CodeNib: A Multi-View Data System for Serving Repository Context to Coding Agents
Authors: name: Zhongming Yu, name: Hengjia Yu, name: Boqin Yuan, name: Shuting Zhao, name: Yizhao Chen, name: Aryan Dokania, name: Mihir Jagtap, name: Jiayu Chang, name: Yitong Ma, name: Yash Jayswal, name: Wentao Ni, name: Hejia Zhang, name: Zhaoling Chen, name: Gangda Deng, name: Jishen Zhao
Organization: SysEvol AI Research

Coding agents repeatedly search, navigate, and retain context from evolving repositories, but disconnected indexes, language servers, and task-local histories force repeated discovery and obscure lifecycle costs. CodeNib builds reusable lexical, dense, and structural views per repository commit, maps outputs to repository-relative source ranges, maintains selected views across edits, and serves ranked search, symbol navigation, and bounded context through one runtime.
  Across 100 snapshots, we map quality-cost frontiers across the repository-context lifecycle. When outputs match an independent rebuild, graph and vector updates are 8.7times and 25.4times faster at the median. On the static-navigation subset matching normalized live-server locations (63% of 1,000 requests), the median per-request live/static latency ratio is 4.7times. Across five models, selected context policies preserve localization with 50--87% fewer trajectory tokens than paired grep/read. Together, these results support multi-view repository-context serving with explicit, operation-specific validity boundaries.