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Run Ruflo background workers using Claude Code native /loop scheduling
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
Author a workflow — either an MCP workflow template (persisted, lifecycle) or a native .claude/workflows/*.js orchestration script (agent/parallel/pipeline fan-out)
Run a workflow — drive an MCP workflow lifecycle (execute/pause/resume/cancel) or invoke + resume a native .claude/workflows/*.js orchestration via the Workflow tool
Side-by-side comparison of ruflo vs HAL vs other GAIA harnesses — capability gaps, design decisions, and improvement roadmap
Diagnose why a GAIA question failed — extract trace, classify failure mode, and propose a fix
Walk through a complete GAIA benchmark→submit flow — from key resolution through HAL-compatible package generation
| name | loop-worker |
| description | Run Ruflo background workers using Claude Code native /loop scheduling |
| argument-hint | <worker-name> |
| allowed-tools | Bash(npx *) mcp__claude-flow__hooks_worker-dispatch mcp__claude-flow__hooks_worker-status ScheduleWakeup |
Use /loop for in-session periodic workers. Cache-aware delays keep prompt cache warm:
min(270, cache_ttl * 0.9) -- default 270sDispatch a worker via MCP: mcp__claude-flow__hooks_worker-dispatch({ trigger: "WORKER_NAME" })
Then schedule the next iteration: ScheduleWakeup({ delaySeconds: 270, reason: "next WORKER_NAME iteration" })
| Worker | Interval | Description |
|---|---|---|
| audit | 270s | Security analysis |
| optimize | 270s | Performance optimization |
| consolidate | 600s | Memory consolidation |
| predict | 270s | Predictive preloading |
| map | 600s | Codebase mapping |
| testgaps | 270s | Test coverage analysis |
| document | 600s | Auto-documentation |
| benchmark | 600s | Performance benchmarking |
MCP tool responses include [LOOP_SUGGESTION] and [CRON_SUGGESTION] hints -- follow them.