002FAvoid](#must--prefer--avoid) | Guardrails for schema discovery |\n| Progressive Discovery Strategy | [SKILL.md: Progressive Schema Discovery](#progressive-schema-discovery) | Decision tree for on-demand metadata fetching |\n| Recommended Discovery Order | [SKILL.md: Recommended Discovery Order](#recommended-discovery-order) | Start with scope estimation → tables → columns → measures → relationships |\n| Metadata Object → INFO Function Map | [SKILL.md: Metadata Object → INFO Function Map](#metadata-object--info-function-map) | Tables, columns, measures, relationships, calc groups, calendars, UDFs, variations |\n| Scope Estimation Queries | [discovery-queries.md: Scope Estimation Queries](.\u002Freferences\u002Fdiscovery-queries.md#scope-estimation-queries) | Probe table\u002Fcolumn\u002Fmeasure\u002Frelationship counts before deep discovery |\n| INFO Output Columns | [discovery-queries.md: INFO Output Columns](.\u002Freferences\u002Fdiscovery-queries.md#info-output-columns) | INFO.VIEW.*(read access); INFO.* (may need elevated access) |\n| Narrowing Results (Projection + Filtering) | [discovery-queries.md: Narrowing Results](.\u002Freferences\u002Fdiscovery-queries.md#narrowing-results-projection--filtering) | SELECTCOLUMNS + FILTER to reduce output volume |\n| Advanced Metadata (Calc Groups, Calendars, UDFs) | [discovery-queries.md: Advanced Metadata Queries](.\u002Freferences\u002Fdiscovery-queries.md#advanced-metadata-queries) | INFO.CALCULATIONGROUPS, INFO.CALENDARS, INFO.USERDEFINEDFUNCTIONS, INFO.VARIATIONS |\n| Complete INFO Function Catalog | [discovery-queries.md: Complete INFO Function Catalog](.\u002Freferences\u002Fdiscovery-queries.md#complete-info-function-catalog-dynamic) | Dynamic query to enumerate all INFO functions in the engine |\n\n## Must \u002F Prefer \u002F Avoid\n\n### Must\n\n- Use fully-qualified `'Table'[Column]` for column references\n- Use simple `[Measure]` for measure references\n\n### Prefer\n\n- INFO.VIEW functions for initial metadata discovery (read access, lightweight)\n- Progressive schema discovery over full schema dumps\n- SELECTCOLUMNS + FILTER to narrow INFO results\n\n### Avoid\n\n- Fetching full schema upfront — discover incrementally based on need\n- Re-fetching metadata already discovered in this conversation\n- Using GetSemanticModelSchema, DiscoverArtifacts, or GenerateQuery MCP tools (these are not available)\n\n## Progressive Schema Discovery\n\nDiscover metadata incrementally based on what the user actually needs.\n\n### Strategy (Decision Tree)\n\n```text\nUser asks a question\n  → Do I know which tables are relevant?\n    → NO: Run INFO.VIEW.TABLES() to get table inventory\n    → YES: Do I know the columns\u002Fmeasures for those tables?\n      → NO: Run filtered INFO.VIEW.COLUMNS() and INFO.VIEW.MEASURES() for those tables\n      → YES: Do I need relationships?\n        → YES: Run INFO.VIEW.RELATIONSHIPS() filtered to those tables\n        → NO: Do I need advanced metadata?\n          → Have elevated INFO functions already failed in this session?\n            → YES: Skip — assume no permission for all elevated queries\n            → NO: Try the relevant elevated query:\n              → Calculation groups: INFO.CALCULATIONGROUPS() + INFO.CALCULATIONITEMS()\n              → Calendars: INFO.CALENDARS()\n              → User-defined functions: INFO.USERDEFINEDFUNCTIONS()\n              → Variations: INFO.VARIATIONS()\n              → If query fails with permission error: mark elevated access as unavailable\n  → Use discovered schema to write DAX queries (see dax-authoring skill)\n```\n\n### Rules\n\n- **Start with scope estimation** — Run the scope probe query first to understand model size\n- **Discover on demand** — Only fetch tables\u002Fcolumns\u002Fmeasures relevant to the current user request\n- **Use INFO.VIEW functions first** (read access) — tables, columns, measures, relationships\n- **Use INFO functions** (may need elevated access) for: calculation groups, calculation items, variations, user-defined functions, calendars\n- **Handle permission failures gracefully** — If an elevated INFO function fails but INFO.VIEW.* functions succeeded, assume the user lacks elevated permissions and skip all elevated discoveries entirely\n- **Always narrow results** — Use SELECTCOLUMNS + FILTER to fetch only needed columns and rows\n- **Cache discovered schema mentally** — Don't re-fetch what you've already discovered in this conversation\n\n### Recommended Discovery Order\n\n1. **Scope estimation** — Count tables, columns, measures, relationships\n2. **Tables** — Get table names, identify relevant ones\n3. **Columns** — Get columns for relevant tables only\n4. **Measures** — Get measures (prefer using these over raw aggregations)\n5. **Relationships** — Get relationships between relevant tables\n6. **Advanced metadata** (if needed) — Calculation groups, calendars, UDFs, variations\n\n### Scope Estimation Query\n\n```dax\nEVALUATE\nROW(\n    \"TableCount\", COUNTROWS(INFO.VIEW.TABLES()),\n    \"ColumnCount\", COUNTROWS(INFO.VIEW.COLUMNS()),\n    \"MeasureCount\", COUNTROWS(INFO.VIEW.MEASURES()),\n    \"RelationshipCount\", COUNTROWS(INFO.VIEW.RELATIONSHIPS())\n)\n```\n\n### Metadata Object → INFO Function Map\n\n| Metadata Object | Primary INFO Functions | Access Level |\n|---|---|---|\n| Tables | `INFO.VIEW.TABLES()` | Read |\n| Columns | `INFO.VIEW.COLUMNS()` | Read |\n| Measures | `INFO.VIEW.MEASURES()` | Read |\n| Relationships | `INFO.VIEW.RELATIONSHIPS()` | Read |\n| Model config | `INFO.MODEL()` | May need elevated |\n| Calculation groups | `INFO.CALCULATIONGROUPS()`, `INFO.CALCULATIONITEMS()` | May need elevated |\n| Calendars | `INFO.CALENDARS()`, `INFO.CALENDARCOLUMNGROUPS()`, `INFO.CALENDARCOLUMNREFERENCES()` | May need elevated |\n| User-defined functions | `INFO.USERDEFINEDFUNCTIONS()` | May need elevated |\n| Variations | `INFO.VARIATIONS()` | May need elevated |\n\nFor the full query catalog and output column details, see [discovery-queries.md](.\u002Freferences\u002Fdiscovery-queries.md).\n\n## Running Discovery Queries\n\nUse `npx fabric-app-data query \u003Calias> --query '\u003CDAX>'` to execute INFO queries against a semantic model. For full CLI options (profiles, file input, result limits), see the `fabric-cli` skill.\n\n```bash\nnpx fabric-app-data query \u003Calias> --query \"EVALUATE INFO.VIEW.TABLES()\"\n```\n\n## Troubleshooting\n\n| Problem | Solution |\n|---------|----------|\n| INFO functions return permission errors | Fall back to INFO.VIEW functions; mark elevated access as unavailable for this session |\n| Metadata output too large | Use scope estimation + narrowing patterns from [discovery-queries.md](.\u002Freferences\u002Fdiscovery-queries.md) |\n","# Schema Discovery\n\n## Table of Contents\n\n| Task | Reference | Notes |\n|---|---|---|\n| Must\u002FPrefer\u002FAvoid | [SKILL.md: Must\u002FPrefer\u002FAvoid](#must--prefer--avoid) | Guardrails for schema discovery |\n| Progressive Discovery Strategy | [SKILL.md: Progressive Schema Discovery](#progressive-schema-discovery) | Decision tree for on-demand metadata fetching |\n| Recommended Discovery Order | [SKILL.md: Recommended Discovery Order](#recommended-discovery-order) | Start with scope estimation → tables → columns → measures → relationships |\n| Metadata Object → INFO Function Map | [SKILL.md: Metadata Object → INFO Function Map](#metadata-object--info-function-map) | Tables, columns, measures, relationships, calc groups, calendars, UDFs, variations |\n| Scope Estimation Queries | [discovery-queries.md: Scope Estimation Queries](.\u002Freferences\u002Fdiscovery-queries.md#scope-estimation-queries) | Probe table\u002Fcolumn\u002Fmeasure\u002Frelationship counts before deep discovery |\n| INFO Output Columns | [discovery-queries.md: INFO Output Columns](.\u002Freferences\u002Fdiscovery-queries.md#info-output-columns) | INFO.VIEW.*(read access); INFO.* (may need elevated access) |\n| Narrowing Results (Projection + Filtering) | [discovery-queries.md: Narrowing Results](.\u002Freferences\u002Fdiscovery-queries.md#narrowing-results-projection--filtering) | SELECTCOLUMNS + FILTER to reduce output volume |\n| Advanced Metadata (Calc Groups, Calendars, UDFs) | [discovery-queries.md: Advanced Metadata Queries](.\u002Freferences\u002Fdiscovery-queries.md#advanced-metadata-queries) | INFO.CALCULATIONGROUPS, INFO.CALENDARS, INFO.USERDEFINEDFUNCTIONS, INFO.VARIATIONS |\n| Complete INFO Function Catalog | [discovery-queries.md: Complete INFO Function Catalog](.\u002Freferences\u002Fdiscovery-queries.md#complete-info-function-catalog-dynamic) | Dynamic query to enumerate all INFO functions in the engine |\n\n## Must \u002F Prefer \u002F Avoid\n\n### Must\n\n- Use fully-qualified `'Table'[Column]` for column references\n- Use simple `[Measure]` for measure references\n\n### Prefer\n\n- INFO.VIEW functions for initial metadata discovery (read access, lightweight)\n- Progressive schema discovery over full schema dumps\n- SELECTCOLUMNS + FILTER to narrow INFO results\n\n### Avoid\n\n- Fetching full schema upfront — discover incrementally based on need\n- Re-fetching metadata already discovered in this conversation\n- Using GetSemanticModelSchema, DiscoverArtifacts, or GenerateQuery MCP tools (these are not available)\n\n## Progressive Schema Discovery\n\nDiscover metadata incrementally based on what the user actually needs.\n\n### Strategy (Decision Tree)\n\n```text\nUser asks a question\n  → Do I know which tables are relevant?\n    → NO: Run INFO.VIEW.TABLES() to get table inventory\n    → YES: Do I know the columns\u002Fmeasures for those tables?\n      → NO: Run filtered INFO.VIEW.COLUMNS() and INFO.VIEW.MEASURES() for those tables\n      → YES: Do I need relationships?\n        → YES: Run INFO.VIEW.RELATIONSHIPS() filtered to those tables\n        → NO: Do I need advanced metadata?\n          → Have elevated INFO functions already failed in this session?\n            → YES: Skip — assume no permission for all elevated queries\n            → NO: Try the relevant elevated query:\n              → Calculation groups: INFO.CALCULATIONGROUPS() + INFO.CALCULATIONITEMS()\n              → Calendars: INFO.CALENDARS()\n              → User-defined functions: INFO.USERDEFINEDFUNCTIONS()\n              → Variations: INFO.VARIATIONS()\n              → If query fails with permission error: mark elevated access as unavailable\n  → Use discovered schema to write DAX queries (see dax-authoring skill)\n```\n\n### Rules\n\n- **Start with scope estimation** — Run the scope probe query first to understand model size\n- **Discover on demand** — Only fetch tables\u002Fcolumns\u002Fmeasures relevant to the current user request\n- **Use INFO.VIEW functions first** (read access) — tables, columns, measures, relationships\n- **Use INFO functions** (may need elevated access) for: calculation groups, calculation items, variations, user-defined functions, calendars\n- **Handle permission failures gracefully** — If an elevated INFO function fails but INFO.VIEW.* functions succeeded, assume the user lacks elevated permissions and skip all elevated discoveries entirely\n- **Always narrow results** — Use SELECTCOLUMNS + FILTER to fetch only needed columns and rows\n- **Cache discovered schema mentally** — Don't re-fetch what you've already discovered in this conversation\n\n### Recommended Discovery Order\n\n1. **Scope estimation** — Count tables, columns, measures, relationships\n2. **Tables** — Get table names, identify relevant ones\n3. **Columns** — Get columns for relevant tables only\n4. **Measures** — Get measures (prefer using these over raw aggregations)\n5. **Relationships** — Get relationships between relevant tables\n6. **Advanced metadata** (if needed) — Calculation groups, calendars, UDFs, variations\n\n### Scope Estimation Query\n\n```dax\nEVALUATE\nROW(\n    \"TableCount\", COUNTROWS(INFO.VIEW.TABLES()),\n    \"ColumnCount\", COUNTROWS(INFO.VIEW.COLUMNS()),\n    \"MeasureCount\", COUNTROWS(INFO.VIEW.MEASURES()),\n    \"RelationshipCount\", COUNTROWS(INFO.VIEW.RELATIONSHIPS())\n)\n```\n\n### Metadata Object → INFO Function Map\n\n| Metadata Object | Primary INFO Functions | Access Level |\n|---|---|---|\n| Tables | `INFO.VIEW.TABLES()` | Read |\n| Columns | `INFO.VIEW.COLUMNS()` | Read |\n| Measures | `INFO.VIEW.MEASURES()` | Read |\n| Relationships | `INFO.VIEW.RELATIONSHIPS()` | Read |\n| Model config | `INFO.MODEL()` | May need elevated |\n| Calculation groups | `INFO.CALCULATIONGROUPS()`, `INFO.CALCULATIONITEMS()` | May need elevated |\n| Calendars | `INFO.CALENDARS()`, `INFO.CALENDARCOLUMNGROUPS()`, `INFO.CALENDARCOLUMNREFERENCES()` | May need elevated |\n| User-defined functions | `INFO.USERDEFINEDFUNCTIONS()` | May need elevated |\n| Variations | `INFO.VARIATIONS()` | May need elevated |\n\nFor the full query catalog and output column details, see [discovery-queries.md](.\u002Freferences\u002Fdiscovery-queries.md).\n\n## Running Discovery Queries\n\nUse `npx fabric-app-data query \u003Calias> --query '\u003CDAX>'` to execute INFO queries against a semantic model. For full CLI options (profiles, file input, result limits), see the `fabric-cli` skill.\n\n```bash\nnpx fabric-app-data query \u003Calias> --query \"EVALUATE INFO.VIEW.TABLES()\"\n```\n\n## Troubleshooting\n\n| Problem | Solution |\n|---------|----------|\n| INFO functions return permission errors | Fall back to INFO.VIEW functions; mark elevated access as unavailable for this session |\n| Metadata output too large | Use scope estimation + narrowing patterns from [discovery-queries.md](.\u002Freferences\u002Fdiscovery-queries.md) |\n",{"name":5,"description":7},"main","0979439a7a0806abd0ee48c2619b37f297ae1324","samples\u002Fdata-app\u002F.agents\u002Fskills\u002Fschema-discovery",73,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin","https:\u002F\u002Fgithub.com\u002Fmicrosoft","https:\u002F\u002Fopensource.microsoft.com","Open source projects and samples from Microsoft","2026-11-12 01:21:10",{"source":8,"skillName":5,"commands":36,"prompt":46,"zipAvailable":47},[37,40,43],{"tool":38,"command":39},"npx","npx skills add microsoft\u002Frayfin --skill schema-discovery",{"tool":41,"command":42},"bunx","bunx skills add microsoft\u002Frayfin --skill schema-discovery",{"tool":44,"command":45},"pnpm","pnpm dlx skills add microsoft\u002Frayfin --skill schema-discovery","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin\u002Fblob\u002Fmain\u002Fsamples\u002Fdata-app\u002F.agents\u002Fskills\u002Fschema-discovery\u002FSKILL.md",true,[49],{"path":50,"resourceType":51,"resourceTypeDesc":52,"sizeBytes":53,"sourceHtmlUrl":54},"references\u002Fdiscovery-queries.md","REFERENCE","参考文档",4211,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin\u002Fblob\u002Fmain\u002Fsamples\u002Fdata-app\u002F.agents\u002Fskills\u002Fschema-discovery\u002Freferences\u002Fdiscovery-queries.md",[56,69,89,94,113,121],{"skillNo":57,"name":58,"nameZh":6,"description":59,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":60,"categories":61,"keywords":62,"publishedAt":21},"01M699YEY2QDVPKTZS3HR9AX84","rayfin-getting-started","Use when starting or creating a NEW Rayfin app, or when a Rayfin task comes up and you are not yet inside a Rayfin project. Gets you into a project with the Rayfin CLI, then hands off to the authoritative, version-locked in-project rayfin skill\u002Fdocs that own all in-project work. Triggers: build a Rayfin app, start a Rayfin project, create a new Rayfin app, create-rayfin, npm create @microsoft\u002Frayfin, rayfin init, scaffold rayfin, rayfin CLI, rayfin template, universal app, awesome-rayfin gallery, get started with Rayfin","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin\u002Fblob\u002Fmain\u002Fskills\u002Frayfin-getting-started\u002FSKILL.md",[],[63,64,65,66,9,67,68],"rayfin getting started","rayfin","scaffold","init","docs","cli",{"skillNo":70,"name":71,"nameZh":6,"description":72,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":73,"categories":74,"keywords":85,"publishedAt":21},"01M699YCN4ZDW2AMDP4NVJ2QGC","visuals","Use when user wants to incorporate charts, graphs, data grid,  or other visual representations of data into their project. Use VegaVisual and DataGrid components to create these visuals,  utilizing the shared DataTable input, formatting, theme, and interactivity. Covers the onInteraction selection\u002Fclick events host apps consume, named multi-table data input for layered overlays and reference lines, and Vega-Lite native selections. Triggers: chart, graph, plot, dashboard, KPI, metric, trend, scorecard, data grid, visualize.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin\u002Fblob\u002Fmain\u002Fsamples\u002Funiversal-app\u002Ftemplate\u002F.agents\u002Fskills\u002Fvisuals\u002FSKILL.md",[75,80],{"categoryNo":76,"categoryName":77,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000013","分析与可视化","SCENARIO","使用场景",{"categoryNo":81,"categoryName":82,"taxonomyType":83,"taxonomyTypeDesc":84},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[71,86,87,88],"components","dashboard","visualize",{"skillNo":90,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":91,"categories":92,"keywords":93,"publishedAt":21},"01M699YBEP146MJZJNN8YEBZ2G","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin\u002Fblob\u002Fmain\u002Fsamples\u002Funiversal-app\u002Ftemplate\u002F.agents\u002Fskills\u002Fschema-discovery\u002FSKILL.md",[],[19,20],{"skillNo":95,"name":96,"nameZh":6,"description":97,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":98,"categories":99,"keywords":109,"publishedAt":21},"01M699Y9E80WYFKD1S4MT4B1CS","query-design","Separates DAX data-fetching from TypeScript presentation. Guides when to use  DAX vs. TypeScript vs. Vega-Lite for aggregation, total rows, FORMAT(), SELECTCOLUMNS,  BLANK handling, filtering, multi-grain queries, cross-filtering and cross-highlight subset\u002Foverlay queries, and format strings.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin\u002Fblob\u002Fmain\u002Fsamples\u002Funiversal-app\u002Ftemplate\u002F.agents\u002Fskills\u002Fquery-design\u002FSKILL.md",[100,103,106],{"categoryNo":101,"categoryName":102,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000003","演示文稿",{"categoryNo":104,"categoryName":105,"taxonomyType":78,"taxonomyTypeDesc":79},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":107,"categoryName":108,"taxonomyType":83,"taxonomyTypeDesc":84},"01JBSEEDCAT000000000000032","设计师",[110,111,20,112],"query design","design","typescript",{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":119,"publishedAt":21},"01M699Y7CKZ55QSYFE827RRVJE","functions-capability","Apply and build the Universal App functions capability. Use for trusted server-side logic, secrets, external APIs, custom model endpoints, published Fabric data agents, webhooks, or privileged operations.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin\u002Fblob\u002Fmain\u002Fsamples\u002Funiversal-app\u002Ftemplate\u002F.agents\u002Fskills\u002Ffunctions-capability\u002FSKILL.md",[],[120],"functions capability",{"skillNo":122,"name":123,"nameZh":6,"description":124,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":125,"categories":126,"keywords":127,"publishedAt":21},"01M699Y5R87YE620T78Z30KQSA","fabric-sdk","How to query Fabric data from a running app through the Rayfin connectors client. Use getRayfinClient().connectors.\u003Cname>.executeQuery to run DAX against a semantic model, and toQueryResult to normalize the response.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frayfin\u002Fblob\u002Fmain\u002Fsamples\u002Funiversal-app\u002Ftemplate\u002F.agents\u002Fskills\u002Ffabric-sdk\u002FSKILL.md",[],[128,129,20,130,64,131],"sdk","fabric sdk","rayfin connectors","connectors"]