Entwickler-Tools
artemis
ARTEMIS turns natural-language instructions into reliable Android automation. It automates end-to-end workflows, captures logs, and integrates seamlessly wit…
★ 10,9 Tsd. SterneApache-2.0
Anleitung ansehen →promptscript ist ein Open-Source-Projekt aus der Kategorie Entwickler-Tools von mrwogu (mrwogu/promptscript auf GitHub). Es hat 386 Sterne auf GitHub und 3 Forks, wird unter der Lizenz MIT veröffentlicht und wurde zuletzt am 1. Oktober 2026 auf GitHub aktualisiert.
Prompt-as-code for enterprises — version, audit and deploy AI instructions.
Author instructions in versioned files.
Prompts go through the same gates as code.
Ship approved prompts to every AI coding tool.
Track which prompts ran where.
Instructions live in version control.
Know who approved what and when.
Deploy to any AI coding assistant.
One prompt library for the org.
Revert bad prompt changes fast.
Built for governance and compliance.
Download the source and move into the project folder.
git clone https://github.com/mrwogu/promptscript.git
cd promptscriptEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandMIT licensed — commercial use allowed with attribution.
Any AI coding assistant — check the README for integrations.
For review, versioning, rollback, and audit — the same reasons as code.
Its design targets enterprises; solo users may prefer simpler setups.
Check the docs for the deployment mechanism per assistant.
ARTEMIS turns natural-language instructions into reliable Android automation. It automates end-to-end workflows, captures logs, and integrates seamlessly wit…
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Die anderen Projekte der Kategorie Entwickler-Tools mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls promptscript nicht das Richtige ist.
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Verwandte Projekte der Kategorie Entwickler-Tools im Katalog, die promptscript bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
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Model-agnostic security rules for AI coding workflows — secure by default.
Open-source security framework for AI coding agents — secure by default.
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.