{"id":"ruflo","name":"Ruflo","homepage":"https://github.com/ruvnet/ruflo","repo_url":"https://github.com/ruvnet/ruflo","category":"agent-orchestration","subcategories":["multi-agent","swarm-ai","claude-code-extension"],"tags":["multi-agent","swarm","orchestration","claude-code","mcp","rust","wasm","vector-search","reinforcement-learning"],"what_it_does":"A production-grade multi-agent orchestration platform built on Rust/WebAssembly that deploys coordinated swarms of 60+ specialized AI agents within Claude Code, with persistent memory, cost optimization, and Byzantine fault-tolerant consensus.","use_cases":["Orchestrate specialized coding agent swarms for large-scale software engineering (generation, testing, review, security audit)","Reduce Claude API token usage 30-50% via intelligent caching, compression, and WASM-based transforms","Run parallel agent topologies (hierarchical, mesh, ring) for complex multi-perspective code analysis","Automate DevOps and CI/CD pipelines with coordinated AI workers","Build self-improving workflows that learn from past execution outcomes using reinforcement learning"],"not_for":["Simple single-task Claude Code usage that doesn't need multi-agent coordination","Teams not using Claude Code as their primary AI coding environment","Projects requiring auditability where agent decision chains must be fully transparent"],"best_when":"You are running complex software projects inside Claude Code and want to parallelize work across specialized agents while reducing token costs and maintaining persistent cross-session memory.","avoid_when":"Your tasks are simple enough for a single LLM call; the orchestration overhead and complexity outweigh benefits for small projects.","alternatives":["claude-flow","CrewAI","AutoGen","LangGraph","Swarm (OpenAI)"],"af_score":66.2,"security_score":65.0,"reliability_score":null,"package_type":"mcp_server","discovery_source":["github"],"priority":"low","status":"evaluated","version_evaluated":"latest","last_evaluated":"2026-03-01T09:50:06.154625+00:00","performance":{"latency_p50_ms":null,"latency_p99_ms":null,"uptime_sla_percent":null,"rate_limits":null,"data_source":"llm_estimated","measured_on":null}}