model-creator

Generate and rank 5-8 modeling plans for math competition problems.

1|Updated Apr 2, 2026
One-click install
npx skills add https://github.com/Best6668/AMIS --skill model-creator-best6668
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: model-creator
Source: https://github.com/Best6668/AMIS/tree/main/skills/model-creator
Command: npx skills add https://github.com/Best6668/AMIS --skill model-creator-best6668

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generate and rank modeling plans for math modeling competition problems, enabling structured solution discovery and efficient planning.

Core Features & Use Cases

  • Automated generation of multiple modeling approaches and evaluation criteria tailored to competition problems.
  • Prioritized sequencing of approaches with feasibility indicators for quick decision-making.
  • Integration with /problem-analysis, /feasibility-check, and /model-review workflows to form an end-to-end pipeline.

Quick Start

Provide a complete competition problem description and any data attachments, then request 5-8 candidate modeling plans ranked by feasibility and impact.

Frequently Asked Questions about model-creator

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

FAQPage Schema
How do I generate and rank modeling plans for math modeling competitions?▼

To generate and rank modeling plans, provide a complete competition problem description with data attachments to receive 5-8 candidate modeling approaches prioritized by feasibility and impact.

What is the best way to structure solution discovery for math modeling problems?▼

The best way to structure solution discovery is using automated generation of multiple modeling approaches with evaluation criteria, delivering a prioritized list with feasibility signals and risk assessments.

How many candidate modeling approaches can I expect for a single competition problem?▼

You can expect 5-8 candidate plans generated from the problem description, sequenced with feasibility indicators for quick decision-making during competitions.

When should I not use automated ranking for competition modeling plans?▼

Automated ranking is not suitable for problems lacking defined data, constraints, or structured subproblems, as it requires clear inputs to propose and evaluate candidate modeling approaches.