Creative Technique: Intelligent Book Breakdown

After FeelFish version 2.10.0, we support the intelligent book breakdown feature. You can upload the complete TXT content of a novel, and it will help you split chapters and extract key information based on chapter content for your reference and learning.

Step 1: Create a Novel Based on the Intelligent Book Breakdown Template Project

Click the switch project button on the left side of the novel name, then click "New Creative Project", select "Intelligent Book Breakdown Template", enter the name of the book you want to break down, and create it.

Step 2: Import Complete TXT Text

In the pop-up window, you can import the complete TXT text. Or when the chapter content is empty, you can also find the import button in the chapter content list.

After importing, it will identify the chapter numbers in the novel and split the entire TXT into independent chapters. This process may have matching errors, such as matching standalone numbers in the content as chapter numbers. You need to manually check and delete incorrect matches.

If there are matching issues, please provide feedback. We will check if it's a text format we haven't recognized.

Step 3: Extract Novel Content Based on Intelligent Context Feature

The principle of intelligent book breakdown is actually implemented based on FeelFish's intelligent context feature. Essentially, it identifies novel chapters in batches and relies on AI to extract novel content.

You can create multiple intelligent contexts and extract different information according to your needs. Each intelligent context can have its own prompt, and FeelFish will extract novel information based on the corresponding intelligent context's prompt.

About Credit Consumption

Credit consumption is the same as FeelFish's intelligent context feature, both calculated based on the number of AI request tokens. You can choose the model you want to use for book breakdown. If we calculate based on DeepSeek V3.2 (28 credits per input token), roughly two Chinese characters correspond to one token. One million characters correspond to 500K tokens. If only considering novel content input, it requires 14 million credits. Adding the final output and the intelligent context results from the previous batch each time, the total consumption should be around 20 million credits.

If you create multiple intelligent contexts, the repeatedly read novel content within a certain time period is cached and only requires one-tenth of the credits. So overall, creating three or four intelligent contexts, the credit consumption should be within 50 million (equivalent to one-sixth of a premium membership, actual consumption may vary). We recommend analyzing a few chapters first to see how effective it is, then adjust your prompts before running the full batch.

Additionally, you can use AI in intelligent agents to help analyze individual chapters based on existing chapter content.

In summary, FeelFish's intelligent book breakdown feature is very flexible and powerful. You can explore it well~