QuickClass Quiz Converter transforms Word documents, PDFs, scanned worksheets, and images into structured QuickClass homework and quiz JSON.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install quickclass-quiz-converter
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install quickclass-quiz-converter using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
QuickClass Quiz Converter is an Openclaw Skills utility for converting educational materials into QuickClass-compatible quiz data. It extracts question text, identifies single-choice, multiple-choice, and true/false formats, captures options and answers, infers difficulty, preserves explanations, and generates standardized JSON for classroom assignments.
The skill also handles image-based questions. It can extract embedded Word images, render scanned PDF pages, use visual understanding to associate diagrams with question numbers, and create a companion Word document containing labeled diagrams. This provides a practical workflow when QuickClass JSON cannot embed the original images directly.
.temp/.SINGLE_CHOICE, MULTIPLE_CHOICE, or TRUE_FALSE using wording, option structure, and answer format.A,B,C for multiple-choice, and T or F for true/false.has_image to true.convert_to_quickclass.py with teacher, grade, subject, task, quiz, input, and output metadata.Install or place the skill in the Openclaw Skills or WorkBuddy skills directory. In WorkBuddy, the typical location is ~/.workbuddy/skills/quickclass-quiz-converter. Set SKILL_DIR to the skill's actual absolute path before running commands. The workflow may also use the related docx, pdf, paddleocr-doc-parsing, and image_understanding capabilities.
Convert an intermediate question file into QuickClass JSON:
python {SKILL_DIR}/scripts/convert_to_quickclass.py \
--teacher "Teacher Name" \
--grade "Grade 3 Semester 2" \
--subject "Mathematics" \
--task-title "Understanding Circles" \
--quiz-title "Practice Questions" \
--input .temp/questions.json \
--output "teacher_grade_subject_task_title_QuickClass_homework_quiz_title.json"
Extract embedded images from a Word document:
python {SKILL_DIR}/scripts/extract_images.py \
--input "source_exam.docx" \
--output-dir .temp/images \
--mapping .temp/image_mapping.json
Render scanned PDF pages for visual analysis:
python {SKILL_DIR}/scripts/extract_images.py \
--input "scanned_exam.pdf" \
--output-dir .temp/page_images \
--render-pages
Generate a companion Word diagram document for embedded images:
python {SKILL_DIR}/scripts/generate_image_doc.py \
--mapping .temp/image_mapping.json \
--images-dir .temp/images \
--output "teacher_grade_subject_task_QuickClass_homework_quiz_diagrams.docx" \
--title "Understanding Circles Diagrams"
For scanned PDFs, add --pages-dir .temp/page_images to generate_image_doc.py. The mapping must contain crop and source_page values so the script can crop the relevant diagram from the rendered full-page image.
| Field | Format | Description |
|---|---|---|
type |
Enum | SINGLE_CHOICE, MULTIPLE_CHOICE, or TRUE_FALSE |
content |
String | Question text, including concise visual description when needed |
options |
Object | Lettered options such as A, B, C, and D; use {} for true/false questions |
answer |
String | One letter, comma-separated letters such as A,B,C, or T/F |
difficulty |
Enum | BASIC, INTERMEDIATE, ADVANCED, or EXPANDED |
score |
Number | Question score; 0 is valid for classroom homework mode |
explanation |
String or null | Answer explanation when available |
has_image |
Boolean | true when the source question contains a diagram or image; defaults to false |
id |
Generated | A CUID2-style identifier is generated automatically by the conversion script |
.temp/questions.json: normalized intermediate question array..temp/images/: extracted embedded image files such as image_1.png..temp/page_images/: high-resolution rendered scanned PDF pages such as page_1.png..temp/image_mapping.json: question-to-image association records.image_file, question_number, page, context, crop, and source_page.crop coordinates use percentages and support precise diagram extraction from full-page renders.The JSON filename follows {teacher}_{grade}_{subject}_{taskTitle}_QuickClass_homework_{quizTitle}.json. When images exist, a separate labeled Word document is generated because QuickClass JSON does not embed source images. The companion document includes the title, question-number labels, centered original or cropped diagrams, question previews, and explanatory text.
paddleocr-doc-parsing workflow.source_page support for scanned PDF pages.generate_image_doc.py.Loading
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