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OpenClaw 学习循环与技能提炼：用于在非显而易见的问题解决后记录 learning、复盘并晋升为 skill；用于需要检查 self-improving-agent、生成学习记录、输出 dry-run 预览或执行一键式学习闭环时。
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Install two Hermes-like capabilities into OpenClaw: a learning loop for self-improvement and Honcho-based user modeling for richer cross-session memory. Use when the user wants a packaged OpenClaw upgrade kit, a public tutorial bundle, or a one-click distribution package that combines OpenClaw Learning Loop and Honcho onboarding.
Set up Honcho as a shared memory layer for one or more AI agents, verify it is healthy, and demonstrate how to inspect user memory, agent memory, and cross-agent context. Use when the user wants a practical Honcho tutorial, local self-hosting guide, multi-agent memory sync pattern, or a quick way to connect multiple OpenAI-compatible or custom agents to a shared memory workspace.
| name | openclaw-learning-loop |
| description | OpenClaw 学习循环与技能提炼：用于在非显而易见的问题解决后记录 learning、复盘并晋升为 skill；用于需要检查 self-improving-agent、生成学习记录、输出 dry-run 预览或执行一键式学习闭环时。 |
把一次问题解决，变成可复用的学习记录。
scripts/bootstrap.sh to verify OpenClaw and self-improving-agent availability.scripts/extract.sh <skill_name> <dry_run> to generate a learning prompt or record.skill_name: my-new-skilldry_run: trueclawhub list as the source of truth for installed skills.self-improving-agent.