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English(EN) How much context does Cursor spend understanding a large repository before writing code?

编码代理在重复的代码库探索中浪费上下文

一位用户在对代码分析工作流程进行基准测试时发现,编码代理消耗了相当一部分上下文预算用于重复的代码库探索,而不是用于推理或代码生成。这表明当前系统可能效率低下,会重新发现它们已经处理过的信息。用户正在寻求关于如何最好地衡量这些代码库智能系统的有效性的意见,并考虑检索准确性、答案质量、令牌使用和探索循环等因素。 AI

影响 突出了当前 AI 编码工具的潜在低效率,表明需要优化上下文管理和代码库理解。

排序理由 用户生成的产品性能讨论和基准测试。

在 r/cursor 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

编码代理在重复的代码库探索中浪费上下文

本文如何被排名

Signal score
0 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Commentary
用户生成的产品性能讨论和基准测试。
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
product, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
82 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准

报道来源 [1]

  1. r/cursor TIER_2 English(EN) · /u/Western-Stock2454 ·

    Cursor 在编写代码前需要花费多少时间来理解大型代码库?

    <table> <tr><td> <a href="https://www.reddit.com/r/cursor/comments/1tyv20r/how_much_context_does_cursor_spend_understanding/"> <img alt="How much context does Cursor spend understanding a large repository before writing code?" src="https://preview.redd.it/a9dtezztpq5h1.png?width=…