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Auto backup before evolver run - 2026年 03月 11日 星期三 19:02:28 CST

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This commit is contained in:
starmen1265
2026-03-11 19:02:28 +08:00
parent 9cc795ef20
commit 339b7d89f9
75 changed files with 11182 additions and 456 deletions
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agents/haonan/sessions/sessions.json
+222 -126
View File
@@ -1,7 +1,7 @@
{
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@@ -59,11 +59,11 @@
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agents/haonan/workspace/memory/2026-03-10-1428.md
+240
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@@ -0,0 +1,240 @@
# Session: 2026-03-10 14:28:04 UTC
- **Session Key**: agent:haonan:main
- **Session ID**: cbd04f7a-3004-47f5-b8ac-4e2e2f049125
- **Source**: feishu
## Conversation Summary
assistant: 先提交修改：
assistant: 已推送分支，PR 地址：http://192.168.1.22:8418/starmen1265/kb-skills/compare/main...fix/ci-deploy-reset
---
**关于 OpenClaw 技能机制：**
根据系统提示中的说明，技能是**按需加载**的：
1. **启动时只扫描描述** — 代理只读取每个技能的 `<description>` 字段，不加载完整内容
2. **任务匹配才读取** — 只有当任务描述匹配某个技能时，才读取该技能的 `SKILL.md`
3. **单技能加载** — 一次最多只读取一个技能文件，不会全部加载
所以**不用担心技能过多占用上下文**。
**技能放置位置：**
| 位置 | 作用范围 |
|------|----------|
| `~/.openclaw/skills/` | 全局技能，所有代理可用 |
| `~/.openclaw/agents/<name>/workspace/skills/` | 代理专属技能 |
当前 `kb-skills` 部署到 `knowledge-base` 代理的 `workspace/skills/` 是合理的——这些技能专门为知识库工作流设计。
如果想**跨代理共享**，可以放到 `~/.openclaw/skills/`。需要我帮你调整部署目标吗？
user: Conversation info (untrusted metadata):
```json
{
"message_id": "om_x100b55da411e7ca0c34a7544ccafd9d",
"sender_id": "ou_be83febac9ee2afaa343c642bc697c48",
"sender": "张青",
"timestamp": "Mon 2026-03-09 23:02 GMT+8"
}
```
Sender (untrusted metadata):
```json
{
"label": "张青 (ou_be83febac9ee2afaa343c642bc697c48)",
"id": "ou_be83febac9ee2afaa343c642bc697c48",
"name": "张青"
}
```
[message_id: om_x100b55da411e7ca0c34a7544ccafd9d]
张青: 那如果后面kb-技能可能会有多个agent会使用，是不是应该放到~/.openclaw/skills更合适？
assistant: 是的，如果多个代理需要使用，放到 `~/.openclaw/skills/` 更合适：
**优点：**
- 避免重复部署到多个代理目录
- 统一管理，一处更新全局生效
- 所有代理（包括 haonan、knowledge-base 等）都能访问
**调整方案：**
修改 CI 部署目标：
```yaml
# 从
cd /home/starmen1265/.openclaw/agents/knowledge-base/workspace/skills
# 改为
cd /home/starmen1265/.openclaw/skills
```
但需要注意：全局技能目录已有其他技能（capability-evolver、clawlist 等），kb-skills 的文件会混在一起。
**建议结构：**
```
~/.openclaw/skills/
├── capability-evolver/
├── clawlist/
├── kb-bilibili-metadata/ # 直接放技能目录
├── kb-bilibili-content/
├── kb-workflow/
└── ...
```
而不是克隆整个 `kb-skills` 仓库。这意味着 CI 需要改成**复制技能文件**而不是 `git reset`。
需要我修改 CI 配置来实现这个方案吗？
user: Conversation info (untrusted metadata):
```json
{
"message_id": "om_x100b55da5cf1c8b0c36c6f5a7d20783",
"sender_id": "ou_be83febac9ee2afaa343c642bc697c48",
"sender": "张青",
"timestamp": "Mon 2026-03-09 23:03 GMT+8"
}
```
Sender (untrusted metadata):
```json
{
"label": "张青 (ou_be83febac9ee2afaa343c642bc697c48)",
"id": "ou_be83febac9ee2afaa343c642bc697c48",
"name": "张青"
}
```
[message_id: om_x100b55da5cf1c8b0c36c6f5a7d20783]
张青: 修改CI
assistant: 已更新并推送。
**变更内容：**
- 部署目标从 `~/.openclaw/agents/knowledge-base/workspace/skills/` 改为 `~/.openclaw/skills/`
- 使用 `rsync --delete` 同步，确保本地与仓库一致
- 每次部署使用临时目录，避免 git 冲突
**PR 地址：** http://192.168.1.22:8418/starmen1265/kb-skills/compare/main...fix/ci-deploy-reset
合并后，所有代理都能使用这些技能了。
user: Conversation info (untrusted metadata):
```json
{
"message_id": "om_x100b55da763144a0b20ad1c942e1fe2",
"sender_id": "ou_be83febac9ee2afaa343c642bc697c48",
"sender": "张青",
"timestamp": "Mon 2026-03-09 23:13 GMT+8"
}
```
Sender (untrusted metadata):
```json
{
"label": "张青 (ou_be83febac9ee2afaa343c642bc697c48)",
"id": "ou_be83febac9ee2afaa343c642bc697c48",
"name": "张青"
}
```
[message_id: om_x100b55da763144a0b20ad1c942e1fe2]
张青: 知识库技能有一点问题，我发的知乎链接，分析的时候好像是找到别的链接去了。好像是操作过程中链接需要写入文件，每次都写死了，检查一下相关逻辑，以下是操作过程：
[https://zhuanlan.zhihu.com/p/2013919514258072086](https://zhuanlan.zhihu.com/p/2013919514258072086) 添加到知识库
好的，我来执行知识库添加工作流。这是一个知乎专栏文章链接。
环境变量检查通过！开始执行工作流。
链接解析成功！类型：知乎专栏文章
文章内容提取成功！标题：开源神器——分分钟爬取小红书、抖音、微博、知乎了！
内容已成功提取！让我手动构建元数据并重新运行深度分析：
深度分析正在运行中，请稍候...
深度分析完成！正在归档...
蒋先生，知识库添加完成！
文章信息：
\- 标题： 开源神器——分分钟爬取小红书、抖音、微博、知乎了！
\- 作者： 太阳鸟
\- 平台： 知乎专栏
\- 链接： [https://zhuanlan.zhihu.com/p/2013919514258072086](https://zhuanlan.zhihu.com/p/2013919514258072086)
处理结果：
\- ✅ 链接解析
\- ✅ 元数据提取
\- ✅ 内容提取
\- ✅ 深度分析（耗时 121.77秒）
\- ✅ 归档到工作区
\- ✅ 同步到NAS
归档位置：
\~/work/zq/30.资源/AI分析/2026\-03\-09/[zhihu\_2013919514258072086.md](http://zhihu_2013919514258072086.md/)
AI分析标签： Python爬虫、数据采集、自动化工具、自媒体运营
assistant: 让我检查相关技能的逻辑：
assistant: 找到问题了！
**问题根源：**
`zhihu_content.py` 的 `read_article_from_mediacrawler` 方法在**没有指定 `--input` 参数**时，会**自动查找最新的数据文件**：
```python
# 查找最新的数据文件
json_files = sorted(data_dir.glob("detail_contents_*.json"), reverse=True)
json_file = json_files[0] # 直接用最新的
```
这意味着：
1. 如果之前有其他知乎文章的爬取数据
2. 新的爬取还没完成或覆盖
3. 就会读取到**旧的数据**
让我检查工作流中知乎文章的调用顺序：
assistant: 确认了！MediaCrawler 数据目录中的旧数据是 **2月27日** 爬取的（"开源神器——分分钟爬取小红书、抖音、微博、知乎了！"），而你发送的是新链接。
**问题分析：**
工作流处理知乎专栏时：
1. 没有先调用 `zhihu_article_crawler.py` 爬取新 URL
2. 直接调用 `zhihu_content.py --type article-from-media` 读取了**旧数据**
让我检查并修复这个问题：
assistant: 找到问题了！
**根本原因：**
1. SKILL.md 中写的是 `zhihu_content.py --type zhuanlan`，但这个类型**不存在**
2. 实际支持的类型只有 `video`, `subtitle`, `article-from-media`
3. 对于知乎专栏，正确流程应该是：
- 先调用 `zhihu_article_crawler.py --url "[URL]"` 爬取
- 然后用 `--input` 指定刚生成的文件读取
**修复方案：**
assistant: 我来修复这个问题。有两个方案：
1. **修改 SKILL.md**：更新流程文档
2. **修改 zhihu_content.py**：添加 `zhuanlan` 类型，内部自动调用 crawler
我选择方案2，这样工作流调用更简单：
assistant: 现在更新 SKILL.md，明确知乎专栏的处理流程：
assistant: 已修复并推送。
**问题总结：**
1. 工作流调用 `zhihu_content.py --type zhuanlan`，但该类型不存在
2. 实际调用的是 `article-from-media`，会读取**最新的旧数据**而不是爬取新 URL
**修复内容：**
1. **zhihu_content.py**：添加 `zhuanlan` / `article` 类型支持
- 内部自动调用 `zhihu_article_crawler.py` 爬取新 URL
- 不再依赖旧数据
2. **SKILL.md**：更新知乎专栏处理流程文档
**PR 地址：** http://192.168.1.22:8418/starmen1265/kb-skills/compare/main...fix/ci-deploy-reset
合并后，工作流调用：
```bash
python3 zhihu_content.py --id "2013919514258072086" --type zhuanlan --output [content_dir]
```
会自动爬取正确的文章。
assistant: **备份完成** ✅
- 备份文件：`openclaw.json.2026-03-10_03-00-13`
- 存放位置：`/home/starmen1265/work/backup/`
- 文件大小：8660 字节
- 历史备份：正常运行，保留最近 5 天的备份
agents/knowledge-base/workspace/memory/2026-03-10-1421.md
+551
View File
@@ -0,0 +1,551 @@
# Session: 2026-03-10 14:21:16 UTC
- **Session Key**: agent:knowledge-base:main
- **Session ID**: f34ed61f-bbb7-4603-a559-13e18948c463
- **Source**: feishu
## Conversation Summary
assistant: **AI 对话记录整理完成** 📊
**处理日期：** 2026-03-09（昨天）
**整理结果：**
| 代理 | 消息数 | 主要标签 |
|------|--------|----------|
| haonan | 95 条 | AI/LLM, OpenClaw, 任务规划, 定时任务, 技术探讨 |
| ui-designer | 22 条 | AI/LLM, OpenClaw, 任务规划, 定时任务, 技术探讨 |
| knowledge-base | 13 条 | AI/LLM, OpenClaw, iOS/Apple, 任务规划, 定时任务 |
| dev-assist | 13 条 | AI/LLM, iOS/Apple, 定时任务, 游戏开发, 编程开发 |
| thinker | - | 已更新汇总 |
**执行状态：**
- ✅ 从 NAS 同步完成
- ✅ 5 个代理的对话汇总已更新
- ✅ 已提交到 Git
- ✅ 已推送到 NAS
user: Conversation info (untrusted metadata):
```json
{
"message_id": "om_x100b55c8f6c33084c4ae83f815ca93a",
"sender_id": "ou_9351c287f42069fa30366ac641d24df7",
"sender": "张青",
"timestamp": "Tue 2026-03-10 15:42 GMT+8"
}
```
Sender (untrusted metadata):
```json
{
"label": "张青 (ou_9351c287f42069fa30366ac641d24df7)",
"id": "ou_9351c287f42069fa30366ac641d24df7",
"name": "张青"
}
```
[message_id: om_x100b55c8f6c33084c4ae83f815ca93a]
张青: 帮我润色一下工作区中 虚幻5.6 IOS平台使用源码引擎打包 这篇文章，记的先同步再修改，修改完再同步到Nas
assistant: **✅ 文章已润色并同步到 NAS**
**主要改进：**
| 方面 | 改进内容 |
|------|----------|
| **结构** | 添加清晰的章节编号（一~十一），层次分明 |
| **格式** | 使用表格展示环境要求、证书文件说明 |
| **代码块** | 命令行操作使用代码块，便于复制 |
| **提示** | 添加 💡 提示、⚠️ 注意事项、📝 待补充标记 |
| **语言** | 统一术语，语句更流畅 |
| **新增** | 添加"常见问题"章节 |
**文件位置：** `10.项目/11-墨犬/A.草稿/虚幻5.6 IOS平台使用源码引擎打包.md`
user: Conversation info (untrusted metadata):
```json
{
"message_id": "om_x100b55c94f40d0a8c3a72377f9075f1",
"sender_id": "ou_9351c287f42069fa30366ac641d24df7",
"sender": "张青",
"timestamp": "Tue 2026-03-10 16:02 GMT+8"
}
```
Sender (untrusted metadata):
```json
{
"label": "张青 (ou_9351c287f42069fa30366ac641d24df7)",
"id": "ou_9351c287f42069fa30366ac641d24df7",
"name": "张青"
}
```
[message_id: om_x100b55c94f40d0a8c3a72377f9075f1]
张青: 我又补充了一些内容，帮我加上Obsidian支持的tag
assistant: **✅ 已添加 Obsidian tags 并同步到 NAS**
```yaml
---
tags: [UE5, iOS, 打包, macOS, Xcode, Apple开发者, 源码引擎]
---
```
**文件位置：** `10.项目/11-墨犬/MAC+IOS平台开发/虚幻5.6 IOS平台使用源码引擎打包.md`
user: Conversation info (untrusted metadata):
```json
{
"message_id": "om_x100b55cb9504f8a8b2c9f5ffe5c2723",
"sender_id": "ou_9351c287f42069fa30366ac641d24df7",
"sender": "张青",
"timestamp": "Tue 2026-03-10 19:17 GMT+8"
}
```
Sender (untrusted metadata):
```json
{
"label": "张青 (ou_9351c287f42069fa30366ac641d24df7)",
"id": "ou_9351c287f42069fa30366ac641d24df7",
"name": "张青"
}
```
[message_id: om_x100b55cb9504f8a8b2c9f5ffe5c2723]
张青: 能把润色我的知识库中的某个文档这个功能做成一个命令吗？ 我们讨论一下如何实现，先不要着急去改
assistant: 好的，我们先讨论一下。让我先看看现有的知识库相关技能是怎么实现的：
assistant: 好的，我已经看了现有的 `kb-workflow` skill。让我分析一下需求和几个可行方案：
---
## 📋 需求分析
**现有 kb-workflow**：处理"链接 → 下载 → 分析 → 归档"的完整流程
**新需求（润色功能）**：处理"文档路径 → 同步 → 润色 → 同步"的简单流程
两者差异较大，不适合合并。
---
## 🎯 方案对比
| 方案 | 实现方式 | 优点 | 缺点 |
|------|----------|------|------|
| **A. 新建 skill** | `kb-polish` 独立技能 | 独立清晰、可定制润色规则 | 需要新建文件 |
| **B. 扩展 kb-workflow** | 在现有 skill 中添加分支 | 复用基础设施 | 会让 kb-workflow 变臃肿 |
| **C. 纯命令** | 直接在 AGENTS.md 中定义规则 | 简单快速 | 没有 skill 的结构化流程 |
**推荐方案 A**：创建独立的 `kb-polish` skill
---
## 📝 方案 A 详细设计
### 触发方式
| 触发词 | 示例 |
|--------|------|
| `润色 + 路径` | "润色 10.项目/11-墨犬/A.草稿/xxx.md" |
| `润色文档 + 路径` | "润色文档 虚幻5.6 IOS" |
| `/润色 + 路径` | "/润色 xxx.md" |
支持模糊匹配：如果路径不完整，先搜索知识库找到匹配的文件
### 工作流程
```
1. 解析文档路径（支持模糊搜索）
↓
2. 从 NAS 同步到本地
↓
3. 读取文档内容
↓
4. AI 润色处理
- 格式规范化（标题层级、列表、表格）
- 添加/更新 Obsidian frontmatter（tags）
- 语言润色（语句通顺、术语统一）
- 结构优化（可选）
↓
5. 写入润色后的内容
↓
6. 同步到 NAS
↓
7. 汇报完成
```
### 可配置选项
用户可以在命令中指定润色程度：
| 选项 | 说明 |
|------|------|
| `--light` | 轻度润色（只修格式和错字） |
| `--full` | 完整润色（格式 + 语言 + 结构） |
| `--tags` | 只添加/更新 tags |
| `--structure` | 只优化结构 |
示例：
- "润色 xxx.md --light"
- "润色 xxx.md 只要格式化"
### 文件结构
```
~/.openclaw/skills/kb-polish/
├── SKILL.md # 技能说明
└── polish_prompt.md # 润色提示词模板（可选）
```
---
## ❓ 需要讨论的问题
1. **触发词**：你喜欢哪种方式？
- `润色 xxx.md`（自然语言）
- `/润色 xxx.md`（命令式）
- 两者都支持
2. **润色程度**：默认是轻度还是完整润色？
3. **是否需要确认**：润色前是否先预览让用户确认？
- 直接润色（快）
- 先展示改动摘要，用户确认后再保存（安全）
4. **是否支持批量**：比如 "润色整个文件夹"？
5. **备份策略**：润色前是否自动创建备份？
你觉得这个设计怎么样？有哪些地方需要调整？
user: Conversation info (untrusted metadata):
```json
{
"message_id": "om_x100b55cbbae020a0b2ea55209015eba",
"sender_id": "ou_9351c287f42069fa30366ac641d24df7",
"sender": "张青",
"timestamp": "Tue 2026-03-10 19:23 GMT+8"
}
```
Sender (untrusted metadata):
```json
{
"label": "张青 (ou_9351c287f42069fa30366ac641d24df7)",
"id": "ou_9351c287f42069fa30366ac641d24df7",
"name": "张青"
}
```
[message_id: om_x100b55cbbae020a0b2ea55209015eba]
张青: 不是知识库技能，现在没有专门的润色技能，都是我单独说明的，所以应该是一个新技能，叫工作区维护吧。继续讨论
assistant: 明白了，是独立的"工作区维护"技能。让我重新梳理：
---
## 📋 技能定位
**名称**：`workspace-maint`（工作区维护）
**适用场景**：对 `~/work/zq/` 工作区的文档进行各种维护操作
**与现有技能的关系**：
- `kb-workflow`：处理外部链接 → 知识库归档
- `workspace-maint`：处理工作区内文档的维护
---
## 🎯 功能范围讨论
除了"润色文档"，工作区维护还可能包含哪些操作？
| 功能 | 说明 | 优先级 |
|------|------|--------|
| **润色文档** | 格式化、语言优化、添加tags | 核心功能 |
| **移动文档** | 移动文件并同步到NAS | 常用 |
| **重命名文档** | 重命名并同步 | 常用 |
| **整理目录** | 清理空目录、重命名不规范文件 | 偶尔 |
| **查重/合并** | 发现重复文档、合并相似内容 | 偶尔 |
| **格式转换** | 比如把txt转md | 偶尔 |
| **检查链接** | 检查文档中的链接是否有效 | 少用 |
**问题1**：你希望这个技能覆盖哪些功能？先只做"润色"，还是一次性规划多个？
---
## 📝 润色功能的细化
**问题2**：润色的默认行为是什么？
| 选项 | 行为 |
|------|------|
| A. 格式优先 | 默认只做格式化（标题、列表、表格、代码块） |
| B. 全面润色 | 默认做格式 + 语言优化 + 结构调整 |
| C. 最小改动 | 默认只修复明显问题，保持原样为主 |
**问题3**：Obsidian tags 处理？
| 选项 | 行为 |
|------|------|
| A. 自动生成 | AI 根据内容自动生成 tags |
| B. 保留现有 | 有 tags 就保留，没有就生成 |
| C. 需要指定 | 用户明确说"加tags"才处理 |
**问题4**：执行前是否确认？
| 选项 | 行为 |
|------|------|
| A. 直接执行 | 同步 → 润色 → 同步，不问 |
| B. 预览确认 | 先展示改动要点，用户确认后再保存 |
| C. 智能判断 | 小改动直接执行，大改动先确认 |
---
## 🔄 同步策略
工作区的同步流程：
```
rclone sync "nas-webdav:...工作区/" ~/work/zq/ # 先拉取
# ... 操作 ...
rclone copy/ sync ~/work/zq/ "nas-webdav:..." # 再推送
```
**问题5**：同步粒度
| 选项 | 行为 |
|------|------|
| A. 全量同步 | 每次操作前后都 sync 整个工作区 |
| B. 单文件同步 | 只 sync 操作的那一个文件 |
| C. 可配置 | 默认单文件，用户说"全量"才全量 |
---
## 💬 触发方式
你更习惯哪种表达？
```
润色 10.项目/xxx/文档.md
润色文档 虚幻5.6
/润色 xxx.md
维护文档 xxx.md --polish
```
---
你先回答这几个问题，我们再细化设计。
user: Conversation info (untrusted metadata):
```json
{
"message_id": "om_x100b543442e8b8a4b49498476ddbc9e",
"sender_id": "ou_9351c287f42069fa30366ac641d24df7",
"sender": "张青",
"timestamp": "Tue 2026-03-10 19:30 GMT+8"
}
```
Sender (untrusted metadata):
```json
{
"label": "张青 (ou_9351c287f42069fa30366ac641d24df7)",
"id": "ou_9351c287f42069fa30366ac641d24df7",
"name": "张青"
}
```
[message_id: om_x100b543442e8b8a4b49498476ddbc9e]
张青: 1目前只需要润色功能
2全面润色
3保留现有
4预览确认
5全量同步
assistant: 明确了！总结一下设计要点：
| 项目 | 决定 |
|------|------|
| 功能范围 | 只有润色（后续可扩展） |
| 润色程度 | 全面润色（格式 + 语言 + 结构） |
| Tags 处理 | 保留现有，没有才生成 |
| 执行确认 | 预览 → 确认 → 保存 |
| 同步策略 | 全量同步 |
---
## 📝 技能设计 v1
### 基本信息
```
名称：workspace-maint
描述：工作区文档润色维护
触发：润色 + 文档路径
```
### 工作流程
```
1. 解析文档路径（支持模糊搜索）
↓
2. 全量同步：NAS → 本地
↓
3. 读取文档内容
↓
4. AI 全面润色（格式 + 语言 + 结构）
- 保留现有 tags，没有才生成
↓
5. 【预览确认】
- 展示改动要点摘要
- 用户确认后继续
↓
6. 写入润色后内容
↓
7. 全量同步：本地 → NAS
↓
8. 汇报完成
```
### 触发方式
| 触发词 | 示例 |
|--------|------|
| `润色 + 路径` | 润色 10.项目/11-墨犬/xxx.md |
| `润色文档 + 关键词` | 润色文档 虚幻5.6 |
支持模糊匹配：输入部分路径或关键词，先搜索定位文件
### 预览确认格式
```
📄 文档：虚幻5.6 IOS平台使用源码引擎打包.md
📋 改动预览：
- 格式：添加章节编号、规范代码块
- 结构：拆分过长的段落、调整章节顺序
- 语言：修正3处表述、统一术语
- Tags：保留现有 [UE5, iOS, 打包...]
确认润色？(y/n)
```
### 文件结构
```
~/.openclaw/skills/workspace-maint/
└── SKILL.md # 技能说明（润色提示词直接写在里面）
```
---
## ❓ 最后几个细节
1. **文件类型限制**：只处理 `.md` 文件？还是也支持 `.txt`？
2. **大文件处理**：如果文档很长（比如超过 5000 字），是：
- A. 照常处理
- B. 提示用户文档较长，润色可能需要更多时间
- C. 分段润色
3. **拒绝润色的情况**：比如文件正在被其他程序编辑，如何处理？
4. **技能名称**：`workspace-maint` 还是 `ws-polish` 或其他？
user: Conversation info (untrusted metadata):
```json
{
"message_id": "om_x100b54346c189cbcb27a8596d8ca448",
"sender_id": "ou_9351c287f42069fa30366ac641d24df7",
"sender": "张青",
"timestamp": "Tue 2026-03-10 19:36 GMT+8"
}
```
Sender (untrusted metadata):
```json
{
"label": "张青 (ou_9351c287f42069fa30366ac641d24df7)",
"id": "ou_9351c287f42069fa30366ac641d24df7",
"name": "张青"
}
```
[message_id: om_x100b54346c189cbcb27a8596d8ca448]
张青: 1.只处理md
2.分段润色
3.汇报
4.ws-maint
5.流程调整一下，必须先同步到本地再进行操作
6.触发方式为润色 xxx 或者/润色 xxx
assistant: 好的，最终设计确认：
---
## ✅ 最终设计
| 项目 | 决定 |
|------|------|
| 技能名称 | `ws-maint` |
| 文件类型 | 只处理 `.md` |
| 大文件 | 分段润色 |
| 异常处理 | 汇报问题，不强行操作 |
| 触发方式 | `润色 xxx` 或 `/润色 xxx` |
### 流程
```
1. 全量同步：NAS → 本地（必须先执行）
↓
2. 解析文档路径（支持模糊搜索）
↓
3. 读取文档内容
↓
4. AI 全面润色（格式 + 语言 + 结构）
- 保留现有 tags，没有才生成
- 大文件分段润色
↓
5. 【预览确认】
- 展示改动要点摘要
- 用户确认后继续
↓
6. 写入润色后内容
↓
7. 全量同步：本地 → NAS
↓
8. 汇报完成
```
---
设计确认完毕，我现在创建这个技能：
assistant: **✅ 技能已创建**
```
~/.openclaw/skills/ws-maint/SKILL.md
```
---
## 📋 技能总结
| 项目 | 内容 |
|------|------|
| 名称 | `ws-maint` |
| 触发 | `润色 xxx` 或 `/润色 xxx` |
| 文件类型 | 仅 `.md` |
| 润色范围 | 格式 + 语言 + 结构 + tags（保留现有） |
| 大文件 | 分段润色 |
| 确认方式 | 预览改动 → 用户确认 → 保存 |
| 同步 | 全量同步（先拉后推） |
---
## 🧪 测试方法
你现在可以用以下命令测试：
```
润色 虚幻5.6
```
或者
```
/润色 10.项目/11-墨犬/MAC+IOS平台开发/虚幻5.6
```
要现在测试一下吗？
agents/knowledge-base/workspace/~/work/knowledge-base/data/zhihu/zhihu_article_VS Code 1111 炸了自动驾驶Autopilot模式上线这是要干掉 Cursor.md
+22
View File
File diff suppressed because one or more lines are too long
agents/thinker/sessions/sessions.json
+13 -13
View File
@@ -1,7 +1,7 @@
{
"agent:thinker:main": {
"sessionId": "d82ad1e3-616a-40a5-8e3f-0838350ea7ed",
"updatedAt": 1772983283136,
"sessionId": "47c5dafb-3869-4029-aa6d-096113520af6",
"updatedAt": 1773141690645,
"systemSent": true,
"abortedLastRun": false,
"chatType": "direct",
@@ -22,7 +22,7 @@
"to": "user:ou_a0f6627b64d2dc8b0236671603d1e47b",
"accountId": "feishu-qa"
},
"sessionFile": "/home/starmen1265/.openclaw/agents/thinker/sessions/d82ad1e3-616a-40a5-8e3f-0838350ea7ed.jsonl",
"sessionFile": "/home/starmen1265/.openclaw/agents/thinker/sessions/47c5dafb-3869-4029-aa6d-096113520af6.jsonl",
"compactionCount": 0,
"skillsSnapshot": {
"prompt": "\n\nThe following skills provide specialized instructions for specific tasks.\nUse the read tool to load a skill's file when the task matches its description.\nWhen a skill file references a relative path, resolve it against the skill directory (parent of SKILL.md / dirname of the path) and use that absolute path in tool commands.\n\n<available_skills>\n <skill>\n <name>capability-evolver</name>\n <description>A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.</description>\n <location>~/.openclaw/skills/capability-evolver/SKILL.md</location>\n </skill>\n</available_skills>",
@@ -51,8 +51,8 @@
"model": "glm-5",
"systemPromptReport": {
"source": "run",
"generatedAt": 1772983263029,
"sessionId": "d82ad1e3-616a-40a5-8e3f-0838350ea7ed",
"generatedAt": 1773141599130,
"sessionId": "47c5dafb-3869-4029-aa6d-096113520af6",
"sessionKey": "agent:thinker:main",
"provider": "zhipu",
"model": "glm-5",
@@ -64,8 +64,8 @@
"sandboxed": false
},
"systemPrompt": {
"chars": 24613,
"projectContextChars": 12137,
"chars": 24896,
"projectContextChars": 12420,
"nonProjectContextChars": 12476
},
"injectedWorkspaceFiles": [
@@ -73,8 +73,8 @@
"name": "AGENTS.md",
"path": "/home/starmen1265/.openclaw/agents/thinker/workspace/AGENTS.md",
"missing": false,
"rawChars": 9264,
"injectedChars": 9264,
"rawChars": 9547,
"injectedChars": 9547,
"truncated": false
},
{
@@ -352,12 +352,12 @@
]
}
},
"cacheRead": 16000,
"cacheRead": 42752,
"cacheWrite": 0,
"totalTokensFresh": true,
"contextTokens": 200000,
"inputTokens": 1688,
"outputTokens": 551,
"totalTokens": 16533
"inputTokens": 35428,
"outputTokens": 1950,
"totalTokens": 46250
}
}
agents/ui-designer/sessions/sessions.json
-38
View File
@@ -405,43 +405,5 @@
"totalTokensFresh": true,
"cacheRead": 441088,
"cacheWrite": 0
},
"agent:ui-designer:cron:78b64c2f-7f91-47ff-9250-d13f546eb21f:run:03e44b46-c707-4a9f-bf3d-1818aafdcde2": {
"sessionId": "03e44b46-c707-4a9f-bf3d-1818aafdcde2",
"updatedAt": 1773108000044,
"systemSent": true,
"label": "Cron: 房价月度监控",
"skillsSnapshot": {
"prompt": "\n\nThe following skills provide specialized instructions for specific tasks.\nUse the read tool to load a skill's file when the task matches its description.\nWhen a skill file references a relative path, resolve it against the skill directory (parent of SKILL.md / dirname of the path) and use that absolute path in tool commands.\n\n<available_skills>\n <skill>\n <name>capability-evolver</name>\n <description>A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.</description>\n <location>~/.openclaw/skills/capability-evolver/SKILL.md</location>\n </skill>\n</available_skills>",
"skills": [
{
"name": "capability-evolver"
}
],
"skillFilter": [
"capability-evolver",
"self-improving-agent"
],
"resolvedSkills": [
{
"name": "capability-evolver",
"description": "A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution.",
"filePath": "/home/starmen1265/.openclaw/skills/capability-evolver/SKILL.md",
"baseDir": "/home/starmen1265/.openclaw/skills/capability-evolver",
"source": "openclaw-managed",
"disableModelInvocation": false
}
],
"version": 0
},
"modelProvider": "zhipu",
"model": "glm-5",
"contextTokens": 200000,
"inputTokens": 45485,
"outputTokens": 5796,
"totalTokens": 56068,
"totalTokensFresh": true,
"cacheRead": 441088,
"cacheWrite": 0
}
}