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V3 Deep Integration

Integrate claude-flow with agentic-flow@alpha via an adapter-layer and phased migration.

Updated Feb 24, 2026
Search Tags:#performance optimization#MCP tools#system migration#code deduplication#agentic integration#SONA learning#AgentDB memory
One-click install
npx skills add https://github.com/FrekiManagarm/dunlo --skill v3-deep-integration-frekimanagarm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: V3 Deep Integration
Source: https://github.com/FrekiManagarm/dunlo/tree/main/.claude/skills/v3-integration-deep
Command: npx skills add https://github.com/FrekiManagarm/dunlo --skill v3-deep-integration-frekimanagarm

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Massive duplication and parallel implementations across claude-flow and agentic-flow@alpha make maintenance slow and inconsistent while blocking performance and feature parity.

Core Features & Use Cases

  • Deep adapter-layer integration: Replaces parallel system components (coordinators, managers, schedulers) with a specialized extension of agentic-flow@alpha to sharply reduce code size.
  • Feature-parity integration targets: Integrates SONA learning modes, Flash Attention performance improvements, and AgentDB cross-agent memory/search coordination.
  • MCP tools and hooks wiring: Enables Claude/MCP tooling by leveraging available pre-built MCP tools and configuring multiple hook types for consistent task behavior.
  • Migration with backward compatibility: Supports phased migration (adapter, system migration, cleanup) including dual operation and gradual feature migration to keep v2 functionality intact.

Quick Start

Ask the AI to produce the v3 adapter-layer and phased migration plan that reduces claude-flow duplication by replacing SwarmCoordinator, AgentManager, and TaskScheduler with agentic-flow@alpha equivalents.

Frequently Asked Questions about V3 Deep Integration

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

FAQPage Schema
How do I reduce duplicated orchestration code when migrating agent systems?▼

Reduce duplicated orchestration code by integrating claude-flow with agentic-flow@alpha through a dedicated adapter-layer. This replaces parallel system components like SwarmCoordinator and AgentManager to drastically reduce code size and maintenance overhead.

What is the best way to integrate SONA learning modes and Flash Attention performance tuning?▼

Integrate SONA learning modes and Flash Attention tuning by targeting feature-parity during your agent system migration. This approach ensures performance improvements and cross-agent memory coordination are properly wired into the new unified architecture.

Can I migrate claude-flow to agentic-flow@alpha while keeping v2 functionality intact?▼

Yes, you can migrate claude-flow while keeping v2 functionality intact by using a phased migration approach. This supports dual operation and gradual feature migration through adapter, system migration, and cleanup phases for backward compatibility.

How do I configure MCP tools and hooks for consistent agent task behavior?▼

Configure MCP tools and hooks by leveraging pre-built MCP tools and setting up multiple hook types during your agent system integration. This ensures consistent task behavior across the newly unified agentic-flow@alpha architecture.

What orchestration code cleanup targets should I set during an agent system migration?▼

Set explicit code cleanup targets to reduce your orchestration codebase to under 5,000 lines. Achieve this by replacing parallel coordinators, managers, and schedulers with agentic-flow@alpha equivalents during the final migration phase.

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