autonomous-loops

Provide vetted patterns for running Claude Code in autonomous loops.

2|Updated Mar 12, 2026
One-click install
npx skills add https://github.com/sayasaya8039/ZWG_Terminal --skill autonomous-loops-sayasaya8039
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: autonomous-loops
Source: https://github.com/sayasaya8039/ZWG_Terminal/tree/main/.claude/skills/autonomous-loops
Command: npx skills add https://github.com/sayasaya8039/ZWG_Terminal --skill autonomous-loops-sayasaya8039

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the guesswork of selecting and implementing the right autonomous workflow pattern for Claude Code, providing clear guidance for everything from simple daily scripted tasks to complex multi-agent large feature development.

Core Features & Use Cases

  • 6 Proven Loop Patterns: Covers the full spectrum from low-complexity sequential claude -p pipelines to high-complexity RFC-driven multi-agent DAG orchestration with merge queues.
  • Production-Ready Workflows: Includes battle-tested patterns like the Continuous Claude PR Loop with CI failure recovery, cost/time limits, and cross-iteration context persistence.
  • Use Case Example: A development team building a multi-unit authentication feature can use the Ralphinho DAG pattern to decompose the RFC into parallel work units, run tiered quality pipelines for each, and automatically merge conflict-free changes.

Quick Start

Use the autonomous-loops skill to recommend the optimal loop pattern for your project and generate a ready-to-run sequential pipeline that automates your daily development steps including implementation, cleanup, verification, and commit.

Frequently Asked Questions about autonomous-loops

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build autonomous Claude Code loops for CI/CD pipelines?

Build autonomous Claude Code loops by applying vetted patterns for dev pipelines, enabling context persistence, quality gates, and configurable exit conditions to run CI/CD tasks without human intervention.

What is multi-agent DAG orchestration for large feature development?

Multi-agent DAG orchestration decomposes RFCs into parallel work units using multiple Claude Code agents, running tiered quality pipelines and merge queues to automatically merge conflict-free changes.

How do I recover from merge conflicts in automated multi-agent workflows?

Recover from merge conflicts in automated multi-agent workflows by implementing battle-tested autonomous loop patterns equipped with CI failure recovery and cross-iteration context persistence.

Can I run Claude Code in a continuous PR loop with cost and time limits?

Yes, you can run Claude Code in a continuous PR loop using production-ready patterns that include configurable cost and time limits, CI failure recovery, and cross-iteration context persistence.

How do I choose the right autonomous workflow pattern for my development task?

Choose the right autonomous workflow pattern by evaluating task complexity, ranging from simple sequential pipelines for daily scripted tasks to complex RFC-driven DAG orchestration for large features.