Prompt Optimizer: Open-Source Free AI Prompt Optimizer 136

Prompt Optimizer is a free and open-source AI prompt optimization tool, created by linshenkx, and has already accumulated over 31k Stars on GitHub. Unlike common prompt optimization tools that just help you polish a few sentences, it turns prompt engineering into a complete workflow — covering everything from optimization, testing, and evaluation to version management — and supports deployment across Web, plugins, and Docker.

Basic Information:

• Open-source license: AGPL-3.0

• Repository: linshenkx/prompt-optimizer

• Available forms: Web version, desktop, Chrome extension, Docker, MCP

• Online experience URL: https://prompt.always200.com

Prompt Optimizer Core Features

• Smart optimization: Trigger the optimization process with one click, supporting multi-round iteration. Users can handle system prompts and user prompts separately, and the optimization process strives to preserve the original meaning while improving expression and structure.

• Comparison testing: Prompts before and after optimization can be compared side by side, with testing tools on the right that can run both versions simultaneously, making differences clear at a glance.

• Multi-model integration: Connected to mainstream models such as OpenAI (GPT-3.5, GPT-4, GPT-4o), Google Gemini, DeepSeek, Zhipu GLM-4, SiliconFlow, and more. Each model allows individual adjustment of parameters like temperature and max_tokens.

• Covers four types of prompts

• system/user single prompt: Optimize role settings, rule descriptions, and output format

• Variable templates: Set topic, tone, and role as variables for unified validation

• Multi-message context: system instructions, user input, and context collectively affect the result

• Text-to-image / image-to-image / multi-image: Image generation scenarios, supporting multi-image input and style transfer

• Version management and asset accumulation: Save historical versions, add examples, and record source information. Features like favorites and version history are all available — well-optimized prompts can be reused repeatedly without rewriting each time.

• Privacy handling: All processing is done locally in the browser, and data connects directly to AI service providers without going through any additional servers. API keys and history records are encrypted and stored locally, and will not be uploaded.

Prompt Optimizer Use Cases

• People who use AI frequently on a daily basis: If you interact with models like ChatGPT, Claude, and Gemini every day, optimizing your prompts can stabilize the quality of your output significantly.

• Prompt engineering or AI product development: System prompts and user instructions directly affect product performance and require repeated testing and iteration. Prompt Optimizer's multi-result comparison feature is very useful in this situation.

• Content writers: Titles, scripts, Xiaohongshu copy, WeChat official account articles, image generation prompts — any scenario requiring repeated input adjustments is applicable.

• Building AI tools within a team: Useful prompts can be accumulated to form the team's own prompt library.

• Data-sensitive businesses: Since it's an open-source project, it can be deployed locally, and data never leaves the internal network.

Prompt Optimizer Pros and Cons

Pros

• Privacy guaranteed: Pure frontend architecture with no backend relay, API keys stored locally

• Fully open code: AGPL-3.0 license, allowing self-audit of the code

• Flexible deployment: Web, desktop, Chrome extension, Docker, MCP all supported

• Wide model selection: All mainstream models are supported, and custom interfaces can also be connected

• Complete workflow: Not just optimization — testing, comparison, and version management are all included

• No hidden fees: Open-source and free, you only pay for your own API calls

• Easy to get started: Clean interface, basically works out of the box

Cons

• You need to prepare your own API keys: The tool itself does not provide model capabilities

• Optimization of variable prompts is unstable: When the context is complex, it may misinterpret the meaning

• Lack of automated evaluation metrics: No leaderboard or provably optimal solution

• Self-hosting has a learning curve: Deploying with Docker or Vercel requires some technical background

• Optimization logic is opaque: Limited public information on the internal optimization process

How to Use Prompt Optimizer

Online Version

Simply open https://prompt.always200.com, paste the prompt to be optimized in the left input box, select whether it's a system prompt or a user prompt, configure your API key, and click optimize. On the right, you can compare the output results before and after optimization.

Chrome Extension

Install from the Chrome Web Store

Docker Deployment

docker run -d -p 80:80 --restart unless-stopped --name prompt-optimizer linshen/prompt-optimizer

If you need to configure an API key:

docker run -d -p 80:80 -e VITE_OPENAI_API_KEY=your_key --restart unless-stopped --name prompt-optimizer linshen/prompt-optimizer

Configure API Key

Click the ⚙️ Settings icon in the top right → Model Management → Select the model you want to use → Enter the API key → Save.

Prompt Optimizer vs. Other Competitors

Why Choose Prompt Optimizer

• Privacy-first: The entire process runs locally, with data never passing through third-party servers — this is the biggest difference from cloud-based tools.

• Complete workflow: From optimization to testing to version management, it's an end-to-end pipeline. Prompts can be saved and reused, not treated as one-off consumables.

• Open-source & free: AGPL-3.0 license — self-host or fork for your own development, with no pricing traps.

• Flexible deployment: Covers web version, self-hosting, plugins, and MCP.

• Model freedom: Supports all mainstream models, and can also connect to custom endpoints like local Ollama.

• Active community: 31k+ Stars on GitHub, with relatively frequent updates.

Frequently Asked Questions about Prompt Optimizer

Does Prompt Optimizer cost anything?

No. It's released under the AGPL-3.0 open-source license and is completely free. However, you'll need to pay for the model API calls yourself.

Is the data secure?

Yes. Everything is processed locally in the browser and is not uploaded to any server. API keys are also stored with local encryption.

Which models are supported?

OpenAI, Google Gemini, DeepSeek, Zhipu GLM-4, SiliconFlow, and any endpoint compatible with the OpenAI format.

Can I use it without an API key?

No. The tool itself doesn't provide model capabilities — you need to configure your own key. If you just want to try it out, Gemini offers a daily free quota.

Can it optimize image-generation prompts?

Yes. Text-to-image, image-to-image, and multi-image input are all supported, and you can compare prompt effects using actual generated images.

What's the difference between Prompt Optimizer and asking ChatGPT directly to rewrite a prompt?

Prompt Optimizer provides systematic testing and version management, not a one-off conversational polish. It supports A/B comparison, records input/output samples, and makes it easy to reuse and review later.

Do I need to register an account?

No. The online version is ready to use as soon as you open it, with all data stored in your local browser.