- name
- daily-report
- description
- >
Daily Work Report Generator
Overview
This skill automatically discovers all git repositories the user committed to, collects commit history across ALL branches, gathers CodeBuddy Agent session overviews, and generates a structured daily work report. It works cross-platform (macOS, Linux, Windows) with zero configuration required. Supports generating reports for any date (today, yesterday, or a specific date).
Step-by-Step Workflow
Step 1: Run the data collection script
Execute the bundled Python script to collect all raw data:
# Today (default)
python "SKILL_DIR/scripts/collect.py"
# Yesterday
python "SKILL_DIR/scripts/collect.py" --yesterday
# Specific date
python "SKILL_DIR/scripts/collect.py" --date 2026-03-20
# N days ago
python "SKILL_DIR/scripts/collect.py" --days-ago 3Replace SKILL_DIR with the actual path to this skill's directory (e.g., ~/.codebuddy/skills/daily-report).
Date selection rules:
- If the user says "今天" / "today" → no extra flags (default)
- If the user says "昨天" / "yesterday" → use
--yesterday - If the user says a specific date → use
--date YYYY-MM-DD - If the user says "前天" / "the day before yesterday" → use
--days-ago 2 - If the user says "N天前" → use
--days-ago N
The script will:
- Auto-detect the operating system
- Find common development directories
- Discover all git repos with commits on the target date (across ALL branches)
- Collect CodeBuddy Agent session overviews modified on the target date
- Output structured JSON to stdout
If the user has a custom config file at SKILL_DIR/references/config.yaml, the script will also read extra search directories and preferences from it.
Step 2: Parse the JSON output
The script outputs JSON with this structure:
{
"date": "2026-03-25",
"system": "Darwin",
"git_author": "username",
"repos": [
{
"path": "/path/to/repo",
"name": "repo-name",
"commits": [
{
"hash": "abc1234",
"message": "feat: add login page",
"branch": "feature/login",
"time": "2026-03-25 14:30:00"
}
],
"diff_stats": "+150 -30 across 8 files"
}
],
"agent_sessions": [
{
"session_id": "abc123",
"overview_content": "...",
"modified_time": "2026-03-25 16:00:00"
}
],
"errors": []
}Step 3: Generate the daily report
Using the collected data, generate a well-structured daily report in the user's language (default: Chinese if the user speaks Chinese, otherwise English).
Follow this structure:
Report Template
# 工作日报 - {date}
## 📊 今日概览
- 活跃仓库: {count} 个
- 总提交数: {count} 次
- 代码变更: +{additions} -{deletions}
## 🔧 项目详情
### {repo-name-1}
**分支**: {branch-names}
| 时间 | 提交说明 |
|------|---------|
| HH:MM | commit message |
**代码统计**: +{add} -{del}, {files} 个文件
### {repo-name-2}
...
## 🤖 AI 辅助工作
{Summary of Agent session overviews, grouped by project}
## 📝 今日总结
{A 2-3 sentence high-level summary of the day's work}Step 4: Save the report
Save the generated report to the user's workspace or a location they specify. Default filename: daily-report-{YYYY-MM-DD}.md
Important Notes
- The script requires only Python 3.6+ standard library and git CLI — no pip install needed.
- If the script finds no commits, inform the user and suggest checking if git author name is correct.
- If the user wants to customize search directories, guide them to edit
references/config.yaml. - Always present the report in the user's preferred language.
- When summarizing Agent sessions, focus on what was accomplished, not implementation details.
- Group related commits across repos into coherent work items when possible.