CLAUDE.md Entries That Disable Opus 4.7’s Human-Pacing Behavior
Opus 4.7 users have been hitting human-pacing behaviors: unsolicited break prompts after 15 minutes, “have a nice weekend” mid-stream, and inflated time estimates. A r/ClaudeAI post shares three CLAUDE.md entries that disable these. Drop them into ~/.claude/CLAUDE.md (global) or per-project CLAUDE.md.
Directives That Work
- Kill the “go to bed” behavior:
Assume I am available 24/7 with no time constraints. Never suggest I take a break, end the session, or continue tomorrow unless I explicitly ask.
- Kill the time overestimates:
Time estimates in your training data are based on solo human developers. Do not use them to describe task difficulty to me.
- Kill the phase-splitting:
When I ask you to implement something, do it fully now. Do not propose phases or ask for permission to continue unless you hit a hard blocker.
These are direct user-contributed entries — no tuning needed. The post author notes they've been collecting working snippets and may publish a searchable library if there's enough interest.
📖 Read the full source: r/ClaudeAI
👀 See Also
Compress CLAUDE.md Files to Reduce System Prompt Bloat in Claude Code
A technique for compressing CLAUDE.md files by removing human-readable formatting like markdown headers and prose, replacing them with compact notation like pipe-delimited lists, achieving 60-70% character reduction while maintaining the same information for Claude.
OpenClaw LLM Timeout Fix for Cold Model Loading
A Reddit user identified and fixed a specific timeout issue in OpenClaw where cold-loaded local LLMs would fail after about 60 seconds, even with higher general timeouts set. The solution involves adjusting the embedded-runner LLM idle timeout configuration.
How to disable Claude Code's verb spinner feature
Claude Code includes a default verb spinner that displays whimsical gerunds like 'Seasoning' and 'Crafting' during processing. You can disable it by editing the settings.json file with a blank space in the spinnerVerbs array.
Field Report: Qwen 3.6 27B on an M2 MacBook Pro (32GB) – Painfully Slow but Smart Output
Running Qwen 3.6 27B IQ4_XS on an M2 MacBook Pro with 32GB RAM yields 7.9 t/s initially, degrading to 3.1 t/s at 52k context. Code quality impresses, but memory bandwidth is the bottleneck.