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@@ -35,7 +35,7 @@ Proxy, System, etc.) using ReAct-style reasoning, explicit tool calls, and dynam
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  a deliberate 15% routing-error rate to force models to learn recovery patterns. Sessions average
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  8–15 steps, show 92.9% final success rate, and include rich metadata such as tool-use counts,
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  routing decisions, timestamps, and generator version. The dataset is already split into train
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- (539 ≈70%), validation (127 ≈16.5%), and test (104 ≈13.5%) and is licensed under MIT.
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  **Intended use**
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  a deliberate 15% routing-error rate to force models to learn recovery patterns. Sessions average
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  8–15 steps, show 92.9% final success rate, and include rich metadata such as tool-use counts,
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  routing decisions, timestamps, and generator version. The dataset is already split into train
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+ (539 ≈70%), validation (127 ≈16.5%), and test (104 ≈13.5%).
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  **Intended use**
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