equinor/neqsim/paperlab-exam-alignment

Skill: PaperLab Exam Alignment

Purpose

Check whether a PaperLab course book prepares students for the associated exercises and exams. Use this when a book has source folders with exams, exercise PDFs, review chapters, learning objectives, or end-of-chapter questions.

Inputs

• source_manifest.json or a source root containing exams/ and exercises/.
• Chapter markdown files with learning objectives and exercise sections.
• Review/exam-preparation chapters.
• Optional extracted exam text from paperlab-source-pdf-to-html or OCR.

Workflow

1. Run book-source-inventory for source traceability.
2. Run python paperflow.py book-exam-alignment <book_dir>.
3. Review exam_alignment.md for topics marked needs-review.
4. For each weak topic, add a worked example, a self-test prompt, or a Chapter 26

review item.

1. If exam PDF text is available, rerun with extracted text and update the topic

matrix with evidence from actual problem statements.

Output

• exam_alignment.json
• exam_alignment.md

Topic Matrix

At minimum, map:

• field-development framing,
• PVT and flow performance,
• processing and separation,
• subsea, wells, and SURF,
• economics and scheduling,
• optimization and uncertainty,
• regulation and standards,
• CCS and gas quality.

Safety Rules

• Do not reproduce confidential or copyrighted exam text unless allowed.
• Use topic frequencies and paraphrased problem types for public reports.
• Mark results as needs-review when source PDFs have not been OCR/extracted.
• Keep Chapter 26 concise; use cross-references to detailed worked examples in

earlier chapters.