> ## Documentation Index
> Fetch the complete documentation index at: https://docs.learnterms.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Question Studio

> Generate questions from source material and send them into the right LearnTerms module.

## What Question Studio does

Question Studio is the generation surface for admins and contributors. It lets you choose a semester, class, and module, pull source material from the Content Library, generate questions with a LearnTerms model, review the output, and bulk insert selected questions into the chosen module.

It is not a free-form chatbot. It is a structured generation workflow.

## Destination comes first

The first part of the screen asks you to choose where generated questions should go:

1. Semester
2. Class
3. Module

This ordering matters because LearnTerms generation is not useful without a destination. The app is designed to place generated questions directly into a module, not leave them floating in a detached draft space.

## Source material selection

Question Studio works with selected text. In practice, that usually comes from chunks in the Content Library.

The built-in document browser lets you:

* browse cohort-scoped documents
* search by title
* open a document
* select chunk text to feed into generation

The selected text is then summarized into character and word counts on the generation panel.

## Generation controls

Current generation controls include:

* product model selection
* question count of `5`, `10`, or `15`
* optional custom prompt

The product-facing model options currently are:

* `swift-general`
* `swift-optometry`
* `swift-pharmacy`

All of them currently resolve to the same underlying model with different focus settings. The product docs should explain the product meaning, not just the backend mapping.

## Source-text quality

The generation panel explicitly tracks character count and gives rough quality feedback based on the amount of selected text.

Current behavior treats:

* empty text as unusable
* very short text as low quality
* very large text as over the preferred cap

The current soft cap shown in the component is `3500` characters.

This is worth documenting because a lot of “bad generation” is actually a source-material problem.

## Reviewing generated output

After generation, the user can:

* inspect the generated questions
* select which ones to keep
* remove individual questions
* discard the whole batch
* regenerate from the same source
* add only selected questions to the destination module

This review step is important. Generated output is meant to accelerate authoring, not replace editorial judgment.

## Limits and errors

Question generation can fail for several operational reasons:

* no destination module is selected
* no source material is selected
* usage limits are reached
* module limits are reached when saving

The UI distinguishes between ordinary errors and daily-limit style errors, which is useful to explain in contributor docs.

## Recommended workflow

1. Clean the source chunks first
2. Choose the exact destination module
3. Pick the model that matches the subject matter
4. Generate a smaller batch first
5. Select only the questions worth keeping
6. Edit weak questions after insertion rather than accepting them blindly