Cut OpenClaw Boot Tokens 43% by Slimming Tool & Memory Files
A user on r/openclaw slimmed their agent's boot context from ~9,457 to ~5,400 tokens — a 43% reduction — by cleaning up TOOLS.md and MEMORY.md.
Problems Found
- TOOLS.md bloat: Every tool added usage notes, commands, examples, and edge cases. Useful but not needed every session.
- Memory promotion overgrowth: Promotion candidates were added directly to main memory, causing
MEMORY.mdto grow indefinitely.
Fixes Applied
- Changed
TOOLS.mdto an index (auto-injected, so can't remove). Detailed notes moved totools/; agent reads them only when that tool is invoked. - New memory flow:
daily notes → promotion candidates → curated long-term memory. Promotion candidates go to a separate file; main memory holds only a pointer. Only durable facts needed often stay in boot memory.
Results
After: same agent, same tools, same behavior — just less loaded on every wake-up.
📖 Read the full source: r/openclaw
👀 See Also
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A Claude user discovered that asking for markdown instead of Word documents significantly reduces response time and token usage. The AI natively outputs markdown, while generating .docx files requires spinning up a Python environment and running conversion scripts.
How to Run OpenClaw Without Breaking the Bank
Reddit user digitalknk shared a practical guide on running OpenClaw efficiently. A battle-tested setup focused on stability and cost control.
How a /loop Command Burned $6,000 in Claude API Overnight
A developer's unattended /loop command running every 30 minutes on claude-opus-4-7 consumed $6,000 in one night due to prompt caching expiration and growing context — a cautionary tale for AI agent automation.