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jarodmeng
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mark-goodnote-completion

Mark GoodNotes completion PDFs against DaydreamEdu templates and output JSON marking artifacts.

Updated Aug 27, 2026
Search Tags:#diagnosis#goodnotes#education-technology#learning-report#marking#json-marking
One-click install
npx skills add https://github.com/jarodmeng/daydreamedu-scripts --skill mark-goodnote-completion
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mark-goodnote-completion
Source: https://github.com/jarodmeng/daydreamedu-scripts/tree/main/.cursor/skills_archive/mark-goodnote-completion
Command: npx skills add https://github.com/jarodmeng/daydreamedu-scripts --skill mark-goodnote-completion

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables educators and learning engineers to visually grade a GoodNotes completion PDF against the DaydreamEdu template and a mapped answer-page range, producing a canonical JSON marking artifact and a derived learning report for feedback-driven instruction.

Core Features & Use Cases

  • End-to-end marking: generate marking_results JSON and learning_reports Markdown from a completed GoodNotes file.
  • Audit-ready bundle: organize per-run assets under the standardized marking asset bundle (marking_assets/<student_slug>/<subject_context>/<artifact_stem>).
  • Insightful diagnostics: attach specific diagnoses for each wrong/partial item to guide targeted learning improvements.

Quick Start

Provide a GoodNotes completion PDF path and let the system register, map to a DaydreamEdu template, and render the marking artifacts.

Frequently Asked Questions about mark-goodnote-completion

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I grade GoodNotes completion PDFs with diagnostic feedback?▼

The marking workflow generates human-readable diagnostics for each wrong or partial item by tying the specific diagnosis to the question, answer, and student response. This diagnostic feedback guides targeted learning improvements and instructional interventions.

How does automated marking generate diagnostic feedback for wrong answers?▼

The marking workflow generates human-readable diagnostics for each wrong or partial item by tying the specific diagnosis to the question, answer, and student response. This diagnostic feedback guides targeted learning improvements and instructional interventions.

Do I need a registered DaydreamEdu template to mark GoodNotes files?▼

Marking results are saved as canonical JSON artifacts under ai_study_buddy/context/marking_results/<student>/<subject_context>/, while derived learning reports are written as Markdown files under ai_study_buddy/context/learning_reports/<student>/<subject_context>/.

Where are the marking results and learning reports stored?▼

Marking results are saved as canonical JSON artifacts under ai_study_buddy/context/marking_results/<student>/<subject_context>/, while derived learning reports are written as Markdown files under ai_study_buddy/context/learning_reports/<student>/<subject_context>/.

How do I organize per-run marking assets and cropped script files?▼

The workflow requires a registered template linkage, a mapped answer-page range, and a standardized marking asset bundle to house per-run scripts. Without these prerequisites, the Skill cannot accurately map student responses or render the JSON marking artifacts.

Can I use this GoodNotes grading workflow without the marking asset bundle?▼

The workflow requires a registered template linkage, a mapped answer-page range, and a standardized marking asset bundle to house per-run scripts. Without these prerequisites, the Skill cannot accurately map student responses or render the JSON marking artifacts.

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