Agent skill · Data & Analytics

refresh-semantic-model

Automatically invoke this skill whenever the user asks to refresh a semantic model or a dataset. Can also be used to manage, optimize, troubleshoot, or configure a refresh or a refresh schedule.

data-goblingithub.com/data-goblinGitHub ↗
claude-codecopilotships scriptsGPL-3.0
Install
npx skills add data-goblin/power-bi-agentic-development --skill refresh-semantic-model --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 4
SKILL.md size: 14 KB
Bundled scripts: yes
Path: plugins/semantic-models/skills/refresh-semantic-model/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 833
Language: C#

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Refreshing Semantic Models Trigger, monitor, validate, and troubleshoot semantic model refreshes via the Power BI Enhanced Refresh REST API and Fabric CLI. ## Core Concepts A semantic model refresh reloads data from upstream sources and/or recalculates dependent objects (calculated columns, calculated tables, measures). The scope can be the entire model, specific tables, or individual partitions. Six refresh types are available via the REST API; a seventh (`add`) is TMSL-only: | Type | Reloads Data | Recalculates | Primary Use Case | API | |---------------|:------------:|:------------:|--------------------------------------|:----:| | `full` | Yes | Yes | Complete reload from scratch | REST | | `automatic` | Conditional | Conditional | Smart refresh; process only if needed| REST | | `dataOnly` | Yes | No* | Reload data; clear dependents | REST | | `calculate` | No | Yes | Recalculate without reloading data | REST | | `clearValues` | No | No | Empty data from objects | REST | | `defragment` | No | No | Clean up column dictionaries | REST | | `add` | Append | Yes | Append rows to a partition | TMSL | *`dataOnly` clears dependent objects (calculated columns, calculated tables) but do

What's inside
Steps it walks through
  1. Core Concepts
  2. Refresh Workflow
  3. Step 1: Resolve IDs
  4. Step 2: Query Baseline Data (Pre-Refresh Validation)
  5. Step 3: Trigger the Refresh
  6. Step 4: Monitor Status
  7. Step 5: Post-Refresh Validation
  8. Step 6: Cancel (if needed)
  9. Using the Refresh Script
  10. Enhanced Refresh Options
  11. Common Patterns
  12. Two-Phase Refresh (Large Models)
  13. Selective Partition Refresh
  14. Refresh After ETL
Ships with 3 files
  • references/refresh-types.md
  • references/troubleshooting.md
  • scripts/refresh_model.py
Commands it runs
fab api -A powerbi "groups/$WS_ID/datasets/$MODEL_ID/executeQueries" \
fab api -A powerbi "groups/$WS_ID/datasets/$MODEL_ID/refreshes" \
fab api -A powerbi "groups/$WS_ID/datasets/$MODEL_ID/refreshes?\$top=1"
fab api -A powerbi "groups/$WS_ID/datasets/$MODEL_ID/refreshes/<requestId>" \
Full refresh
uv run scripts/refresh_model.py -w $WS_ID -m $MODEL_ID
Refresh specific tables
uv run scripts/refresh_model.py -w $WS_ID -m $MODEL_ID --tables Sales,Calendar
Refresh specific partitions
uv run scripts/refresh_model.py -w $WS_ID -m $MODEL_ID --partitions Sales:Sales_2024
More from power-bi-agentic-development
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About this skill
What does the refresh-semantic-model skill do?

Automatically invoke this skill whenever the user asks to refresh a semantic model or a dataset. Can also be used to manage, optimize, troubleshoot, or configure a refresh or a refresh schedule.

How do I install it?

Run `npx skills add data-goblin/power-bi-agentic-development --skill refresh-semantic-model --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From data-goblin/power-bi-agentic-development, a repository with 833 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going