Let AI follow your rules and handle asset organization and batch processing in one click.
AI Action is a plugin for building AI-powered batch processing workflows for your images. You can have AI automatically rename images, write descriptions, add tags, sort into folders, and rate them, all in a single run.
This guide covers installation, setup, and running your first AI Action.
AI Action handles the workflow execution, but the actual image analysis is powered by AI models. The AI Models is Eagle’s unified model configuration center. Install it once, and all AI plugins share the same setup. You need to configure the AI Models before AI Action can work.
Open Eagle → “Plugins” → “Plugin Center” → search for “AI Models” → click Install.





After connecting your API Key, set the “Vision Model” under Default Models.
AI Action needs to "see" your images to analyze them, so a Vision Model is required. Without one, AI Action won’t work.
For detailed model configuration steps, see the AI Models Configuration Guide.
We recommend the Claude model family. Here’s a quick guide:
| Use Case | Recommended Model |
|---|---|
| Best results, budget is flexible | Claude Opus 4.6 |
| Balanced quality and cost | Claude Sonnet 4.6 |
| Budget-friendly, lighter tasks | Claude Haiku 4.5 |
If you’d like to run models locally using tools like LM Studio instead of cloud APIs, make sure your hardware meets the following requirements.
Running large language models requires a dedicated GPU with at least 12 GB of VRAM.
Different tasks have different model requirements:
| Use Case | Minimum Model | Recommended Model |
|---|---|---|
| AI Rename, AI Description | Qwen3 4B | Qwen3 8B |
| AI Tags, AI Folders (auto-sorting) | Qwen3 8B | Larger models |
AI Rename / AI Description These tasks are relatively simple. Qwen3 4B is usually sufficient; for better stability and quality, go with 8B.
AI Tags / AI Folders These tasks involve more complex reasoning and classification, so they require at least Qwen3 8B or larger.
If your hardware is limited, online models (e.g. Claude, OpenAI) are usually the better choice:

Let’s start with the simplest example: AI Rename.


Click “+ Add Step” to see all available operation types:
Select “Rename” for this example.
After selecting Rename, you’ll see the step’s settings panel with options for:
For your first time, keep all the defaults. Just click “Create Action” at the bottom.
You’ll be taken back to the action list, where your new AI Rename action is now visible.
Now let’s try it with some real images.
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You’ll enter the “Execute Action” confirmation screen, which shows:
You can also add extra instructions in the text box at the bottom (optional). Once everything looks good, click “Execute Action” to start.
During execution, you can watch the progress of each file in real time. When everything is done, the screen shows “Completed” with:
Click “Confirm” to close the window. Back in Eagle’s file list, you’ll see that the selected images have been renamed.
You’ve now created and run your first AI Action.
The default settings already produce good results, but Custom Instructions let you control exactly how AI generates its output. Over time, you can shape a workflow that fits your habits.

In the edit screen, scroll to the “Custom Instructions” field and enter your requirements.
For example: Name in English, using the format "Subject - Style", keep it under 15 characters.
Then click “Save”.
Select the same images again, repeat the execution steps, and compare with the previous results. You’ll notice that AI now follows your specified format, language, and style more closely.
This is the core loop of AI Action: Create → Test → Tweak Instructions → Test Again. Through this cycle, you can gradually shape AI into an assistant that fits your workflow.
If you’d rather not start from scratch, templates can get you going faster.



Templates are a good starting point. After creating one, you can always fine-tune it through “Edit” to better match your workflow.
Start with a powerful model like Claude Opus 4.6. If results are still off with a strong model, the issue is likely in your prompts or settings, not the model itself. That makes it easier to pinpoint the problem.
Once you’re happy with the results, try switching to a more cost-effective model like Claude Sonnet 4.6 or Haiku 4.5 to see if they still meet your needs.
Don’t start by running hundreds of images at once. Pick 3–5 representative images first, covering different types and complexity levels. This makes it easier to tell whether your setup works.
When adjusting, change only one variable at a time:
This way you’ll know exactly which setting made the difference.
The more specific your instructions, the more consistent the results. Be explicit about:
For example:
Prefer positive instructions. "Use English" tends to work more reliably than "Don’t use Chinese".
One practical tip: Think about how you’d search for an image later, then have AI name, describe, and tag it the same way.
For more prompting techniques, see the AI Action Best Practices Guide.
If you plan to use AI Tags or AI Folders, we recommend installing AI Search first.
AI Search builds a visual similarity index for your library. When AI Action detects this data, it uses visual similarity and your existing organization to improve tagging and sorting accuracy. Instead of analyzing each image in isolation, AI can reference how you’ve already organized similar images.


So far you’ve:
AI Action can do more than renaming. It can write descriptions, sort into folders, tag images, rate quality, and more. By combining different steps and fine-tuning your instructions, you can build a workflow that matches how you actually organize images.
💡 Want to learn how to configure more effective actions? Check out the AI Action Best Practices Guide.
Initial release