By Zekiog
Long-horizon goal planning, deep research orchestration, and adaptive replanning using GOAP algorithms
Recursive parallel multi-source investigator that fans out across web, memory, knowledge-graph, codebase, and ADR index to build a graph-structured dossier on a seed entity, with budget caps, de-duplication, and provenance per claim
Multi-source research specialist that gathers, cross-references, and synthesizes information with evidence grading and contradiction resolution
GOAP specialist that creates optimal action plans using A* search through state spaces, with adaptive replanning, trajectory learning, and multi-mode execution
Long-horizon objective tracker that persists progress across sessions with milestone checkpoints, drift detection, and adaptive timeline management
Orchestrate multi-phase deep research with web search, memory retrieval, pattern matching, and synthesis into structured findings
Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel
Create and execute Goal-Oriented Action Plans (GOAP) with precondition analysis, cost optimization, and adaptive replanning
Track long-horizon objectives across multiple sessions with milestone checkpoints, progress persistence, and drift detection
Synthesize research findings from memory into structured reports with evidence grading, contradiction resolution, and actionable recommendations
Uses power tools
Uses Bash, Write, or Edit tools
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Orchestrate 100+ specialized AI agents across machines, teams, and trust boundaries. Ruflo adds coordinated swarms, self-learning memory, federated comms, and enterprise security to Claude Code โ so agents don't just run, they collaborate.
Claude Flow is now Ruflo โ named by rUv, who loves Rust, flow states, and building things that feel inevitable. The "Ru" is the Ruv. The "flo" is the flow. Underneath, WASM kernels written in Rust power the policy engine, embeddings, and proof system.
One init gives Claude Code a nervous system: agents self-organize into swarms, learn from every task, remember across sessions, and โ with federation โ securely talk to agents on other machines without leaking data. You keep writing code. Ruflo handles the coordination.
Self-Learning / Self-Optimizing Agent Architecture
User --> Ruflo (CLI/MCP) --> Router --> Swarm --> Agents --> Memory --> LLM Providers
^ |
+---- Learning Loop <-------+
New to Ruflo? You don't need to learn 314 MCP tools or 26 CLI commands. After
init, just use Claude Code normally -- the hooks system automatically routes tasks, learns from successful patterns, and coordinates agents in the background.

There are two different install paths with very different surface areas. Pick based on what you need (#1744):
| Claude Code Plugin | CLI install (npx ruflo init) | |
|---|---|---|
| What it gives you | Slash commands + a few skills + agent definitions per-plugin | Full Ruflo loop โ 98 agents, 60+ commands, 30 skills, MCP server, hooks, daemon |
| Files in your workspace | Zero | .claude/, .claude-flow/, CLAUDE.md, helpers, settings |
| MCP server registered | No (memory_store, swarm_init, etc. unavailable to Claude) | Yes |
| Hooks installed | No | Yes |
| Best for | Try a single plugin's commands without committing to the full install | Production use โ everything works as documented |
# Add the marketplace
/plugin marketplace add ruvnet/ruflo
# Install core + any plugins you need
/plugin install ruflo-core@ruflo
/plugin install ruflo-swarm@ruflo
/plugin install ruflo-autopilot@ruflo
/plugin install ruflo-federation@ruflo
This adds slash commands and agent definitions only. The Ruflo MCP server is NOT registered, so memory_store, swarm_init, agent_spawn, etc. won't be callable from Claude. For the full loop, use Path B below.
| Plugin | What it does |
|---|---|
| ruflo-core | Foundation โ server, health checks, plugin discovery |
| ruflo-swarm | Coordinate multiple agents as a team |
| ruflo-autopilot | Let agents run autonomously in a loop |
| ruflo-loop-workers | Schedule background tasks on a timer |
| ruflo-workflows | Reusable multi-step task templates |
| ruflo-federation | Agents on different machines collaborate securely |
| Plugin | What it does |
|---|---|
| ruflo-agentdb | Fast vector database for agent memory |
| ruflo-rag-memory | Smart retrieval โ hybrid search, graph hops, diversity ranking |
| ruflo-rvf | Save and restore agent memory across sessions |
| ruflo-ruvector | ruvector โ GPU-accelerated search, Graph RAG, 103 tools |
| ruflo-knowledge-graph | Build and traverse entity relationship maps |
Cross-installation agent federation with zero-trust security, peer discovery, consensus-based task routing, and per-call budget circuit breaker (ADR-097)
RuVector memory with HNSW search, AgentDB, and semantic retrieval
IoT device lifecycle, telemetry anomaly detection, fleet management, and witness chain verification for Cognitum Seed hardware
Neural trading via npx neural-trader โ self-learning strategies, Rust/NAPI backtesting, 112+ MCP tools, swarm coordination, and portfolio optimization
Test gap detection, coverage analysis, and automated test generation โ drives the testgaps background worker via hooks_worker-dispatch; SPARC Refinement-phase canonical owner
npx claudepluginhub zekiog/ruflo --plugin ruflo-goalsComprehensive UI/UX design plugin for mobile (iOS, Android, React Native) and web applications with design systems, accessibility, and modern patterns
Multi-model consensus engine integrating OpenAI Codex CLI, Gemini CLI, and Claude CLI for collaborative code review and problem-solving.
Standalone image generation plugin using Nano Banana MCP server. Generates and edits images, icons, diagrams, patterns, and visual assets via Gemini image models. No Gemini CLI dependency required.
Ultra-compressed communication mode. Cuts ~75% of tokens while keeping full technical accuracy by speaking like a caveman.
Write feature specs, plan roadmaps, and synthesize user research faster. Keep stakeholders updated and stay ahead of the competitive landscape.
Curate auto-memory, promote learnings to CLAUDE.md and rules, extract proven patterns into reusable skills.