How do I install the Powerbi Source Metadata Discovery skill?

Run npx skillmds@latest add rweisssieker-xp/powerbi-source-metadata-discovery in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Powerbi Source Metadata Discovery safe to use?

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Which AI agents work with Powerbi Source Metadata Discovery?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Powerbi Source Metadata Discovery free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Powerbi Source Metadata Discovery?

rweisssieker-xp (@rweisssieker-xp) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Powerbi Source Metadata Discovery by rweisssieker-xp

Name: Powerbi Source Metadata Discovery
Author: rweisssieker-xp

Powerbi Source Metadata Discovery

Use when a Power BI solution needs metadata discovery for SAP, Salesforce, Dynamics/Dataverse, Power BI/Fabric, SQL databases, OData feeds, REST APIs, files, warehouses, lakehouses, or semantic models before designing reports.

File contents

Power BI Source Metadata Discovery

Use this skill before committing to field names, tables, relationships, or extraction logic.

Discovery Targets

Power BI native connector source classes: File, Database, Microsoft Fabric, Power Platform, Azure, Online Services, and Other.
Files: Excel Workbook through the native Excel connector, Text/CSV, XML, JSON, Folder, PDF, Parquet, SharePoint Folder, OneDrive/SharePoint-hosted files, and folder-combine patterns.
SAP: CDS views, OData metadata, BW queries, Datasphere objects, replicated warehouse tables.
Salesforce: objects, fields, relationships, picklists, record types.
Dynamics/Dataverse: entities/tables, columns, option sets, relationships, security roles.
Power BI/Fabric: workspaces, semantic models, tables, measures, lineage, refresh, endorsements.
SQL/warehouse/lakehouse: schemas, tables, columns, data types, constraints, row counts, partitions.
APIs/OData: metadata document, endpoints, pagination, filters, throttling, delta support.
Generic connectors: Web, OData, ODBC, OLE DB, certified third-party connectors, custom connectors, R/Python script sources, and exported files from unsupported source products.

Output Requirements

Produce metadata inventory, candidate facts/dimensions, key candidates, quality concerns, and extraction options.
Mark unknowns that block model design.
State the exact Power BI / Power Query connector family, connection mode, gateway/credential need, folding expectation, and production fallback.
For Excel sources, identify workbook path type, sheets/tables/named ranges, header rows, date/number culture, merged cells, hidden sheets, schema drift risk, and whether the source should be promoted into a governed lakehouse/warehouse before production use.

---name: powerbi-source-metadata-discoverydescription: Use when a Power BI solution needs metadata discovery for SAP, Salesforce, Dynamics/Dataverse, Power BI/Fabric, SQL databases, OData feeds, REST APIs, files, warehouses, lakehouses, or semantic models before designing reports.---# Power BI Source Metadata DiscoveryUse this skill before committing to field names, tables, relationships, or extraction logic.## Discovery Targets- Power BI native connector source classes: File, Database, Microsoft Fabric, Power Platform, Azure, Online Services, and Other.- Files: Excel Workbook through the native Excel connector, Text/CSV, XML, JSON, Folder, PDF, Parquet, SharePoint Folder, OneDrive/SharePoint-hosted files, and folder-combine patterns.- SAP: CDS views, OData metadata, BW queries, Datasphere objects, replicated warehouse tables.- Salesforce: objects, fields, relationships, picklists, record types.- Dynamics/Dataverse: entities/tables, columns, option sets, relationships, security roles.- Power BI/Fabric: workspaces, semantic models, tables, measures, lineage, refresh, endorsements.- SQL/warehouse/lakehouse: schemas, tables, columns, data types, constraints, row counts, partitions.- APIs/OData: metadata document, endpoints, pagination, filters, throttling, delta support.- Generic connectors: Web, OData, ODBC, OLE DB, certified third-party connectors, custom connectors, R/Python script sources, and exported files from unsupported source products.## Output Requirements- Produce metadata inventory, candidate facts/dimensions, key candidates, quality concerns, and extraction options.- Mark unknowns that block model design.- State the exact Power BI / Power Query connector family, connection mode, gateway/credential need, folding expectation, and production fallback.- For Excel sources, identify workbook path type, sheets/tables/named ranges, header rows, date/number culture, merged cells, hidden sheets, schema drift risk, and whether the source should be promoted into a governed lakehouse/warehouse before production use.

Frequently asked questions