CodeBuddy 每日工作日报生成

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name: daily-report description: > Generate a daily work report by automatically discovering all git repositories the user worked on, collecting commit logs across all branches, and summarizing CodeBuddy Agent session overviews. Supports any date via --date, --yesterday, or --days-ago flags. Use this skill when the user asks to generate a daily report, work summary, daily log, 日报, 工作日报, 今日工作总结, 昨日工作总结, or any variation of "what did I do today/yesterday".

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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 3

Replace 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.