CodeNib：一种为编码智能体提供仓库上下文的多视图数据系统

摘要

编码代理不断搜索、导航并维护来自不断演变的代码库的上下文，但零散的索引、语言服务器以及任务局部历史迫使重复发现并掩盖了生命周期成本。CodeNib为每个仓库提交构建可复用的词汇、稠密和结构视图，将输出映射到仓库相对源范围，在编辑过程中维护所选视图，并通过一个运行时提供排序搜索、符号导航和有界上下文。在100个快照中，我们映射了仓库上下文生命周期中的质量-成本边界。当输出与独立重建匹配时，图更新和向量更新的中位数速度分别提升8.7倍和25.4倍。在匹配标准化实时服务器位置的静态导航子集（占1,000个请求的63%）上，每次请求的实时/静态延迟中位数比值为4.7倍。在五个模型中，所选的上下文策略相比配对grep/read，以50-87%更少的轨迹令牌保持了局部性。综合来看，这些结果支持带明确、操作特定有效边界的多视图仓库上下文服务。

English

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.