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prompt-optimizerは、linshenkxが公開しているオープンソースの生産性プロジェクトです(GitHub: linshenkx/prompt-optimizer)。GitHubスターは36,898、フォークは4,233で、AGPL-3.0ライセンスの下で公開されています。GitHubでの最終更新は2026年9月24日です。
Optimize, test and compare AI prompts — web app, desktop app, Chrome extension and Docker
Decide what you want to achieve with prompt-optimizer and check the README on GitHub for requirements before installing.
Clone the repository from GitHub (or take the packaged install route in step 3 if the README offers one).
Follow the project's documented install commands — the Run section below lists the exact ones — and add any required API keys or models.
Work through the README's quickstart example end to end, then adapt it to your own project or data.
Rewrites your draft prompt into a clearer, more effective version using your chosen LLM.
Run original vs. optimized prompts and compare model outputs side by side, including an advanced testing mode.
Includes a dedicated mode for optimizing prompts for image-generation models.
Save, organize and reuse your best prompts with smart favorites.
Use the hosted web version, self-host with Docker or Docker Compose, install the desktop app, or add the Chrome extension.
The Docker deployment supports API-key configuration and basic-auth password protection via environment variables.
Get the source if you plan to self-host with Docker Compose or develop it.
git clone https://github.com/linshenkx/prompt-optimizer.git
cd prompt-optimizerStart the published image; the web UI serves on port 8081.
docker run -d -p 8081:80 --restart unless-stopped --name prompt-optimizer linshen/prompt-optimizerOpen http://localhost:8081, add your LLM API key in settings, paste a draft prompt and run an optimization.
# configure your model/API key in the app settings at http://localhost:8081prompt-optimizer is maintained by the linshenkx organization/account on GitHub, together with open-source contributors, in the public repository linshenkx/prompt-optimizer.
Yes — the code is open source under the AGPL-3.0 license. You can use, modify and redistribute it under that license's terms.
The tool itself is free and open source (AGPL-3.0), but optimization calls use an LLM — you supply your own provider API key, or use a compatible local endpoint if configured.
Instead of trial-and-error editing in a chat window, Prompt Optimizer gives you structured optimization, side-by-side testing and a saved prompt library in one tool.
Clone the repository from GitHub, follow the install commands in the Run section (taken from the project's README), and complete the documented quickstart example before adapting it to your own use case.
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