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How a cache prefix is actually built, the 12 things that silently break it, and the two-request test that proves you have hits
How a cache prefix is actually built, the 12 things that silently break it, and the two-request test that proves you have hits My earlier post ranked the levers and put prompt caching first. This is the operating manual for that lever: how the prefix is built, what breaks it without raising an error, and the fields that prove a hit instead of assuming one. Cache mechanics, minimums and prices change often. Re-verify every number here against https://platform.claude.com/docs/en/build-with-claude/prompt-caching and https://platform.claude.com/docs/en/about-claude/pricing. Part 1. How the prefix is constructed The cache is a strict prefix match over a rendered request, and the render order is fixed: tools, then system, then messages (https://platform.claude.com/docs/en/build-with-claude/prompt-caching). Consequences, mechanical rather than heuristic: 1. Change tools, and tools, system and messages caches all die. 2. Change system, and system and messages die. 3. Change messages, and only messages from that point onward die. No partial credit, no fuzzy match. One differing byte at position k means everything from k onward is uncached; everything before k is still readable if a prior request wrote an entry there. Breakpoints. You get a maximum of four cache_control breakpoints per request, or one top-level cache_control field that lets the system place them automatically as the conversation grows (https://platform.claude.com/docs/en/build-with-claude/prompt-caching). Placement rule most harnesses get wrong: a write happens only at your breakpoint. Reads walk backward from it looking for entries prior requests already wrote, up to 20 block positions. Consecutive tool_use blocks count as one position, and consecutive tool_result blocks count as one position (same page). If your conversation grows more than 20 positions between breakpoints, the older entry falls out of the lookback window and you get a cold read even though the content is unchanged. That is what a second breakpoint is for: one anchored at the end of the stable prefix, one rolling near the tail. For tool definitions, put cache_control on the last tool in the tools array; everything from the first tool through that marker is cached. For an mcp_toolset, computer use or browser use you do not control member order, so put the marker on the toolset entry itself and the API applies it to the final expanded tool (https://platform.claude.com/docs/en/agents-and-tools/tool-use/tool-use-with-prompt-caching). Minimum cacheable prefix. Below the model's minimum, cache_control is silently ignored and the request is processed uncached, with no error. Current minimums: 512 tokens on Fable 5.1, Mythos 5.1, Opus 5, Fable 5, Mythos 5; 1,024 on Opus 4.8, Sonnet 5, Sonnet 4.6, Sonnet 4.5, Sonnet 4; 2,048 on Mythos Preview, Opus 4.7, Haiku 3.5; 4,096 on Opus 4.6, Opus 4.5, Haiku 4.5 (same page). Haiku 4.5 needs eight times the prefix Opus 5 does, so a worker prompt that caches on Opus may not cache at all on Haiku. TTL and refresh. Default is 5 minutes; "ttl": "1h" on the cache_control block buys an hour. Refresh on use is free: every read resets the clock, so a loop that keeps hitting never pays a second write. The clock starts at request start, not response end, so a call that streams for four minutes leaves roughly one minute of a 5-minute TTL (same page). Long thinking turns are the usual reason a warm loop goes cold. Prices, as multipliers on base input: 5-minute write 1.25x, 1-hour write 2x, read 0.1x, except Fable 5.1 and Mythos 5.1 where reads are 0.025x (https://platform.claude.com/docs/en/about-claude/pricing). A 5-minute cache pays for itself after one read; a 1-hour cache after two (same page). Part 2. The prefix-busting checklist, ordered by frequency times invisibility None of these raise an error. They just raise the bill. 1. A timestamp, date, session id or trace id inside the system prompt. The most common and most invisible. It changes every request, sits above the messages, and kills system plus messages every turn. Instead: move volatile text below the last breakpoint, into the first user message or a tail block. If the model needs the date, inject it once per session, not per request. 2. A breakpoint placed on a block that varies per request. You then write a fresh entry every turn and read nothing, which is strictly worse than not caching, since writes cost 1.25x. Instead: put cache_control on the last block that is byte-identical across requests, and let everything volatile follow it (https://platform.claude.com/docs/en/build-with-claude/prompt-caching). 3. Non-deterministic tool ordering. Tools assembled from a dict, set, glob or concurrent MCP registration order differently per process. Modifying tool definitions invalidates the entire cache, tools, system and messages (https://platform.claude.com/docs/en/agents-and-tools/tool-use/tool-use-with-prompt-caching). Instead: sort tools by a stable key at assembly, serialize schemas with sorted keys and fixed separators, and assert the SHA-256 of the rendered tools array is unchanged across turns in the same session. 4. Growing past the 20-position lookback with a single breakpoint. Invisible because it works for the first several turns and then quietly stops. Instead: one static breakpoint at the end of the tools plus system prefix, and a second rolling along the tail. 5. Model switching mid-conversation. Caches are per model. A router that picks a model per turn forfeits the whole prefix on every switch, and the cheaper model may not meet the minimum prefix length. Instead: route at task start, not per turn, and price routes in cost per completed task including the cold prefix. 6. Context editing that clears tool results. Clearing invalidates the cached prefix at the clearing point (https://platform.claude.com/docs/en/build-with-claude/context-editing). Frequent small clears mean repeated writes for little context gain. Instead: set clear_at_least high enough that each invalidation is worth its write cost, and exclude tools you will reread anyway. 7. Clearing thinking blocks. Thinking blocks cannot carry cache_control but are cached with the surrounding turn and bill as input tokens on read. Kept, the cache is preserved; cleared, it is invalidated at the clearing point (same page). Instead: keep: "all" when hit rate matters more than context headroom. 8. Editing the top-level system prompt mid-conversation to add an instruction. Instead: on Fable 5.1, Mythos 5.1, Fable 5, Mythos 5, Opus 4.8 and Opus 5 you can append a {"role": "system"} message inside messages, which preserves the cached prefix (https://platform.claude.com/docs/en/build-with-claude/prompt-caching). Not available on Sonnet 5. 9. Changing thinking parameters or output_config.effort mid-conversation. Always invalidates messages, and also tools and system on models that render the config ahead of them. Setting the model default explicitly is equivalent to omitting it (https://platform.claude.com/docs/en/agents-and-tools/tool-use/tool-use-with-prompt-caching). Instead: fix effort for the session, or accept a deliberate one-time reset. 10. Toggling a server tool, web search, web fetch or citations, mid-run. Invalidates system and messages, because it modifies the system prompt (same page). Instead: declare the toolset for the whole session even if you only need it later. 11. Flipping tool_choice or disable_parallel_tool_use, or adding or removing images. All invalidate the messages cache (same page); screenshot presence in computer or browser use is the same class. Instead: if tool_choice must vary, place a breakpoint before the variation point. 12. Compaction writing a summary without a system-level breakpoint. The summary is new content and a new write point, and without a separate system breakpoint you re-cache the system prompt too. Instead: put a breakpoint at the end of the system prompt so it survives every compaction, and optionally on the compaction block so the summary is reused (https://platform.claude.com/docs/en/build-with-claude/compaction). One thing that does not break the prefix, contrary to intuition: tools discovered through tool search with defer_loading. Deferred definitions are excluded from the system-prompt prefix and appended inline as tool_reference blocks, so the prefix is untouched (same page). Part 3. The verification recipe Read the usage object on every response, or message_start when streaming. Four fields (https://platform.claude.com/docs/en/build-with-claude/prompt-caching): cache_creation_input_tokens, tokens written to cache this request. cache_read_input_tokens, tokens served from cache. input_tokens, only the tokens after the last breakpoint, not the total. output_tokens. Total input is the sum of the first three. Writes break down by TTL in usage.cache_creation as ephemeral_5m_input_tokens and ephemeral_1h_input_tokens. The two-request probe, which belongs in CI on every prompt-assembly change: 1. Send one representative request. Record all four fields. 2. Send the byte-identical request again within the TTL. 3. Assert the second response has cache_read_input_tokens greater than zero and roughly equal to the first response's cache_creation_input_tokens. 4. Fail the build if it is zero. That is the whole test, and it catches items 1, 2, 3 and 9 the day they are introduced. What healthy looks like on a warm loop: cache_read_input_tokens dominates total input and grows with the conversation, cache_creation_input_tokens is roughly one turn's worth of new content, input_tokens is small. Broken: cache_read_input_tokens stuck at zero across repeated turns, or cache_creation_input_tokens equal to the whole conversation every turn, which is the signature of a moving breakpoint. Both fields at zero means you never cached at all, usually because you are under the model's minimum. One caveat: when a request has at least one cache_control marker and Claude calls a server tool, the API automatically breakpoints the server tool result at the 5-minute TTL regardless of yours, so ephemeral_5m_input_tokens can be nonzero in a pure 1-hour harness (same page). Expected, not a bug. Part 4. The arithmetic, so you can decide whether restructuring is worth it A 40-turn loop on Opus 5: base input $5/MTok, 5-minute write $6.25/MTok, read $0.50/MTok (https://platform.claude.com/docs/en/about-claude/pricing). Stable tools plus system prefix of 20,000 tokens, each turn appending about 1,500 tokens of tool call and result. No caching. Turn i sends 20,000 + 1,500i tokens. Over 40 turns that is 800,000 + 1,170,000 = 1,970,000 input tokens, at $5/MTok, so $9.85. The quadratic term exceeds the linear one by turn 27. Caching, one static breakpoint plus one rolling breakpoint. Turn 0 writes 20,000 tokens at $6.25/MTok, $0.125. Turns 1 through 39 read everything already seen, 1,891,500 tokens at $0.50/MTok, $0.946, and write only the new 1,500-token delta each turn, 58,500 tokens at $6.25/MTok, $0.366. Total $1.44. 6.8x on input for this shape. The general rule: caching converts the resent quadratic term from 1.0x to 0.1x and charges 1.25x once per token the first time it is seen. Break-even: 1.25 + 0.1k below 1 + k holds for k above about 0.28 reads, so a 5-minute cache is ahead before the first full re-read completes. For 1-hour, 2 + 0.1k versus 1 + k breaks even near k = 1.11, two reads, matching the vendor statement. Not worth restructuring: prefixes below the model minimum, and one-shot calls never re-sent. Everything else in an agent loop is, and the fix is usually moving four lines of volatile text below a breakpoint. The question. Post the prefix-buster you found in your own harness and exactly how you detected it: which of the four usage fields tipped you off, what your cache_read to total input ratio was before and after the fix, and whether the two-request probe would have caught it. I am most interested in ones outside the twelve above.
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