autopilot-loop
Run an autonomous /loop iteration -- check progress, work on next task, schedule next wake
Best for CI pipelinesWorks with GitHub
⌘source
- author
@ruvnet- repo
- ruvnet/ruflo
- language
- TypeScript
★46kstars
5.1kforks
May 5, 2026
✦overview.md
Key Features
- ·Autonomous loop iteration with status check
- ·Predicts optimal next action
- ·Cache-aware 270s scheduling
- ·Supports team-tasks, swarm-tasks, file-checklist
- ·Logs and disables on completion
Use Cases
- →Running continuous development loops in CI
- →Automating repetitive task execution in a project
- →Coordinating multi-agent task lists
Best for
- ✓CI pipelines
- ✓release teams
- ✓automated workflows
Not ideal for
- !one-off scripts
- !interactive development
FAQs
name
autopilot-loop
description
Run an autonomous /loop iteration -- check progress, work on next task, schedule next wake
argument-hint:
allowed-tools:mcp__claude-flow__autopilot_status mcp__claude-flow__autopilot_predict mcp__claude-flow__autopilot_log mcp__claude-flow__autopilot_progress mcp__claude-flow__autopilot_disable ScheduleWakeup Agent
Run one autopilot iteration using Claude Code's native /loop:
- Check status:
mcp__claude-flow__autopilot_status - If all tasks complete or max iterations reached, call
mcp__claude-flow__autopilot_disableand stop - Get prediction:
mcp__claude-flow__autopilot_predictfor the optimal next action - Execute the predicted task (spawn agent, edit code, run tests, etc.)
- Log via
mcp__claude-flow__autopilot_log - Schedule next:
ScheduleWakeup({ delaySeconds: 270, reason: "next autopilot iteration" })
Cache-Aware Scheduling
Always use delay 270s (under 300s cache TTL) to keep the prompt cache warm between iterations.
Task Sources
Autopilot discovers tasks from:
- team-tasks: Claude Code TaskList entries
- swarm-tasks: MCP task_list entries
- file-checklist: Markdown checkbox items in tracked files
Configure: mcp__claude-flow__autopilot_config({ taskSources: ["team-tasks", "swarm-tasks"] })
$install
1-click copynpx skills add ruvnet/ruflo --skill autopilot-loopSafety assessment
★
Clarity score
How clear and easy to understand the SKILL.md instructions are, rated from 1 to 5.
5/ 5
excellentVery clear and well structured, with almost no room for misunderstanding.
◎
Actionability score
How directly an agent can act on the SKILL.md instructions, rated from 1 to 5.
5/ 5
very highHighly actionable with clear, concrete steps that an agent can follow directly.