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multi-agent-ralph-loop
by alfredolopez80
Memory-first multi-agent orchestration with built-in quality gates and learning
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Updated Jun 22, 2026
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Overview
Orchestrates multi-agent workflows with a memory-first, parallel-team design built for Claude Code. Uses a 4-layer MemPalace memory stack, Aristotle First Principles reasoning, and 4-stage quality gates to evaluate and improve agent outputs automatically. Ships extensive test coverage, hooks for instrumentation, and an automatic learning pipeline to close the loop on failures and retries. Evaluation-Driven Development (EDDOps)
Why It Matters
As agents delegate and collaborate, you need continuous checks that track which agents actually deliver reliable results. Ralph Loop codifies evaluation into the orchestration layer—making agent reliability, failure modes, and quality gates visible and actionable. That visibility is essential for building agent-to-agent evaluation, agent track record analysis, and trust signals rather than treating models as opaque components. Orchestration and Agent-to-Agent Protocol (A2A) help codify these dynamics, while watching for Cascading Reliability Failures.
Best For
Teams building production multi-agent workflows (especially Claude-based) who need evaluation-driven orchestration and automated quality gates. Leverage the Tool Use Pattern to orchestrate tool-enabled agents effectively.
Use Cases
- Coordinate parallel specialist agents on complex code or planning tasks with memory-aware context
- Automatically gate and reroute agent outputs via 4-stage quality checks and failure-recovery hooks
- Continuously evaluate agent performance and feed failures into a learning pipeline to improve reliability
Works With
anthropic
Topics
ai-orchestrationautomationbats-testingclaude-codecode-qualitycodexcodex-clidynamic-contextseval-driven-developmentllm+10 more
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Keywords
multi-agent trustA2A evaluationmulti-agent orchestrationagent track record