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Power Bi

Community
korchard333
power-bi

Power BI Development. Use when: building reports, TMDL semantic models, DAX patterns, PBIR report definitions, Fabric REST API, Direct Lake, incremental refresh, Dataverse as data source, Power BI Embedded in Code Apps, CI/CD for Power BI.

Overview

Publisherkorchard333
Repositoryclaude-power-platform-community
Skill namepower-bi
Stars
50
Forks
6
Bundled files
8
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by korchard333 on GitHub. Read the source before you install it.

Installation

Install the Power Bi AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/korchard333/claude-power-platform-community/tree/main/.claude/skills/power-bi
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/korchard333/claude-power-platform-community.git /tmp/claude-power-platform-community
mkdir -p .claude/skills
cp -r /tmp/claude-power-platform-community/.claude/skills/power-bi .claude/skills/power-bi
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Power Bi in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Power Bi on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Power Bi is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Skill: Power BI Development

When to Use

Trigger when building Power BI semantic models, reports, DAX measures, or managing Power BI via Fabric REST APIs. Covers TMDL/model.bim semantic model definitions, PBIR report definitions, DAX patterns, and deployment automation.


Architecture Overview

Power BI Project Structure (PBIP Format)

MyReport.pbip                    # Project file
├── MyReport.SemanticModel/
│   ├── definition/
│   │   ├── model.tmdl           # TMDL format (modern, human-readable)
│   │   ├── tables/
│   │   │   ├── Sales.tmdl       # Table definitions with columns, measures
│   │   │   ├── Date.tmdl
│   │   │   └── Product.tmdl
│   │   ├── relationships.tmdl   # All relationships
│   │   ├── expressions.tmdl     # M/Power Query expressions
│   │   ├── cultures/
│   │   │   └── en-US.tmdl       # Translations
│   │   └── roles/
│   │       └── RegionRLS.tmdl   # Row-level security
│   ├── definition.pbism         # Semantic model metadata
│   └── .platform
│
├── MyReport.Report/
│   ├── definition/
│   │   ├── report.json          # Report definition
│   │   ├── pages/
│   │   │   ├── page1/
│   │   │   │   ├── page.json    # Page config
│   │   │   │   └── visuals/
│   │   │   │       ├── visual1.json
│   │   │   │       └── visual2.json
│   │   ├── bookmarks/           # Report bookmarks
│   │   └── theme.json           # Report theme
│   ├── definition.pbir          # Report metadata
│   └── .platform

⚠️ REQUIRED: Load Sub-Files Before Implementation

SKILL.md is a summary only — it is NOT sufficient for implementation.

The detailed content (complete payloads, XML templates, working examples, edge-case handling) lives in sub-files in the same directory as this SKILL.md. Before writing any code, you MUST use read_file on the sub-files relevant to your task:

  • TMDL — table definitions, columns, measures, partitions, Date table pattern, relationships, row-level security
  • DAX Patterns — time intelligence, ranking, KPIs, field parameters, CALCULATE context patterns
  • PBIR Report Definition — page.json, visual.json, theme definition
  • Fabric REST API — authentication, workspace management, dataset operations, report operations, deployment pipeline
  • Direct Lake & Incremental Refresh — Direct Lake mode, storage mode selection, incremental refresh setup
  • Dataverse as Data Source — Power Query M connection, TDS endpoint SQL access
  • Power BI Embedded — embed token generation, React integration for Code Apps
  • CI/CD — GitHub Actions pipeline for automated deployment

Best Practices

Semantic Model

  • Always create a dedicated Date table (don't rely on auto date/time)
  • Use star schema: fact tables at center, dimension tables around
  • Hide foreign key columns from report view
  • Set summarizeBy: none on non-additive columns (IDs, codes)
  • Use folders to organize measures by business domain
  • Format strings on all measures (currency, %, number)

DAX

  • Use variables (VAR ... RETURN) for readability and performance
  • Use DIVIDE() instead of / (handles division by zero)
  • Use BLANK() not 0 for missing values
  • Avoid FILTER(table, ...) when column filter works — use KEEPFILTERS or VALUES
  • Never use CALCULATE with row context unless you understand context transition

Reports

  • Maximum 8-10 visuals per page
  • Use bookmarks for showing/hiding visual states instead of multiple pages
  • Apply consistent theme across all reports
  • Use drill-through for detail pages, not separate reports
  • Test with Row-Level Security using "View As" in Power BI Service

Anti-Patterns

  • Auto date/time enabled (creates hidden tables, bloats model)
  • Bidirectional cross-filtering (causes ambiguity, performance issues)
  • Too many measures without folders (unnavigable model)
  • CALCULATE(COUNTROWS(...)) when COUNTROWS alone works
  • Import mode on large Dataverse tables without incremental refresh
  • Publishing .pbix files directly instead of using deployment pipelines
  • Hardcoding server/database names instead of using parameters
  • Missing RLS when multiple business units access the same report
  • Calculated columns for values that should be measures
  • Not testing refresh after deployment (connection strings, credentials)

Note: Power BI Dashboards and Datasets are NOT supported in Power Platform Pipelines. Use Power BI's own deployment pipelines (Fabric REST API) for Power BI content promotion.


Related Skills

  • dataverse — Dataverse as a Power BI data source
  • code-apps — Embedding Power BI in Code Apps

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Power Bi AI skill do?

Power BI Development. Use when: building reports, TMDL semantic models, DAX patterns, PBIR report definitions, Fabric REST API, Direct Lake, incremental refresh, Dataverse as data source, Power BI Embedded in Code Apps, CI/CD for Power BI.

Why use Power Bi on TypingMind?

Because you install it once and use it with any model. Power Bi is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Power Bi in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/korchard333/claude-power-platform-community/tree/main/.claude/skills/power-bi. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Power Bi?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Power Bi?

As many as you like. As long as a model supports skills, you can use Power Bi with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Power Bi AI skill free?

Yes. It is published on GitHub by korchard333 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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