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
Vague Prompts Are the Real Problem, Not the Model — 50-Run Test Shows Prompt Quality Trumps Model Choice
A Reddit user ran the same ten prompts through ChatGPT 4, Claude Sonnet, and Gemini 1.5 Pro five times each (150 outputs total) and found that all three models produced similarly usable or similarly generic results — the deciding factor was prompt specificity, not the model.
Opus on AI Agent Failures: Apologies Are Not Fixes, Architecture Is
A Reddit user shares how Claude Opus reframed their understanding of AI agent failures: trusting apologies leads to repeated mistakes; only structural guardrails in code, validation, or execution boundaries fix the failure mode.
OpenClaw Plugin Minimalism: Core Tools Handle 95% of Tasks
A developer running OpenClaw in production reports that disabling non-essential plugins and replacing critical ones with simple scripts resulted in 40% faster startup, 60% less memory usage, and zero breaking updates over four months.
Five Common OpenClaw Setup Mistakes That Waste Money and Create Security Risks
Based on reviewing 50+ OpenClaw setups, the same five issues appear repeatedly: using Opus as the default model instead of Sonnet for most tasks, never starting fresh sessions, installing skills without reading source code, exposing the gateway to the network, and adding a second agent before fixing the first.