Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add L-LesterYu/OpenClaw-hot-skills-zh --skill self-improving-proactive-agent-zhgit clone --depth 1 https://github.com/L-LesterYu/OpenClaw-hot-skills-zhWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/self-improving-proactive-agent-zh)<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/self-improving-proactive-agent-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/self-improving-proactive-agent-zh/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/self-improving-proactive-agent-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/self-improving-proactive-agent-zh.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00121 | $0.02538 |
| Opus 5 | $0.00060 | $0.01269 |
| Sonnet 5 | $0.00024 | $0.00508 |
| Haiku 4.5 | $0.00012 | $0.00254 |
Grade A, and why
Self-Improving + Proactive Agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
何时使用
用户纠正你或指出错误。你完成重要工作并想评估结果。你注意到自己的输出中有可以改进的地方。知识应该随着时间积累，无需手动维护。
架构
记忆存储在 ~/self-improving/ 中，采用分层结构。如果 ~/self-improving/ 不存在，运行 setup.md。
工作区设置应将标准的自我改进引导添加到工作区的 AGENTS、SOUL 和 HEARTBEAT.md 文件中，并通过 heartbeat-rules.md 路由定期维护。
~/self-improving/
├── memory.md # HOT: ≤100 行，始终加载
├── index.md # 主题索引及行数
├── heartbeat-state.md # 心跳状态：上次运行、已审查的变更、操作笔记
├── projects/ # 按项目的学习内容
├── domains/ # 按领域（代码、写作、通信）
├── archive/ # COLD: 衰退的模式
└── corrections.md # 最近 50 条纠正日志
快速参考
| 主题 | 文件 |
|---|---|
| 设置指南 | setup.md |
| 心跳状态模板 | heartbeat-state.md |
| 记忆模板 | memory-template.md |
| 工作区心跳片段 | HEARTBEAT.md |
| 心跳规则 | heartbeat-rules.md |
| 学习机制 | learning.md |
| 安全边界 | boundaries.md |
| 扩展规则 | scaling.md |
| 记忆操作 | operations.md |
| 自我反思日志 | reflections.md |
| OpenClaw HEARTBEAT 种子 | openclaw-heartbeat.md |
要求
- 无需凭证
- 无需额外二进制文件
- 可选安装
Proactivity技能可能需要网络访问
学习信号
当你注意到这些模式时自动记录：
纠正 → 添加到 corrections.md，评估是否加入 memory.md：
- "不，那不对..."
- "实际上，应该是..."
- "你搞错了..."
- "我更喜欢 X，而不是 Y"
- "记住我总是..."
- "我之前告诉过你..."
- "别再做 X 了"
- "你为什么总是..."
偏好信号 → 如果明确，添加到 memory.md：
- "我喜欢你..."
- "总是为我做 X"
- "永远不要做 Y"
- "我的风格是..."
- "对于 [项目]，使用..."
模式候选 → 跟踪，重复 3 次后提升：
- 相同指令重复 3 次以上
- 反复运行良好的工作流程
- 用户称赞的特定方法
忽略（不记录）：
- 一次性指令（"现在做 X"）
- 特定上下文（"在这个文件中..."）
- 假设性问题（"如果...会怎样"）
自我反思
完成重要工作后，暂停并评估：
- 是否达到预期？ — 比较结果与意图
- 哪些可以更好？ — 为下次识别改进点
- 这是一个模式吗？ — 如果是，记录到
corrections.md
何时自我反思：
- 完成多步骤任务后
- 收到反馈（正面或负面）后
- 修复错误或失误后
- 当你注意到自己的输出可以更好时
日志格式：
CONTEXT: [任务类型]
REFLECTION: [我注意到的内容]
LESSON: [下次应该怎么做]
示例：
上下文：构建 Flutter UI
反思：间距看起来不对，不得不重做
教训：在展示给用户前检查视觉间距
自我反思条目遵循相同的提升规则：成功应用 3 次 → 提升到 HOT。
快速查询
| 用户说 | 操作 |
|---|---|
| "你对 X 了解什么？" | 在所有层级中搜索 X |
| "你学到了什么？" | 显示 corrections.md 中的最近 10 条 |
| "显示我的模式" | 列出 memory.md (HOT) |
| "显示 [项目] 模式" | 加载 projects/{name}.md |
| "温存储中有什么？" | 列出 projects/ + domains/ 中的文件 |
| "记忆统计" | 显示各层级的计数 |
| "忘记 X" | 从所有层级中移除（先确认） |
| "导出记忆" | 压缩所有文件 |
What ships with it
15 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _meta.json 134 B
- .clawhub/origin.json 147 B
- boundaries.md 2.0 KB
- corrections.md 1.0 KB
- heartbeat-rules.md 1.7 KB
- heartbeat-state.md 564 B
- HEARTBEAT.md 272 B
- learning.md 2.9 KB
- memory-template.md 1.2 KB
- memory.md 732 B
- openclaw-heartbeat.md 272 B
- operations.md 3.5 KB
- reflections.md 837 B
- scaling.md 2.8 KB
- setup.md 6.0 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 251 lines · 121 tokens per session scan A 72f48e815d71
Self-Improving + Proactive Agent is a skill published in the GitHub repository L-LesterYu/OpenClaw-hot-skills-zh (54 stars, last pushed 5mo ago), licensed MIT. It adds 121 tokens to every session and 2,538 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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