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jarodmeng
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mark-student-work-multi-agent

Coordinate multi-agent workflows to mark student PDFs and generate JSON artifacts.

Updated Aug 27, 2026
Search Tags:#education#pdf#multi-agent#orchestration#artifacts#grading
One-click install
npx skills add https://github.com/jarodmeng/daydreamedu-scripts --skill mark-student-work-multi-agent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mark-student-work-multi-agent
Source: https://github.com/jarodmeng/daydreamedu-scripts/tree/main/.cursor/skills_archive/mark-student-work-multi-agent
Command: npx skills add https://github.com/jarodmeng/daydreamedu-scripts --skill mark-student-work-multi-agent

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a robust orchestration layer to automate the marking of a student's completion PDF using a multi-agent architecture. It eliminates manual, error-prone grading workflows by coordinating specialized subagents to map the document structure, transcribe and grade responses, and tag taxonomy, producing a canonical JSON marking artifact and a derived markdown learning report.

Core Features & Use Cases

  • Orchestrates a Hierarchical Multi-Agent System that reads a student attempt PDF and, if available, an answer key or teacher annotations, to generate structured marking data.
  • Spawns specialized subagents for structural mapping, transcription/grading, and taxonomy tagging, then aggregates their outputs into standardized artifacts.
  • Supports both Standard (answer key) and Teacher-Annotated workflows, with clear error handling and retry boundaries; outputs are suitable for auditing, reporting, and learner diagnostics.

Quick Start

Provide the student attempt PDF path and optional answer key, then instruct the orchestrator to run the multi-agent marking workflow to produce a canonical JSON artifact and a learning report.

Frequently Asked Questions about mark-student-work-multi-agent

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

FAQPage Schema
How does multi-agent grading work for student PDF submissions?▼

Multi-agent grading uses a hierarchical orchestration architecture to read student PDFs, spawn specialized subagents to map structure and transcribe responses, and aggregate results into canonical JSON artifacts and a markdown learning report.

What's the best way to automate marking a student's PDF completion against an answer key?▼

Automating PDF marking against an answer key requires orchestrating a multi-agent workflow that maps document structure, grades transcribed responses, and tags taxonomy to output standardized JSON artifacts and a derived learning report.

Can I grade student work PDFs using teacher annotations instead of an answer key?▼

Yes, the multi-agent marking workflow supports both Standard answer key and Teacher-Annotated workflows, reading teacher annotations from the PDF to generate structured marking data and a learning report.

How do subagent failures get handled during multi-agent PDF grading orchestration?▼

Multi-agent PDF grading enforces strict orchestrator boundaries and handles subagent failures gracefully with clear error handling and retry boundaries to ensure standardized results suitable for downstream reporting.

What output formats are produced when automating student completion PDF grading?▼

Automating student PDF grading produces a canonical JSON marking artifact containing structured grading data and a derived markdown learning report suitable for auditing, reporting, and learner diagnostics.

Do I need to manually map document structure before grading a student attempt PDF?▼

No, the multi-agent orchestrator spawns a specialized subagent for structural mapping to automatically map the student attempt PDF layout before transcribing and grading the responses.

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