onton

Decompose large codebase changes into ordered patches for parallel AI execution.

10|4|Updated Mar 15, 2026
One-click install
npx skills add https://github.com/flowglad/onton --skill onton
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: onton
Source: https://github.com/flowglad/onton/tree/main/skills/write-gameplan
Command: npx skills add https://github.com/flowglad/onton --skill onton

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Managing large-scale codebase modifications is challenging due to complexity, dependencies, and risks, making review and merging difficult.

Core Features & Use Cases

  • Change Decomposition: Break down extensive code changes into small, ordered patches with formal specifications.
  • Parallel Execution: Coordinate AI agents to implement patches concurrently based on dependency graphs.
  • Workflow Automation: Automate code reviews, CI integration, rebasing, and merging processes to streamline large project updates.
  • Use Case: When refactoring a monolithic app, generate a structured plan that reduces review effort and mitigates merge conflicts with formal specs.

Quick Start

Use the onton tool to generate a structured plan for your upcoming large change by defining specifications and dependencies beforehand.

Frequently Asked Questions about onton

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

FAQPage Schema
How do I orchestrate large-scale codebase changes using AI agents?▼

You orchestrate large-scale codebase changes by decomposing them into small, formally specified patches executed by AI agents. This approach manages complexity by coordinating dependency-aware parallel execution and automating review cycles.

What is the best way to automate code reviews for complex refactoring?▼

The best way to automate code reviews for complex refactoring is by generating a structured plan that breaks down modifications into ordered patches. This workflow automation integrates CI, rebasing, and merging to reduce review effort.

How do I break down extensive code modifications into manageable patches?▼

You break down extensive code modifications into manageable patches by defining structured specifications and dependencies beforehand. This change decomposition generates a formal plan that mitigates merge conflicts and ensures ordered execution.

Can I coordinate parallel execution of code patches based on a dependency graph?▼

Yes, you can coordinate parallel execution of code patches based on a dependency graph. By defining formal dependencies beforehand, AI agents implement patches concurrently while ensuring dependency-aware execution.

Do I need formal specifications to automate complex deployment scenarios?▼

Yes, you need formal specifications to automate complex deployment scenarios. Structured specifications are required to decompose extensive code changes into ordered patches, ensuring dependency-aware execution and automated review cycles.

When should I not use AI-driven patches for refactoring a monolithic app?▼

You should not use AI-driven patches for refactoring a monolithic app when you cannot define structured specifications and formal dependencies beforehand. Without these inputs, generating a dependency-aware structured plan is not possible.