CORVUS trims LLM coding agent histories, cutting tokens and cycles by up to 37%
CORVUS redesigns LLM coding agent trajectories by separating file‑read actions from snapshot observations, keeping a synchronized file registry that injects current contents only when needed. On SWE‑PolyBench and SWE‑Bench, it slashes average input tokens 9‑50%, shortens prompts 15‑32% and reduces reasoning cycles up to 37% without hurting pass rates.