ruflo and autobeat

ruflo
80
Verified
autobeat
46
Emerging
Maintenance 25/25
Adoption 10/25
Maturity 24/25
Community 21/25
Maintenance 13/25
Adoption 9/25
Maturity 24/25
Community 0/25
Stars: 31,326
Forks: 3,495
Downloads:
Commits (30d): 107
Language: TypeScript
License: MIT
Stars: 3
Forks:
Downloads: 314
Commits (30d): 0
Language: TypeScript
License: MIT
No Dependents
No risk flags

About ruflo

ruvnet/ruflo

🌊 The leading agent orchestration platform for Claude. Deploy intelligent multi-agent swarms, coordinate autonomous workflows, and build conversational AI systems. Features enterprise-grade architecture, distributed swarm intelligence, RAG integration, and native Claude Code / Codex Integration

This platform helps software development teams automate and improve complex coding tasks by orchestrating multiple AI agents. It takes your project requirements and code as input, and outputs refined code, test plans, security audits, and documentation, coordinated by specialized AI agents. This is for lead developers, engineering managers, and architects who want to leverage AI for more efficient software delivery.

software-development devops code-review test-automation software-architecture

About autobeat

dean0x/autobeat

Autonomous coding agent orchestration. Give it a goal, walk away, come back to finished work. Eval loops, multi-agent pipelines, DAG dependencies, crash-proof persistence.

Implements a meta-agent architecture where the orchestrator itself recursively uses Autobeat's primitives (persistence, delegation, eval loops, resource management) to break down goals, spawn worker agents with DAG-enforced dependencies, and retry failures with enriched context—completely autonomous, no human intervention. Integrates with any MCP-compatible coding agent (Claude, Gemini, etc.) via the Model Context Protocol, exposing four core primitives that agents can't implement themselves while delegating all domain logic (CI/CD, testing, code review, PRs) to the agent's judgment, so the framework gains capabilities automatically as models improve.

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