Run an autonomous /loop iteration -- check progress, work on next task, schedule next wake
Scanned 9/4/2026
Install to Claude Code
npx -y skills add ruvnet/claude-flow --skill autopilot-loop --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Autopilot Loop?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/ruvnet-autopilot-loop-ruflo)More formats (shields.io, HTML) on the badges page.
---
name: autopilot-loop
description: Run an autonomous /loop iteration -- check progress, work on next task, schedule next wake
argument-hint: ""
allowed-tools: mcp__plugin_ruflo-core_ruflo__autopilot_status mcp__plugin_ruflo-core_ruflo__autopilot_predict mcp__plugin_ruflo-core_ruflo__autopilot_log mcp__plugin_ruflo-core_ruflo__autopilot_progress mcp__plugin_ruflo-core_ruflo__autopilot_disable ScheduleWakeup Agent
---
Run one autopilot iteration using Claude Code's native /loop:
1. Check status: `mcp__plugin_ruflo-core_ruflo__autopilot_status`
2. If all tasks complete or max iterations reached, call `mcp__plugin_ruflo-core_ruflo__autopilot_disable` and stop
3. Get prediction: `mcp__plugin_ruflo-core_ruflo__autopilot_predict` for the optimal next action
4. Execute the predicted task (spawn agent, edit code, run tests, etc.)
5. Log via `mcp__plugin_ruflo-core_ruflo__autopilot_log`
6. 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__plugin_ruflo-core_ruflo__autopilot_config({ taskSources: ["team-tasks", "swarm-tasks"] })`
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.