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HarnessX

Composable runtime scaffolding for adaptive AI agents that learn from execution traces

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HarnessX is an academic research framework for building evolvable agent harnesses that systematically compose prompts, tools, memory, and control flow. Unlike static frameworks, it introduces runtime scaffolding that learns from execution traces to improve agent behavior over time. Designed for researchers exploring adaptive agent architectures and self-improving systems.

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frameworkopen-sourceautonomousmemoryorchestrationevaluationtracing