hs3180/daily-chat-review

Daily Chat Review

Review all chat histories, identify repetitive issues, and generate improvement reports.

When to Use This Skill

Use this skill for:

• Daily automated chat history review
• Identifying repetitive user requests
• Detecting common issues and errors
• Generating improvement recommendations
• Triggering offline discussions for important issues

Keywords that trigger this skill: "每日回顾", "聊天分析", "识别问题", "daily review", "pattern analysis", "chat history"

Context Variables

When invoked, you receive:

• Chat ID: Feishu chat ID (from "Chat ID: xxx")
• Message ID: Message ID (from "Message ID: xxx")
• Sender Open ID: Sender's open ID (from "Sender Open ID: xxx")

---

Core Principle

Use LLM-based analysis to identify patterns from chat history.

The LLM analyzes message patterns directly from log files, identifying:

• Repeated user requests (same question asked multiple times)
• Manual corrections (user repeatedly correcting agent's output)
• Error patterns (similar errors occurring frequently)
• Improvement opportunities (tasks that could be automated)

---

Analysis Process

Step 1: Read All Chat Logs

Read all chat log files from the logs directory:

workspace/logs/
├── oc_chat1/
│   ├── 2026-03-05.md
│   └── 2026-03-06.md
├── oc_chat2/
│   └── 2026-03-06.md
└── ...

Actions:

1. Use Glob to find all log files: workspace/logs/**/*.md
2. Read each log file with Read tool
3. Focus on recent logs (last 7 days recommended)

Step 2: Analyze Patterns

Analyze the chat history to identify:

1. Repetitive User Requests

   • Same or similar questions asked multiple times
   • Pattern: "帮我查...", "检查一下...", "看看..."
   • Frequency: 3+ occurrences indicates automation opportunity

2. Manual Corrections

   • User correcting agent's output repeatedly
   • Pattern: "不对...", "应该是...", "改成..."
   • Indicates agent behavior needs improvement

3. Error Patterns

   • Similar error messages appearing frequently
   • Pattern: "失败", "错误", "无法", "error", "failed"
   • Indicates systemic issues

4. Improvement Opportunities

   • Tasks that could be automated
   • Common workflows that could be streamlined
   • Missing features that users frequently request

Step 3: Generate Report

Create a structured analysis report:

## 📊 每日聊天回顾分析报告

**分析时间**: [Timestamp]
**分析范围**: 最近 7 天
**聊天数量**: [Number of chats analyzed]
**消息数量**: [Total messages analyzed]

---

### 🔴 重复问题 (需要关注)

#### 问题 1: [Issue Title]
- **出现次数**: X 次
- **涉及聊天**: [Chat IDs]
- **典型请求**:
  > [Example user request]

- **建议行动**:
  - [ ] 创建定时任务自动化
  - [ ] 创建 skill 简化操作
  - [ ] 创建 issue 记录需求

---

### 🟡 改进机会 (可选优化)

#### 机会 1: [Opportunity Title]
- **描述**: [Description]
- **潜在收益**: [Expected benefit]

---

### ✅ 运行良好

- [List of things working well]

---

### 📋 建议的下一步

1. **立即行动**: [High priority items]
2. **计划中**: [Medium priority items]
3. **观察**: [Low priority items]

Step 4: Send Report

CRITICAL: Always send the report to the user using send_user_feedback.

Use send_user_feedback with:
- content: [The report in markdown format]
- format: "text"
- chatId: [The chatId from context]

---

Pattern Detection Guidelines

What to Look For

| Pattern Type | Indicators | Minimum Occurrences | |--------------|------------|---------------------| | Repetitive Request | Same/similar questions | 3+ | | Manual Correction | User corrections | 2+ | | Error Pattern | Error messages | 3+ | | Feature Request | "希望能...", "如果有..." | 2+ |

What to Ignore

• One-time issues
• Personal preferences
• Context-specific requests
• Test/debug messages

---

Example Analysis

Input (Chat History Excerpt):

## [2026-03-05T09:15:00Z] 📥 User
帮我看看今天有什么新的 GitHub issues

## [2026-03-05T09:20:00Z] 📤 Bot
正在检查 issues...

## [2026-03-06T09:10:00Z] 📥 User
查看今天的 GitHub issues

## [2026-03-07T09:30:00Z] 📥 User
今天有什么新 issues 吗

Output (Report Section):

#### 问题 1: GitHub Issues 每日检查
- **出现次数**: 3 次
- **涉及聊天**: oc_xxx
- **典型请求**:
  > 帮我看看今天有什么新的 GitHub issues

- **建议行动**:
  - [x] 创建定时任务自动化 (推荐: 每天 09:00)
  - [ ] 考虑创建 skill 简化操作

---

Integration with Other Systems

Phase 1: Report Only (Current)

• Analyze chat history
• Generate report
• Send via send_user_feedback

Phase 2: Offline Discussion (Future)

• Use leave_note from offline-notes module
• Create discussion threads for important issues
• Track discussion outcomes

Phase 3: Automated Actions (Future)

• Automatically create issues for detected problems
• Create skills for repetitive tasks
• Create schedules for automation opportunities

---

Checklist

• [ ] Read all chat log files from workspace/logs/
• [ ] Analyzed patterns across all chats
• [ ] Identified at least 3 repetitive patterns (if any)
• [ ] Generated structured report
• [ ] Sent report via send_user_feedback (CRITICAL)

---

DO NOT

• Create schedules without user confirmation
• Send reports to wrong chatId
• Include sensitive information in reports
• Make assumptions about user intent
• Skip the send_user_feedback step