roster-match

Name: roster-match
Availability: InStock
Author: shuff57

Cross-reference student IDs from PDF rosters with unstructured class data text blocks.

Updated Mar 29, 2026

Search Tags:#PDF processing #roster matching #grade extraction #class data analysis #student information system

Ready to run

npx skills add https://github.com/shuff57/agent-evo --skill roster-match

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: roster-match
Source: https://github.com/shuff57/agent-evo/tree/main/skills/roster-match
Command: npx skills add https://github.com/shuff57/agent-evo --skill roster-match

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of cross-referencing student rosters from PDFs with unstructured class data text dumps, enabling quick identification of overlapping students and extraction of grades.

Core Features & Use Cases

Roster Matching: Cross-reference student IDs from PDF sign-up rosters with unstructured class data text blocks.
Grade Extraction: Extracts grades for students who appear in both rosters.
Use Case: Ideal for educators or administrators who need to match student sign-ups with class data and extract grades for reporting purposes.

Quick Start

Use the roster-match skill to match students between the 'sign-up-rosters.pdf' and 'class-data.txt'.

Frequently Asked Questions about roster-match

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

FAQPage Schema

How do I cross-reference student rosters from a PDF with unstructured class data?▼

To cross-reference student rosters from a PDF with unstructured class data, you need a process that parses student IDs from both sources and matches overlapping entries to identify shared students.

Can I extract grades for specific students from unstructured class data text blocks?▼

Yes, you can extract grades for specific students from unstructured class data text blocks by first matching their student IDs against a sign-up roster, then pulling the associated grade information for those overlapping records.

What is the best way to handle various data formats and quirks when matching student IDs?▼

Handling various data formats and quirks during student ID matching requires an automated extraction process that normalizes inconsistent text dumps and PDF roster layouts to accurately isolate and cross-reference the correct identifiers.

Does this roster matching approach require a specific student information system to work?▼

No, this roster matching approach does not require a specific student information system because it processes raw PDF sign-up rosters and unstructured text blocks directly to identify overlapping students and extract grades.

How do I automate grade extraction for reporting purposes from a class data text dump?▼

You can automate grade extraction for reporting purposes by cross-referencing a PDF student roster with the class data text dump, matching the student IDs, and automatically pulling the grades for students present in both datasets.