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work-summary工作总结

Agent Skill

work-summary 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

372

周安装

16

GitHub Stars

公开资料未说明

下载量

131
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:work-summary(工作总结)
来源仓库:https://github.com/xiaomi/mone
仓库路径:skills/work-summary
安装命令:
npx skills add xiaomi/mone --skill "work-summary"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add xiaomi/mone --skill "work-summary"

简介

用于发现并安装 AI 代理技能的通用工具。

  • 适用于工作总结类任务自动化处理场景。work-summary 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 支持按时间维度聚合信息与关键事件提取。
  • 安装命令:npx skills add xiaomi/mone --skill "work-summary"。
  • 需确认输入数据来源权限与隐私合规要求。

SKILL.md

name
work-summary
description
Generate performance review summaries from git repositories by analyzing commits, code changes, and contribution patterns over a specified time range. Use when the user needs to create work reports, performance reviews, or contribution summaries from git history.
allowed-tools
Read, Bash, Write, Glob

Work Summary Skill

Comprehensive git repository analysis tool for generating performance review content and work summaries.

When to Use

  • User asks to generate a work summary or performance review
  • User needs to analyze git contributions over a time period
  • User wants statistics about their work in one or more repositories
  • User requests a report of code changes, commits, or development activity

How to Use

Step 1: Gather Information

Ask the user for:

  • Repository path(s): One or more local git repository paths (absolute or relative)
  • Time range: Start and end dates (e.g., "2024-01-01 to 2024-12-31", "last 3 months", "Q4 2024")
  • Author filter (optional): Git author name/email to filter commits (defaults to current git user)
  • Output format (optional): "markdown", "text", or "json" (defaults to markdown)

Step 2: Validate Repository

Use the Bash tool to verify the repository exists and is a valid git repository:

cd <repo_path> && git rev-parse --git-dir

Step 3: Run Analysis Script

Execute the work summary analysis script:

python $SKILL_ROOT/scripts/analyze_work.py \
  --repo <absolute_repo_path> \
  --start-date <YYYY-MM-DD> \
  --end-date <YYYY-MM-DD> \
  --author "<author_name_or_email>" \
  --output <output_json_path> \
  --format <markdown|text|json>

For multiple repositories:

python $SKILL_ROOT/scripts/analyze_work.py \
  --repo <repo1> <repo2> <repo3> \
  --start-date <YYYY-MM-DD> \
  --end-date <YYYY-MM-DD> \
  --author "<author_name_or_email>" \
  --output <output_json_path>

Step 4: Parse and Present Results

Read the generated output file and present the work summary to the user in a well-formatted report. Include:

  1. Overview Section

- Time period covered - Total commits, files changed, lines added/removed - Repositories analyzed

  1. Key Achievements

- Major features or changes based on commit messages - Significant file modifications - Pattern analysis of work type

  1. Contribution Statistics

- Commit frequency over time - Code churn metrics - File type breakdown - Most active areas of codebase

  1. Detailed Timeline (optional)

- Week-by-week or month-by-month breakdown - Notable commits and changes

Step 5: Offer Enhancements

Ask the user if they want:

  • To filter by specific file patterns or directories
  • To exclude certain types of commits (e.g., merges, automated commits)
  • To add more repositories to the analysis
  • To export in a different format
  • To generate visualizations (commit heatmap, language breakdown, etc.)

Script Dependencies

The analysis script requires:

  • Python 3.8+
  • GitPython library for git operations

Install with:

pip install -r $SKILL_ROOT/scripts/requirements.txt

Output Structure

The script generates a JSON file with the following structure:

{
  "summary": {
    "time_range": {"start": "...", "end": "..."},
    "total_commits": 123,
    "total_files_changed": 456,
    "total_insertions": 7890,
    "total_deletions": 1234,
    "repositories": ["repo1", "repo2"]
  },
  "commits": [
    {
      "hash": "abc123",
      "date": "2024-01-15T10:30:00",
      "message": "Add new feature",
      "files_changed": 5,
      "insertions": 120,
      "deletions": 30,
      "files": ["path/to/file.py", ...]
    }
  ],
  "statistics": {
    "commits_by_week": {...},
    "files_by_extension": {...},
    "most_modified_files": [...],
    "largest_commits": [...]
  },
  "achievements": [
    "Implemented authentication system (23 commits)",
    "Refactored database layer (15 files changed)",
    ...
  ]
}

Tips for Best Results

  1. Meaningful Commit Messages: The quality of the summary depends on commit message quality
  2. Time Alignment: Align time ranges with review periods (quarters, months, etc.)
  3. Multiple Repos: Analyze all relevant repositories for complete picture
  4. Author Matching: Ensure author filter matches git config user (name or email)
  5. Exclude Noise: Consider filtering out automated commits, merges, or trivial changes

Example Usage

User: "Generate my work summary for Q4 2024 from the ~/projects/my-app repository"

Claude:

  1. Confirms repository path and time range (Oct 1 - Dec 31, 2024)
  2. Runs analysis script with appropriate parameters
  3. Generates comprehensive markdown report with:

- 47 commits over 3 months - Key features: user authentication, API optimization, bug fixes - 2,345 lines added across 89 files - Primary work areas: backend services, database migrations - Contribution timeline with weekly breakdown

Troubleshooting

  • Invalid git repository: Ensure path points to a directory with .git folder
  • No commits found: Check author filter matches git user configuration
  • Date parsing errors: Use YYYY-MM-DD format for dates
  • Permission errors: Ensure read access to git repository

Related

See reference.md for detailed explanation of metrics and examples.md for sample outputs.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

31.33%
按下载量换算41

github-copilot

22.25%
按下载量换算29

Antigravity

17.75%
按下载量换算23

kilo

13.67%
按下载量换算18

windsurf

7.21%
按下载量换算9

zencoder

3.69%
按下载量换算5

安全审计

暂无安全审计结果可展示。

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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