Contestant-scale code simplification

SkillAI & models

Contestant-scale code simplification. Simplify unnecessary engineering structure while preserving mathematical/numerical behavior; any executable hash change requires result/evaluator regression.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Contestant-scale code simplification skill

What this skill tells your AI

The instructions your AI receives, as published by mantou6666/math-modeling-agent-flow in math-modeling-finalizer/skills/modeling-behavior-refactor/SKILL.md and read by ahel’s review.

Compare baseline and current executable hashes. Simplify only unnecessary engineering structure. Preserve mathematical kernels, formal evaluator, numerical stability and performance-critical vectorization. After changes, compare official Result IDs/values, feasibility, key intermediates and independent evaluator outputs within declared tolerance. No freeze/state-machine dependency is required.

Signals

GitHub stars
22
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
modeling-behavior-refactor
Source
github.com/mantou6666/math-modeling-agent-flow