By meefs
Agent runtimes for ruflo — local WASM-sandboxed agents (rvagent: 10 wasm_agent_*/wasm_gallery_* MCP tools, built on @ruvector/rvagent-wasm + @ruvector/ruvllm-wasm per ADR-070) plus Anthropic Claude Managed Agents as a cloud backend (managed_agent_* MCP tools per ADR-115). One interface, local-vs-cloud runtimes.
Orchestrator that spawns nested sub-agents (up to depth=5) via Claude Code's native Task tool — for deep delegation where context isolation matters more than throughput
Leaf-worker template for nested spawn trees — performs one focused task and returns a structured summary. Deliberately does NOT have the Task tool (least-privilege boundary)
Tier-2 leaf — bottom of a queen-led tree. Deliberately no Task tool (least-privilege), but DOES record trajectory steps, AIDefence-scan its own inbound prompt, and report cost — so the queen's intelligence pipeline learns from every leaf outcome
Tier-2 recursive researcher — nested-researcher's role with HNSW pattern retrieval, AIDefence-gated web content, hive-mind consensus on which followups to pursue, and full trajectory recording
Tier-2 recursive reviewer — find-and-verify like nested-reviewer, but with hive-mind byzantine consensus on findings (replaces inline majority voting), AIDefence-screened evidence, and trajectory learning across review runs
Run an Anthropic Claude Managed Agent — a cloud agent harness (container + filesystem + tools), the cloud counterpart of the local wasm-agent runtime
Spawn nested sub-agents (agents that spawn sub-agents, up to depth=5) via Claude Code's native Task tool — for context-managed deep delegation
Create and manage sandboxed WASM agents for isolated code execution
Browse, publish, and install WASM agents from the community gallery
Uses power tools
Uses Bash, Write, or Edit tools
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Agent = Model + Harness. The model writes; the harness gives it tools, memory, loops, sandboxes, and controls so it can actually work. Ruflo is the harness — the execution layer around Claude Code and Codex that adds 100+ specialized agents, coordinated swarms, self-learning memory, federated comms across machines, and enterprise security guardrails. So agents don't just run, they collaborate.
One npx ruflo init gives Claude Code a nervous system: agents self-organize into swarms, learn from every task, remember across sessions, and — with federation — securely talk to agents on other machines without leaking data. You keep writing code. Ruflo handles the coordination.
Self-Learning / Self-Optimizing Agent Architecture
npx claudepluginhub meefs/claude-code-flow --plugin ruflo-agentExplore, compare, iterate, and export interactive UI design prototypes from the Design app.
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