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 proactive-self-improving-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/proactive-self-improving-agent-zh)<a href="https://agentmods.dev/skills/l-lesteryu/openclaw-hot-skills-zh/proactive-self-improving-agent-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/proactive-self-improving-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/proactive-self-improving-agent-zh"><img src="https://agentmods.dev/badge/skills/l-lesteryu/openclaw-hot-skills-zh/proactive-self-improving-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 | $0.00206 | $0.04258 |
| Opus 5 | $0.00103 | $0.02129 |
| Sonnet 5 | $0.00041 | $0.00852 |
| Haiku 4.5 | $0.00021 | $0.00426 |
Grade A, and why
proactive-self-improving-agent scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- 审查 SKILL.md 有无可疑命令（shell、curl、数据外传） How it starts
The opening of the file, as written. The whole thing — 436 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Proactive Self-Improving Agent
自动捕获经验 · 安全进化 · 记录轨迹
让 agent 在日常工作中自动识别错误、纠正和最佳实践，结构化记录，安全地将经验沉淀为长期能力。
目录
1. 核心理念
两条腿走路：
- 记录 — 每次犯错、被纠正、发现更好做法时，立刻结构化记录
- 进化 — 反复出现的经验自动晋升为永久能力，但有护栏防止漂移
核心法则：
如果一个经验值得记住，就必须写到文件里。脑子里的"记住了"不算数。
去重法则：
触发 ≠ 必须写入。每次触发时先判断：这个经验是否真正新颖？如果没什么可学的，或者本质上已经包含在已有条目中，直接跳过，不写入。避免用重复的低价值记录污染 .learnings/。
2. 经验记录系统
2.1 触发条件
检测到以下 7 种场景时，评估是否有新经验值得记录：
| # | 场景 | 记录到 | 类别 |
|---|---|---|---|
| 1 | 命令/操作失败 | ERRORS.md |
- |
| 2 | 用户纠正（"不对"/"应该是…"/"Actually…"） | LEARNINGS.md |
correction |
| 3 | 用户需要不存在的能力 | FEATURE_REQUESTS.md |
- |
| 4 | 外部 API/工具出错 | ERRORS.md |
- |
| 5 | 发现自己知识过时/错误 | LEARNINGS.md |
knowledge_gap |
| 6 | 发现了更好的做法 | LEARNINGS.md |
best_practice |
| 7 | 任务完成时 | LEARNINGS.md |
task_review |
场景 7：任务完成触发（Task Review）
每次完成一个任务后，主动回顾：
- 这次过程中踩了什么坑？
- 有没有走弯路？下次怎么做更快？
- 有没有发现新的工具用法或技巧？
- 有没有什么值得其他 agent 也知道的？
如果有真正新颖的经验 → 写入 LEARNINGS.md
如果没什么可学的，或已有条目已覆盖 → 跳过，不写入
学术场景扩展
在论文检索/分析场景中，额外关注：
- 📚 论文关键结论 — 解析出的重要发现或反直觉结论
- 🏷️ 分类决策 — 为什么把论文归入某个类别
- ⚖️ 评分依据 — review 打分时的关键判断理由
- 🔍 检索技巧 — 某个搜索策略特别有效或无效
检测关键词
纠正信号：
- "不对" / "不是" / "错了" / "应该是" / "Actually" / "No, I meant"
能力请求信号：
- "能不能…" / "有没有办法…" / "要是能…" / "Can you…"
知识空白信号：
- 用户提供了你不知道的信息
- API 行为和你的理解不一致
- 文档内容已过时
2.2 文件体系
.learnings/
├── LEARNINGS.md # 经验/纠正/最佳实践/任务回顾
├── ERRORS.md # 错误日志
├── FEATURE_REQUESTS.md # 能力请求
└── CHANGELOG.md # 操作日志（详见第 4 节）
2.3 记录格式
Learning 条目
## [LRN-YYYYMMDD-XXX] category
**Priority**: low | medium | high | critical
**Status**: pending | resolved | promoted | promoted_to_skill
**Area**: research | infra | tools | docs | config
### 内容
简述：发生了什么、为什么错/不好、正确/更好的做法是什么。
### 建议修复
具体应该怎么改、改哪里。
### 元数据
- Source: error | correction | user_feedback | task_review | best_practice
- See Also: LRN-XXXXXXXX-XXX（关联条目）
- Pattern-Key: xxx（可选，用于递归模式检测）
- Promoted-To: AGENTS.md（仅晋升后填写）
---
What ships with it
5 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.
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 · 436 lines · 206 tokens per session scan A 8502c14ed668
proactive-self-improving-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 206 tokens to every session and 4,258 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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