problem-parser

Name: problem-parser
Availability: InStock
Author: echo-ice

Parse mathematical modeling problems into structured specifications with goals, constraints, and outputs.

Updated Jul 6, 2026

Search Tags:#text extraction #NLP #mathematical modeling #problem parsing #structured information

Ready to run

npx skills add https://github.com/echo-ice/mathmodeling-ssl --skill problem-parser-echo-ice

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: problem-parser
Source: https://github.com/echo-ice/mathmodeling-ssl/tree/main/.codex/skills/problem-parser
Command: npx skills add https://github.com/echo-ice/mathmodeling-ssl --skill problem-parser-echo-ice

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill automates the parsing of mathematical modeling problems, extracting structured information for efficient analysis and modeling.

Core Features & Use Cases

Automated Problem Parsing: Extracts goals, objects, constraints, data, outputs, and subquestions from raw problem statements.
Use Case: With a complex mathematical modeling problem, this Skill can quickly convert the problem into a structured format for further analysis, saving time on manual parsing.

Quick Start

Run the problem-parser skill on the new problem statement 'contest-problem.pdf'.

Frequently Asked Questions about problem-parser

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

FAQPage Schema

How do I extract structured information from mathematical modeling problems?▼

You can parse mathematical modeling problems by running an automated text extraction tool that identifies goals, objects, constraints, data, outputs, and subquestions from raw statements, converting them into structured specifications for analysis.

Can I parse mathematical modeling problems directly from a PDF file?▼

Yes, you can parse mathematical modeling problems directly from PDF content. The skill processes PDF files to extract natural language text and structures it into goals, constraints, and subquestions without requiring manual transcription beforehand.

What is problem parsing for mathematical modeling and when do I need it?▼

Problem parsing for mathematical modeling is the process of using natural language processing to extract structured specifications from complex problem statements. You need it when preparing for analysis and modeling to save time on manual text breakdown.

Do I need natural language processing capabilities to extract constraints and goals from problem statements?▼

Yes, extracting constraints, goals, and objects from problem statements requires natural language processing and parsing capabilities to accurately interpret raw text and format it into structured specifications for mathematical modeling.

What's the best way to convert raw text into structured specifications for mathematical modeling?▼

The best way to convert raw text into structured specifications for mathematical modeling is using automated problem parsing, which leverages NLP to extract and categorize goals, objects, constraints, data, and outputs efficiently.

What are the limitations of automated problem parsing for complex mathematical modeling texts?▼

Limitations of automated problem parsing include its reliance on natural language processing accuracy, meaning highly ambiguous or unstructured mathematical modeling texts may result in incomplete extraction of constraints or subquestions.