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code-dispatcher

Execute multi-backend AI code tasks with DAG scheduling and session resume.

7|1|Updated Jan 19, 2026
Search Tags:#workflow automation#code generation#parallel execution#code refactoring#ai coding#multi-backend
One-click install
npx skills add https://github.com/makoMakoGo/code-dispatcher-toolkit --skill code-dispatcher
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-dispatcher
Source: https://github.com/makoMakoGo/code-dispatcher-toolkit/tree/main/skills/code-dispatcher
Command: npx skills add https://github.com/makoMakoGo/code-dispatcher-toolkit --skill code-dispatcher

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines complex coding tasks by intelligently routing them to the most suitable AI backend (Codex, Claude, or Gemini), managing parallel execution, and enabling session resumption for continuity.

Core Features & Use Cases

  • Multi-Backend Support: Seamlessly integrates with Codex, Claude, and Gemini.
  • Parallel Execution: Run multiple tasks concurrently, with optional DAG scheduling for complex workflows.
  • Session Resume: Continue previous tasks without losing context.
  • Use Case: Refactor a large codebase by analyzing modules with Codex, documenting the changes with Claude, and generating UI components with Gemini, all within a single, orchestrated workflow.

Quick Start

Execute a simple task using the code-dispatcher skill with the codex backend.

Frequently Asked Questions about code-dispatcher

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

FAQPage Schema
How do I run parallel AI code generation tasks across multiple backends?▼

Large-scale code refactoring across multiple AI backends is managed by routing specific modules to pluggable interfaces like Codex, Claude, or Gemini. This orchestrated workflow handles complex code analysis and automated code generation concurrently using DAG scheduling.

Can I resume an interrupted AI coding session without losing context?▼

Yes, you can resume an interrupted AI coding session without losing context. The dispatcher supports session resume functionality, allowing you to continue previous complex refactoring or code generation tasks exactly where they stopped.

What is the best way to orchestrate a complex codebase refactoring workflow with different AI models?▼

The best way to orchestrate complex codebase refactoring with different AI models is using DAG scheduling for parallel task execution. This approach analyzes modules with Codex, documents changes with Claude, and generates UI components with Gemini centrally.

Does multi-backend AI coding support configurable security controls for automated code generation?▼

Yes, multi-backend AI coding supports configurable security controls during automated code generation. The dispatcher manages backend selection with configurable security parameters to ensure safe execution of complex code analysis and refactoring tasks.

How does DAG scheduling work for parallel code generation tasks?▼

DAG scheduling for parallel code generation works by mapping task dependencies into a directed acyclic graph to manage execution order. This allows the dispatcher to run multiple concurrent operations across selected backends and output structured results.

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