comp-prob-analysis

Decompose competition math problems into structured modeling plans with variables and assumptions.

1|Updated May 14, 2026
One-click install
npx skills add https://github.com/lix965996-art/MMM --skill comp-prob-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: comp-prob-analysis
Source: https://github.com/lix965996-art/MMM/tree/main/resources/app/skills/comp-prob-analysis
Command: npx skills add https://github.com/lix965996-art/MMM --skill comp-prob-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It turns competition problem statements into a structured modeling plan by decomposing sub-questions, defining variables, and outlining step-by-step approaches based on the given task text and any attached datasets.

Core Features & Use Cases

  • Problem-to-plan decomposition: Breaks the competition into top-level sub-questions and clarifies inputs, outputs, difficulty, and dependencies between them.
  • Assumption sensitivity pre-check: Identifies ambiguous wording, proposes multiple interpretations, runs quick comparative checks (typically on Question 1), and records the final chosen assumptions.
  • Modeling roadmap + visualization plan: Produces a concrete workflow including variable/symbol table, modeling strategy per sub-question, and mandatory diagram/table planning with formula- and tool-appropriate diagram types.

Quick Start

Ask the assistant to run comp-prob-analysis on your competition problem text and any available attachments to generate a complete PROBLEM_ANALYSIS.md modeling report.

Frequently Asked Questions about comp-prob-analysis

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

FAQPage Schema
How do I break down a competition math problem into a modeling plan?▼

Competition problem analysis breaks down ambiguous math modeling statements into top-level sub-questions, defining variables and outlining workflows. It requires strict assumption pre-checking and variable symbol table construction to produce a solid modeling roadmap.

What is the best way to validate assumptions in ambiguous competition problem statements?▼

Assumption validation identifies ambiguous wording in competition problems, proposes multiple interpretations, and runs quick comparative checks. This pre-checking process records final chosen assumptions to ensure your math modeling roadmap remains accurate and defensible.

How do I plan diagrams and tables for a math modeling roadmap?▼

Planning diagrams for math modeling involves creating an explicit pre-planning workflow that mandates formula- and tool-appropriate diagram types. It integrates variable and symbol tables to ensure your visualization strategy aligns directly with the defined modeling strategy per sub-question.

Can I use OCR text inputs for competition problem analysis with missing attachments?▼

Competition problem analysis supports optional extracted OCR text inputs to handle missing attachments and ambiguous problem statements. This dataset-aware approach ensures accurate formula handling and structured analysis even when original data files are unavailable.

Does competition problem analysis require specific prerequisite tools or dependencies?▼

Competition problem analysis requires no specific dependencies or components to function. It operates independently to generate a structured PROBLEM_ANALYSIS.md report by processing the provided competition problem text and any available attached datasets directly.