/loop-worker
Run Ruflo background workers using Claude Code native /loop scheduling
$ npx -y skills add ruvnet/ruflo --skill loop-worker --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/loop-worker
Context preview
The summary Claude sees to decide when to auto-load this skill.
Run Ruflo background workers using Claude Code native /loop scheduling
SKILL.md
loop-worker.SKILL.mdname: loop-worker description: Run Ruflo background workers using Claude Code native /loop scheduling argument-hint: "<worker-name>" allowed-tools: Bash(npx *) mcp__plugin_ruflo-core_ruflo__hooks_worker-dispatch mcp__plugin_ruflo-core_ruflo__hooks_worker-status ScheduleWakeup
Use `/loop` for in-session periodic workers. Cache-aware delays keep prompt cache warm:
- Delay formula: `min(270, cache_ttl * 0.9)` -- default 270s
Dispatch a worker via MCP: `mcp__plugin_ruflo-core_ruflo__hooks_worker-dispatch({ trigger: "WORKER_NAME" })`
Then schedule the next iteration: `ScheduleWakeup({ delaySeconds: 270, reason: "next WORKER_NAME iteration" })`
Available Workers
| 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.
An agent meta-harness for Claude Code and Codex. Agent = Model + Harness. The model writes; the harness gives it tools, memory, loops, sandboxes, and controls so it can actually work.
Repo: ruvnet/ruflo
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