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First, separate context size from prompt-cache reuse
Claude Code’s initial context is the instructions and memory loaded into a session, along with the conversation and other request content. User- and project-level CLAUDE.md instructions and auto memory can add to that context. Claude Code loads ancestor instruction files at launch and can load relevant subdirectory instructions when needed. A fresh session starts with a fresh context window, while memory mechanisms carry knowledge across sessions. Anthropic’s memory documentation explains how these sources are organized and loaded.
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Prompt caching concerns whether repeated API requests can reuse matching content. A cache break occurs when content before the relevant breakpoint changes, preventing a match for that prefix. Caching can reduce the cost of repeated content, but it does not remove that content from the request context. Reducing a CLAUDE.md file therefore does not, by itself, fix a cache break in a custom API integration.
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Inspect context before editing files so you can target the actual source of overhead:
- Run
/contextto see what is consuming context. - Run
/usageto inspect token usage.
These commands help distinguish persistent instructions from conversation history and other context consumers. Anthropic documents them alongside other context and cost-management practices in Manage costs effectively.
Reduce instructions loaded at session start
Keep CLAUDE.md short and broadly applicable
Reserve CLAUDE.md for durable information that is useful across many sessions: project conventions, architecture that is not easy to infer, common commands, and broadly applicable instructions. Anthropic’s current documentation recommends targeting fewer than 200 lines per CLAUDE.md file. That is a maintenance guideline, not a guaranteed token budget or a hard limit.
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Prefer concise, verifiable directions over general advice or repeated rules. Review ancestor files, local overrides, and imported content for duplication or conflicts. Imports can make instructions easier to organize, but imported text still enters context; splitting a large file into imports does not reduce the total loaded content.
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Do not load every folder’s specialized instructions for every task. Put guidance for particular paths in .claude/rules/ with path scoping, use a subdirectory CLAUDE.md where appropriate, or put a multi-step procedure into a skill. These options let Claude Code apply relevant guidance without making every instruction part of the always-loaded project file. The memory documentation describes these approaches and their loading behavior.
Manage conversation history between tasks
Use /clear when the next task is unrelated
/clear starts a fresh task context, preventing stale conversation history from carrying into unrelated work. If you may need the earlier conversation, rename the session before clearing it so you can resume it later.
Use /compact when continuing a long task
/compact summarizes the conversation while keeping the session moving. Add a specific instruction about what the summary should emphasize—for example, “Focus on code samples and API usage.” Compaction is a summarization strategy, not a guarantee that every detail from the earlier conversation will remain available.
Anthropic documents both commands in its context and cost-management guidance.
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Choose the right approach for the problem
| Approach | Best for | Trade-off |
|---|---|---|
Shorten CLAUDE.md and scope narrow guidance |
Reducing always-loaded project instructions while retaining relevant rules | You must maintain file scope carefully; imported instructions still consume context. Source: Claude Code memory documentation. |
/clear |
Starting unrelated work without stale conversation history | The next task starts fresh; rename the prior session if you may need to resume it. Source: Claude Code cost-management documentation. |
/compact with guidance |
Continuing a long task with a summarized conversation | Summarization may not preserve every detail. Source: Claude Code cost-management documentation. |
--bare for scripted calls |
Minimal startup when project memory and customizations are unnecessary | Skips discovery of memory and custom features, including CLAUDE.md and auto memory. Source: Claude Code CLI reference. |
| Stable API prefix and cache breakpoint | Improving reuse in a custom API workload | Content before the breakpoint must stay stable; this does not reduce request context. Source: Claude Platform prompt-caching documentation. |
Use –bare only when scripted work does not need customization
The Claude Code CLI documents --bare as a minimal mode for scripted calls. It skips discovery of memory and customizations, including CLAUDE.md and auto memory, as well as features such as MCP servers, plugins, hooks, custom commands, and subagents. That can reduce startup-loaded context when a script does not need them, but it also means those project instructions and features are unavailable. It is not a general recommendation for interactive coding sessions that rely on project guidance. Check the current CLI reference for release-specific details.
The same reference documents --exclude-dynamic-system-prompt-sections for scripted, multi-user workloads. It moves per-user context out of the system prompt and into the first user message to improve cache reuse across users or machines doing the same task. This is a specialized cache-reuse option, not a general way to shrink an interactive Claude Code session; confirm its current availability and behavior in the CLI reference before relying on it.
Keep API prompt prefixes stable to avoid cache breaks
For custom API integrations that use explicit cache breakpoints, Anthropic’s prompt-caching documentation advises keeping the cached prefix identical between requests. In the ordinary case, one breakpoint at the end of static content is sufficient. Put the breakpoint on the last block that remains unchanged, and place per-request content—such as a timestamp or the incoming user message—after that stable portion.
Use multiple breakpoints only when sections change at different rates or you need finer control. Anthropic documents a maximum of four breakpoints. The breakpoint count itself does not add cost; cache writes and reads are billed according to applicable token pricing and cache duration. Model support, minimum cacheable length, time to live, and prices can change, so check the current platform documentation before designing around specific limits or estimating costs.
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