#428 · Primary category: AI Agents & Automation
ralph-orchestrator
An improved implementation of the Ralph Wiggum technique for autonomous AI agent orchestration
Project last updated:08/29/26
GitHub Stars
3.1K
Forks
291
Contributors
35
License
MIT
Why we included this project
Agent loops that drift can quietly burn through tokens, and Ralph Orchestrator is built to stop that. It wraps coding agents like Claude Code and Gemini CLI in a supervised loop that re-injects your prompt each iteration, checks progress, and ends when the work is actually done or a limit is hit. What stands out is the guardrails: ceilings on iterations, runtime, and cost, plus loop detection that halts when outputs start repeating and completion markers that exit early. Teams running large refactors, batch documentation, or test-coverage expansion can hand Ralph a well-specified task and get real autonomy without constant babysitting, though the authors are honest that ambiguous or security-sensitive work still wants a human in the loop. It is early-stage and configuration can shift between releases, so treat it as something to trial against your own workflow rather than a finished product.
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