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Claude 高效使用：从对话到 Claude Code

D2 长文档、多模态与 API 初见：大上下文怎么用、prompt caching 省钱、PDF 与图片输入、带引用回答；Messages API 最小调用

• prompt caching 省在哪？什么情况下反而不省？线上发现缓存命中率是零，你怎么排查？Where does prompt caching save money, when does it cost more, and how do you debug a zero cache-hit rate in production?

  国内高频海外高频进阶#prompt-caching#cost

  分析过程 · 先想清楚再作答

  1. 三问对应三层：原理、边界、排查。只答第一层是背文档，第三层才体现有没有真的上过线。
  2. 原理一句话：缓存匹配的是请求开头到 cache_control 标记为止的精确前缀（顺序是工具、system、messages），命中时这段只收正常输入价的 0.1 倍；代价是写入那一次收 1.25 倍（1 小时档 2 倍）。
  3. 不省的情况由此推出：同一前缀只用一次（多付 25%）；前缀里有每次都变的内容（时间戳、随机 id、未排序 JSON、用户名），导致每次都在写永远用不上的缓存；前缀短于最小门槛（主力模型 1024 token，Haiku 4.5 是 4096）根本不会缓存；两次请求间隔超过 TTL。
  4. 排查清单按发生概率排：一看 system 或工具定义开头有没有动态内容；二看两次请求的模型 id 是否一致；三看前缀长度是否过门槛；四看间隔是否超 5 分钟；五看工具列表顺序是否稳定。判据只有一个字段：usage.cache_read_input_tokens 是否大于 0。
  5. 可预期的追问：断点应该打在哪？不变的末尾——工具定义末尾、system 末尾、长文档末尾、多轮对话倒数第二条消息，最多四个；打在每轮都变的内容上等于白写。

  How to reason about it · think before answering

  1. Three questions, three layers: mechanism, boundaries, debugging. The third layer is what shows production experience.
  2. Mechanism: the cache matches the exact byte prefix from the start of the request to the cache_control marker (tools, then system, then messages). A hit bills that prefix at 0.1x input price; the write costs 1.25x (2x for the one-hour TTL).
  3. When it costs more: a prefix used only once (+25%); volatile content inside the prefix — timestamps, random ids, unsorted JSON, user names — so every call writes a cache nothing will read; a prefix below the minimum (1024 tokens on current flagship models, 4096 on Haiku 4.5) that silently never caches; requests spaced beyond the TTL.
  4. Debug order by likelihood: dynamic content at the head of system or tool definitions; model id mismatch between calls; prefix under the minimum; gap over five minutes; unstable tool ordering. The single signal is usage.cache_read_input_tokens greater than zero.
  5. Follow-up: where do breakpoints go? At the end of stable sections — tools, system, the long document, the second-to-last message in a multi-turn chat — at most four; a breakpoint on per-turn content is a wasted write.

  答题要点

  • 匹配精确前缀（工具 → system → messages 到标记为止）；命中 0.1 倍，写入 1.25 倍
  • 不省：前缀只用一次、前缀含动态内容、前缀短于最小门槛、间隔超过 TTL
  • 排查：动态内容、模型不一致、长度不够、间隔太久、工具顺序变了；看 cache_read_input_tokens
  • 断点打在不变部分的末尾，最多四个

  Key points

  • Matches the exact prefix (tools → system → messages up to the marker); hits bill 0.1x, writes 1.25x
  • Costs more when the prefix is used once, contains volatile content, is under the minimum length, or requests exceed the TTL
  • Debug: dynamic content, model mismatch, length, gap, tool ordering; verify via cache_read_input_tokens
  • Place breakpoints at the end of stable sections, at most four