oc-modularize-ops

Decompose monolithic codebases into modular components using real-world data.

Updated May 15, 2026
One-click install
npx skills add https://github.com/asfbay-bit/opchain-skills --skill oc-modularize-ops
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: oc-modularize-ops
Source: https://github.com/asfbay-bit/opchain-skills/tree/main/skills/oc-modularize-ops
Command: npx skills add https://github.com/asfbay-bit/opchain-skills --skill oc-modularize-ops

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps decompose monolithic codebases into modular components without losing functionality or data, using real-world data to prove equivalence.

Core Features & Use Cases

  • Monolith Decomposition: Decide whether to decompose a monolith and plan the decomposition process.
  • Golden Fixtures: Capture real data from every boundary to serve as an equivalence oracle.
  • Parallel-Copy Strategy: Implement parallel-copy strategy for minimal disruption.
  • Strangler-Fig Strategy: Gradually extract modules using the strangler-fig approach.
  • Code Move and Cutover: Delegate the actual code move and cutover to oc-migration-ops.
  • Use Case: Decompose a monolithic web application into microservices for better scalability and maintainability.

Quick Start

Use the oc-modularize-ops skill to assess the modularization fitness of a monolithic application.

Frequently Asked Questions about oc-modularize-ops

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

FAQPage Schema
How do I decompose a monolithic codebase into modules without losing functionality?

Decompose a monolithic codebase by analyzing system boundaries, deciding on a modularization strategy, and capturing real data from every boundary as a golden fixture to prove zero loss of functionality or data.

What is the strangler-fig approach for monolith decomposition?

The strangler-fig approach gradually extracts modules from a monolithic application, allowing incremental modularization with minimal disruption while proving equivalence through captured real-world boundary data.

How do I prove zero data loss when splitting a monolith into microservices?

Capture real data from every system boundary to serve as a golden fixture equivalence oracle, verifying that the modularized components maintain exact functional and data parity with the original monolith.

When should I use a parallel-copy strategy versus the strangler-fig pattern for microservices migration?

Use the parallel-copy strategy for minimal disruption during monolith decomposition, or choose the strangler-fig pattern to gradually extract modules when a phased, incremental cutover is preferred.

Can I use this skill to assess if my monolithic application is ready for modularization?

Yes, you can assess the modularization fitness of a complex monolithic application by analyzing its system boundaries and evaluating whether decomposition into modular components is viable.

What happens after the modularization strategy is decided and code is ready to move?

After deciding the modularization strategy, the actual code move and cutover is delegated to the migration operations phase, completing the transition from a monolith to modular components.