功能描述

持续学习 Agent - 知识沉淀和经验固化框架。支持学习记录、快速索引、自我修复、经验→模型转化。包含完整模板、索引系统、SOP 流程。让 AI Agent 持续进化，每天进步一点点。

使用说明 (SKILL.md)

Keep Learning Agent - 持续学习系统

Name: Keep Learning Agent
Author: chow651

统一的知识沉淀和经验固化系统

核心理念：学到的东西必须固化成可复用的模块和文档，而不是只存在于临时会话中

🎯 核心功能

功能	说明	文件
学习记录	统一格式记录新知识	`.learnings/LEARNINGS.md`
快速索引	按状态/类别/领域/Patter n-Key 查找	`.learnings/INDEX.md`
自我修复	会话启动自动检查 pending 项	`G:\clawbot\config\self-repair.ps1`
经验→模型	重复模式转化为思维模型	`lib/KNOWLEDGE-SOP.md`
模板系统	统一学习记录格式	`.learnings/templates/`
归档机制	定期整理已 promoted 学习	`.learnings/archive/`

📁 目录结构

.learnings/
├── README.md                    # 使用指南
├── INDEX.md                     # 快速索引（自动更新）
├── LEARNINGS.md                 # 主学习记录
├── ERRORS.md                    # 错误记录
├── FEATURE_REQUESTS.md          # 功能请求
├── INTEGRATION-REPORT.md        # 整合报告
├── TEMPLATE-ANALYSIS.md         # 模板分析报告
├── templates/
│   └── learning-template.md     # 统一模板
└── archive/                     # 已归档学习
    └── 2026-03/

lib/
├── feishu_api.py                # 可复用模块示例
├── README.md                    # 库文档
└── KNOWLEDGE-SOP.md             # 知识固化 SOP

G:\clawbot\config\
├── self-repair.ps1              # 自我修复脚本
├── autoload-configs.ps1         # 配置自动加载
└── skills-config.json           # 技能配置注册表

📝 学习记录模板

标准格式

## [LRN-YYYYMMDD-XXX] 简短标题

**Logged**: 2026-03-04T15:45:00+08:00
**Priority**: low | medium | high | critical
**Status**: new | in_progress | resolved | promoted | archived
**Category**: technical_solution | process_improvement | mindset | bug_fix | feature_request
**Area**: integration | automation | memory | api | ui | cognitive | config
**Source**: conversation | error | user_feedback | self_discovery

### 问题描述
清晰描述遇到的问题和背景

### 根因分析
用 5Why 或其他方法找到根本原因

### 解决方案
详细的解决步骤和代码

### 可复用场景
列出可以复用的场景

### 代码/脚本
可复用的代码片段或脚本位置

### 依赖
需要的库、配置、权限等

### 测试结果
测试时间、结果

### 关联
- **Related**: [LRN-XXXX-XXX](#lrn-xxxx-xxx)
- **See Also**: [文档链接](url)
- **Tags**: tag1, tag2

### Metadata
- **Pattern-Key**: unique.pattern.key
- **Recurrence-Count**: 1
- **First-Seen**: 2026-03-04
- **Last-Seen**: 2026-03-04
- **Time-Spent**: 30min
- **Skill-Path**: skills/skill-name (if promoted_to_skill)

字段说明

字段	必填	说明
Logged	✅	ISO-8601 时间戳
Priority	✅	low/medium/high/critical
Status	✅	new/in_progress/resolved/promoted/archived
Category	✅	学习类别
Area	✅	相关领域
Source	✅	学习来源
Pattern-Key	✅	唯一模式标识
Recurrence-Count	⚠️	重复次数（可选）
Time-Spent	⚠️	花费时间（可选）

🔄 状态流转

new → in_progress → resolved → promoted → archived
              ↓
          abandoned (明确不做)

状态	说明	操作
new	刚记录，未处理	安排优先级
in_progress	正在处理	更新进展
resolved	已解决，待固化	封装模块/更新文档
promoted	已提升到更高层	如写入 AGENTS.md
archived	已归档	移入 archive/
abandoned	明确不做	记录原因

🏷️ 分类体系

按优先级

优先级	说明	处理时限
critical	核心能力/生存相关	立即
high	重要功能/频繁使用	24 小时
medium	有用但不紧急	1 周
low	锦上添花	有空再做

按类别

类别	说明	示例
technical_solution	技术方案/代码实现	飞书 API 调用
process_improvement	流程优化/SOP	知识固化 SOP
mindset	思维模型/认知升级	系统思维应用
bug_fix	错误修复	配置路径问题
feature_request	新功能请求	需要 XX 能力

按领域

领域	说明
integration	外部系统集成 (飞书/Telegram/Email)
automation	自动化脚本/定时任务
memory	记忆/配置持久化
api	API 调用/封装
ui	界面/交互
cognitive	认知/思维模型
config	配置文件管理

🤖 自动化集成

会话启动流程

# 1. 读取核心文件
Read SOUL.md, AGENTS.md, MEMORY.md
Read memory/YYYY-MM-DD.md

# 2. 运行自我修复
G:\clawbot\config\self-repair.ps1

# 3. 加载配置
G:\clawbot\config\autoload-configs.ps1

# 4. 查看索引
Read .learnings/INDEX.md

self-repair.ps1 功能

# 检查 pending 学习项
# 提取 Pattern-Key
# 检查是否已应用改进
# 输出待办清单
# 提示更新 INDEX.md

定期维护

# 每周日执行
1. 检查 new 超过 3 天的 → 安排优先级
2. 检查 resolved 超过 7 天的 → 提醒封装
3. 归档已 promoted 的 → 移入 archive/
4. 更新 INDEX.md → 刷新索引

📊 索引系统

INDEX.md 提供快速查找：

# 学习索引

## 概况
| 状态 | 数量 |
|------|------|
| new | 1 |
| resolved | 9 |
| promoted | 4 |

## 按类别
- technical_solution: 3
- process_improvement: 3
- mindset: 4

## 按 Pattern-Key
- `feishu.api-direct`: LRN-20260304-009
- `memory.persistent`: LRN-20260304-008

## 待办
- [ ] LRN-20260304-012 知识固化 SOP

📈 质量指标

好的学习记录 ✅

问题描述清晰
根因分析深入（5Why）
解决方案可复用
有代码/脚本
有测试结果
Pattern-Key 唯一
状态及时更新

差的学习记录 ❌

只有问题描述
没有根因分析
无法复用
没有 Pattern-Key
状态一直是 new

🚀 快速开始

记录新学习

复制模板：.learnings/templates/learning-template.md
填写内容
追加到：.learnings/LEARNINGS.md
更新索引：.learnings/INDEX.md

查找已有学习

# 按关键词
Select-String -Path ".learnings/LEARNINGS.md" -Pattern "飞书"

# 按 Pattern-Key
Select-String -Path ".learnings/LEARNINGS.md" -Pattern "Pattern-Key:.*feishu"

# 按状态
Select-String -Path ".learnings/LEARNINGS.md" -Pattern "Status\*: resolved"

封装可复用模块

1. 解决方案验证成功
2. 创建 lib/xxx.py 模块
3. 更新 lib/README.md
4. 标记状态为 resolved
5. 更新 INDEX.md

📚 相关文档

文档	用途
`.learnings/README.md`	使用指南
`.learnings/INDEX.md`	快速索引
`.learnings/INTEGRATION-REPORT.md`	整合报告
`.learnings/TEMPLATE-ANALYSIS.md`	模板分析
`lib/KNOWLEDGE-SOP.md`	知识固化 SOP
`lib/README.md`	可复用库文档

🎓 设计原则

单一来源 - 只有一个 LEARNINGS.md
统一格式 - 所有学习用同一模板
可查找 - INDEX.md 提供快速索引
可操作 - self-repair 自动检查 pending 项
定期整理 - 每周/每月归档
可复用 - 封装成 lib/ 模块

📝 版本历史

版本	日期	变更
1.0.0	2026-03-04	初始版本，融合 self-improving-agent + 小咪特色

创建原因：阿 sir 教导「学到的东西应该固化成标准化经验方法」
作者：小咪 (XiaoMi)
最后更新：2026-03-04

安全使用建议

This skill may be useful, but exercise caution before enabling it system-wide. Actionable steps: 1) Verify the skill's source (author unknown) and prefer a trusted origin. 2) Inspect any referenced host scripts before running them (G:\clawbot\config\self-repair.ps1, autoload-configs.ps1) — open them and confirm they do only the expected checks/updates and do not send data to external endpoints. 3) Check files the skill will read (SOUL.md, AGENTS.md, MEMORY.md, skills-config.json) for sensitive information; back them up before running. 4) Run the skill in an isolated/test environment (or sandbox) first. 5) Confirm what external integrations (Feishu, Telegram, Email) are actually used and require credentials; only provide minimal, scoped credentials and preferably service accounts with limited permissions. 6) If you plan to allow automatic invocation, require the author to explicitly document why access to global paths is needed and to supply a safe, auditable self-repair script. If you cannot inspect the referenced scripts or verify their behavior, do not enable the skill on production systems.

功能分析

Type: OpenClaw Skill Name: keep-learning-agent Version: 1.0.0 The skill instructs the AI agent to execute external PowerShell scripts located at absolute paths (`G:\clawbot\config\self-repair.ps1`, `G:\clawbot\config\autoload-configs.ps1`) during its session startup and usage flows, as detailed in `SKILL.md` and `README.md`. While the stated purpose of these scripts (self-repair, config loading) appears benign, relying on and instructing the execution of external, non-skill-contained scripts via absolute paths represents a significant vulnerability. This could lead to arbitrary command execution if the external scripts are compromised or if the `G:\clawbot\config` directory is not adequately secured, making the skill suspicious.

能力评估

⚠ Purpose & Capability

The skill claims to be a knowledge/learning framework, which is reasonable. However its instructions reference absolute system paths (G:\clawbot\config\self-repair.ps1, autoload-configs.ps1) and files outside the skill directory (SOUL.md, AGENTS.md, MEMORY.md, skills-config.json). Those global, system-level accesses are not described in the high-level purpose and suggest the skill expects access to the host's configuration and other skills' state — a capability that is disproportionate to a simple templating/indexing feature.

⚠ Instruction Scope

SKILL.md explicitly instructs the agent to read many external files and run PowerShell scripts (e.g., run G:\clawbot\config\self-repair.ps1, load G:\clawbot\config\autoload-configs.ps1, read SOUL.md/AGENTS.md/MEMORY.md) and to run Python indexing scripts. Those actions allow reading arbitrary files and executing arbitrary code on the host, which is broader than the skill's stated purpose and creates risk (possible exposure of sensitive data or unwanted system changes).

ℹ Install Mechanism

This is an instruction-only skill (no install spec, no code files bundled that would be executed on install), which reduces installation risk. The _meta.json lists dependencies (powershell, python3, requests) but there is no automated installer or external downloads declared. Absence of an install step is lower risk, but the skill still instructs execution of host scripts.

⚠ Credentials

The skill declares no required environment variables or credentials, yet references integration points (feishu_api.py, mentions Feishu/Telegram/Email integrations) that normally require API keys/tokens. It also targets global config files (skills-config.json) and memory files which may contain secrets or other skills' credentials. The lack of declared credentials combined with expected external integrations and filesystem access is disproportionate and unclear.

⚠ Persistence & Privilege

always:false and normal autonomous invocation are set (no excessive platform privilege). However the skill instructs use of autoload scripts and a self-repair script located in a global config directory — behavior that can alter or rely on host-wide configuration. That raises persistence/privilege concerns if those scripts modify global state or other skills' registration (skills-config.json).

版本历史

v1.0.0

Initial release of keep-learning-agent: a standardized framework for knowledge solidification and continuous self-improvement. - Provides a unified system for logging, indexing, and refining learning experiences. - Includes SOP templates, quick indexing, issue state flows, and self-repair automation scripts. - Supports modularization of recurring solutions and easy archiving of promoted learnings. - Features Powershell integration for routine checks and maintenance. - Enables efficient organization and rapid retrieval of technical and process knowledge.

元数据

Slug keep-learning-agent

版本 1.0.0

许可证 —

累计安装 10

当前安装数 10

历史版本数 1

常见问题

Keep Learning Agent 是什么？

持续学习 Agent - 知识沉淀和经验固化框架。支持学习记录、快速索引、自我修复、经验→模型转化。包含完整模板、索引系统、SOP 流程。让 AI Agent 持续进化，每天进步一点点。它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 1192 次。

如何安装 Keep Learning Agent？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install keep-learning-agent」即可一键安装，无需额外配置。

Keep Learning Agent 是免费的吗？

是的，Keep Learning Agent 完全免费（开源免费），可自由下载、安装和使用。

Keep Learning Agent 支持哪些平台？

Keep Learning Agent 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。

谁开发了 Keep Learning Agent？

由 chow651（@chow651）开发并维护，当前版本 v1.0.0。

Keep Learning Agent