skills.rest
Luohaothu
LuohaothuCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

multi-execute

Coordinates multiple AI models to generate prototypes and refactor them into production implementations.

24|5|Updated Feb 8, 2026
Search Tags:#automation#orchestration#multi-model#refactor#code-review#production-grade#code-prototype
One-click install
npx skills add https://github.com/Luohaothu/everything-codex --skill multi-execute
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: multi-execute
Source: https://github.com/Luohaothu/everything-codex/tree/main/skills/multi-execute
Command: npx skills add https://github.com/Luohaothu/everything-codex --skill multi-execute

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Coordinating multi-model backends to generate initial code prototypes and refactor them into production-grade implementations reduces cycle time and accelerates delivery.

Core Features & Use Cases

  • Prototype acquisition: Retrieve provisional implementations from external models and create unified diffs for integration.
  • Refactor to production code: Transform rough prototypes into production-ready code with minimal surface changes.
  • End-to-end audit & delivery: Include external code reviews and verification steps to ensure quality and safety.
  • Context-aware orchestration: Route tasks based on model capabilities (frontend, backend, full-stack) and run in parallel where appropriate.

Quick Start

Describe the feature you want prototyped and run /multi-execute with your plan path or a direct task description.

Frequently Asked Questions about multi-execute

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

FAQPage Schema
How do I use multiple AI models to generate code prototypes and refactor them into production-grade implementations?▼

To generate production-grade implementations, you coordinate multi-model backends to retrieve provisional code prototypes and then apply minimal-risk refactoring to transform them into production-ready code.

What is multi-model orchestration for software development and when do I need it?▼

Multi-model orchestration routes planned tasks or spontaneous requirements across external AI models based on their capabilities, reducing cycle time and accelerating delivery for frontend, backend, and full-stack contexts.

How do I ensure automated verifications and external code reviews validate my AI-generated code?▼

To ensure quality and safety, the orchestration workflow runs automated verifications including lint and tests, alongside external-model reviews to audit changes and validate the refactored production-grade code.

Can I run parallel tasks across different model capabilities for full-stack prototyping?▼

Yes, context-aware orchestration routes tasks based on model capabilities and runs operations in parallel where appropriate, supporting unified diffs for integrating prototypes into full-stack contexts.

What's the best way to refactor rough AI code prototypes into production-ready code with minimal surface changes?▼

The best way to refactor rough prototypes is through minimal-risk refactoring that transforms provisional implementations into production-ready code while keeping surface changes minimal and applying automated verifications.

Related Skills

Explore More Software Engineering Skills→
tacogipstacogips

exec-impl-plan-ref

Coordinate implementation plan tasks with PROGRESS.json tracking and locking.

Community
Advanced
raineraine
126

review-panel

Coordinate parallel multi-model reviews to identify and prioritize code defects.

Community
Advanced
mehdicmehdic
21

lint-check

Run code quality linters across Python, JavaScript, Go, Ruby, and Java projects.

Community
Intermediate
agilebydesignagilebydesign
1

abd-acceptance-test-driven-development

Convert behavioral context into executable test files for the project's language and framework.

Official
Advanced