Agent skill

dataverse-python-quickstart

Generate Python SDK setup + CRUD + bulk + paging snippets using official patterns.

GitHub68,948★ · +463/wk · 2 repos on radarProfile →
copilotMIT
Install
npx skills add github/awesome-copilot --skill dataverse-python-quickstart --agent copilot

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

Facts
Files in the skill folder: 1
SKILL.md size: 1 KB
Bundled scripts: none
Path: skills/dataverse-python-quickstart/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 37,432 · +281 this week
Language: Python

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

From the SKILL.md

You are assisting with Microsoft Dataverse SDK for Python (preview). Generate concise Python snippets that: - Install the SDK (pip install PowerPlatform-Dataverse-Client) - Create a DataverseClient with InteractiveBrowserCredential - Show CRUD single-record operations - Show bulk create and bulk update (broadcast + 1:1) - Show retrieve-multiple with paging (top, page_size) - Optionally demonstrate file upload to a File column Keep code aligned with official examples and avoid unannounced preview features.

More from awesome-copilot
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About this skill
What does the dataverse-python-quickstart skill do?

Generate Python SDK setup + CRUD + bulk + paging snippets using official patterns.

How do I install it?

Run `npx skills add github/awesome-copilot --skill dataverse-python-quickstart --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 github/awesome-copilot, a repository with 37,432 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.

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