prompt-caching-patterns

# Prompt Caching Patterns Cache repeated prefixes when reuse offsets write costs. Cache eligibility and pricing depend on the model and platform; a short system prompt is not cached merely because it repeats. ## Dated cache reference (2026-09-23) | Model | Minimum eligible prefix | Cache read / base input price | |-------|-------------------------|-------------------------------| | Claude Opus 5.5 | 512 tokens | 5% | | Claude Fable 5.1 | 512 tokens | 2.5% | | Claude Sonnet 5 | 1024 tokens | 10% | | Claude Haiku 4.5 | 4096 tokens | 10% | For the Claude API, a five-minute write costs 1.25 times base input and a one-hour write costs 2 times base input. Recheck [current pricing](https://platform.claude.com/docs/en/about-claude/pricing) before budgeting; provider-specific billing and model availability can differ. ## Prefix design Cache order is `tools → system → messages`, regardless of the order of request keys. An explicit breakpoint includes the marked block and everything before it. Keep dynamic material after the stable prefix. ```text [ tool definitions ] breakpoint 1 [ reusable system instructions ] breakpoint 2 [ reference documents ] breakpoint 3 [ stable conversation prefix ] breakpoint 4 [ current variable content ] ``` There are at most four breakpoints. Top-level automatic `cache_control` moves a breakpoint to the last eligible block and consumes one slot. Explicit markers give control over a static prefix. ## Explicit caching example The caller supplies the approved model, text and output limit. Marking a prefix below its model's minimum silently produces no cache entry. ```python def cached_answer(client, model, policy, document, question, max_tokens): return client.messages.create( model=model, max_tokens=max_tokens, system=[{ "type": "text", "text": policy, "cache_control": {"type": "ephemeral"}, }], messages=[{ "role": "user", "content": [ {"type": "text", "text": document, "cache_control": {"type": "ephemeral"}}, {"type": "text", "text": question}, ], }], ) ``` Use `{"type": "ephemeral", "ttl": "1h"}` for an approved one-hour write. When mixing TTLs, put longer-lived breakpoints before shorter-lived ones. Do not send paid heartbeat requests simply to keep an unused prefix warm. ## Invalidation Changing tools invalidates subsequent system and message prefixes; changing the system invalidates subsequent messages. Top-level effort changes invalidate message cache blocks and can affect earlier blocks depending on the model. Supported per-message effort updates preserve earlier prefixes. Changing the model is not a promise of cross-model cache reuse. A static string passed as `system` alone does not enable caching: configure `cache_control` at the request or content-block level. Keep tool definitions, document serialization and stable instructions deterministic. ## Measuring reuse Include writes when calculating the fraction of input served from cache. ```python def cache_read_fraction(usage): read = usage.cache_read_input_tokens or 0 written = usage.cache_creation_input_tokens or 0 uncached = usage.input_tokens or 0 total = read + written + uncached return read / total if total else 0.0 ``` Record write/read counts and actual costs across cold and warm requests. Choose a target from observed reuse; a single universal hit-rate threshold is misleading. Both cache counters remaining zero can indicate an ineligible prefix. ## When not to cache Skip cache writes when no prefix will be reused before expiry or when measured cost exceeds uncached requests. Do not pad prompts with irrelevant content merely to reach a minimum. A one-hour TTL may fit intermittent reuse better than five minutes, within the approved cost policy. ## Sources and related skills Reviewed 2026-09-23: - [Prompt caching](https://platform.claude.com/docs/en/build-with-claude/prompt-caching) - [Pricing](https://platform.claude.com/docs/en/about-claude/pricing) Use `model-routing-patterns` for route evaluation and `llm-ops-engineer` for application operations.