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Agent Skill · AI 工具

pomodoro(pomodoro 命令行)

pomodoro 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

pomodoro 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证为 MIT,第三方扫描已通过,按安装量在AI 工具类的 2,536 个 Skill 里排第 1,088。

总安装 1,173周安装 47GitHub Stars 49下载 380核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:pomodoro(pomodoro 命令行)
来源仓库:https://github.com/jakedahn/pomodoro
仓库路径:skills/pomodoro
安装命令:
npx skills add https://github.com/jakedahn/pomodoro --skill pomodoro
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jakedahn/pomodoro --skill pomodoro

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

Pomodoro 命令行用于处理 GitHub 仓库及协作信息,适合整理代码变更和 Issue 事项。它可协助分析 Pull Request 和仓库状态,适用于开发流程中的协作信息管理。通过 npx skills add 命令从指定仓库安装,具体行为需结合原始 README 验证。

使用前应确认权限范围和维护状态,避免不必要的联网或文件读写操作。pomodoro 属于AI 工具类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/pomodoro

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jakedahn/pomodoro --skill pomodoro;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

pomodoro 怎么安装?

在终端执行 npx skills add https://github.com/jakedahn/pomodoro --skill pomodoro。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pomodoro 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

pomodoro 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/jakedahn/pomodoro --skill pomodoro;npx skills add jakedahn/pomodoro --skill "pomodoro" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

pomodoro 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

pomodoro 用的人多吗?

公开数据是累计安装 1,173 次,近一周安装 47 次,下载 380 次,GitHub 49 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

pomodoro 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理AI 工具类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
pomodoro

pomodoro 命令行 · 本页

1,17349执行命令MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Pomodoro Timer Skill

Overview

A 25-minute timer for focused work sessions that saves every session to SQLite. Enables history tracking, productivity analytics, and pattern recognition over time.

This is a System Skill - it provides handles to operate a personal data system. As commands run and sessions accumulate, context builds and compounds. The system learns patterns and provides increasingly valuable insights through an OODA loop of observation, orientation, decision, and action.

Mental Model: The OODA Loop

Operating this skill involves running a continuous cycle:

  1. Observe → Check current status (./pomodoro status) and review history (./pomodoro history)
  2. Orient → Analyze patterns in the data (./pomodoro stats --period week)
  3. Decide → Determine optimal actions (e.g., "Morning sessions have 95% completion - schedule deep work then")
  4. Act → Start sessions (./pomodoro start), provide recommendations, celebrate milestones

Each cycle builds on accumulated data, making insights more valuable over time.

Dependencies

  • Binary location: ~/.claude/skills/pomodoro/pomodoro
  • Database: Auto-created at ~/.claude/skills/pomodoro/pomodoro.db on first run
  • No external dependencies required

Quick Decision Tree

User task → What kind of request?
   ├─ Start focused work → Check status first, then start session
   ├─ Check current timer → Use status command
   ├─ Review productivity → Use stats command (day/week/month/year)
   ├─ View past sessions → Use history command
   └─ Stop early → Use stop command

Core Commands

To see all available options: Run ./pomodoro --help or ./pomodoro <command> --help

Starting a Session

Begin a Pomodoro session:

# Traditional 25-minute Pomodoro
./pomodoro start --task "Refactor authentication module"

# Custom durations and cycles
./pomodoro start --task "Quick review" --work 5 --break 3 --cycles 2
./pomodoro start --task "Deep focus" --work 50 --break 10 --cycles 1

# Flash cards (rapid cycles)
./pomodoro start --task "Flash cards" --work 2 --break 1 --cycles 5

Options:

  • --work <minutes> - Work duration (default: 25)
  • --break <minutes> - Break duration (default: 5)
  • --cycles <count> - Number of work+break rounds (default: 1)

Behavior:

  • Only one session can run at a time
  • Timer runs in foreground showing progress every minute
  • Breaks start automatically after work sessions
  • Next work session starts automatically after break (if cycles remaining)
  • Each work session saved separately to database

JSON output example:

./pomodoro start --task "Write docs" --json
# Returns: {"status": "started", "task": "Write docs", "duration": 25, "started_at": "2025-10-22T14:30:00Z"}

Checking Status

See if a timer is running:

./pomodoro status
./pomodoro status --json  # For programmatic use

Output example:

Active session: "Write documentation"
Started: 2:30 PM
Time remaining: 18 minutes

Viewing History

Review past sessions:

./pomodoro history --days 7    # Last 7 days
./pomodoro history --days 30   # Last 30 days
./pomodoro history --json      # For programmatic use

Output includes:

  • Task names
  • Start and completion times
  • Duration
  • Completion status (completed vs. stopped early)

Analyzing Productivity

Get insights from accumulated data:

./pomodoro stats --period day     # Today's stats
./pomodoro stats --period week    # This week
./pomodoro stats --period month   # This month
./pomodoro stats --period year    # This year
./pomodoro stats --json           # For programmatic use

Statistics include:

  • Total and completed sessions
  • Completion rate (% of sessions finished)
  • Total focus time
  • Most productive hours of day
  • Task distribution (which tasks completed most often)

JSON output example:

{
  "period": "week",
  "total_sessions": 23,
  "completed": 19,
  "completion_rate": 0.826,
  "focus_hours": 7.9,
  "productive_hours": [9, 10, 11],
  "top_tasks": ["Refactoring", "Documentation", "Code review"]
}

Stopping Early

End the current session before completion:

./pomodoro stop

Use when interruptions occur or task completes early. Session marked as incomplete in database.

Essential Workflows

Starting Focused Work

To help a user start a Pomodoro session:

  1. Check for active session: ./pomodoro status
  2. If clear, start with appropriate options:

- Traditional: ./pomodoro start --task "Deep work on authentication" - Custom: ./pomodoro start --task "Sprint planning" --work 15 --break 5 --cycles 3 - Flash cards: ./pomodoro start --task "Vocabulary review" --work 2 --break 1 --cycles 10

  1. Confirm to user: "25-minute Pomodoro started for [task name]. Timer running."

Daily Review

To provide daily productivity summary:

  1. Fetch today's data: ./pomodoro stats --period day --json
  2. Parse and present insights:

- "Completed 6 Pomodoros today (3.0 hours of focus time)" - "5/6 sessions completed - 83% completion rate" - "Most work on: Refactoring, Documentation" - "Productive hours: 9-11 AM"

Weekly Analysis

To provide weekly productivity review:

  1. Fetch week's data: ./pomodoro stats --period week --json
  2. Identify patterns:

- Compare to previous weeks if data available - Note peak productive hours - Identify which task types have highest completion rates

  1. Make recommendations:

- "Schedule deep work during your peak hours (9-11 AM)" - "Coding sessions have 90% completion vs 70% for meetings - consider task segmentation"

Pattern Recognition Over Time

As sessions accumulate, provide increasingly valuable insights:

After a few sessions (1-5):

  • "Completed 3 Pomodoros today"
  • "Building momentum with focus sessions"

After several days (5-20 sessions):

  • "7 completed out of 9 sessions - 78% completion rate"
  • "Most productive between 9-11 AM"

After a week (20-50 sessions):

  • "Strong week: 23 sessions with 85% completion"
  • "Peak productivity: 9-11 AM (95% completion) vs 2-4 PM (65% completion)"
  • "Consider scheduling deep work in morning hours"

After a month (50+ sessions):

  • "Coding tasks: 90% completion rate"
  • "Documentation tasks: 70% completion rate"
  • "Consider shorter Pomodoros (15 min) for documentation work"

After several months (100+ sessions):

  • "Completion rate improving: 72% → 85% over last 3 months"
  • "Wednesday is most productive day (92% completion)"
  • "Afternoon sessions improve when limited to 15 minutes"
  • "80% more sessions completed on coding vs documentation tasks"

Commands to use for pattern recognition:

./pomodoro stats --period month --json  # Get monthly data
./pomodoro history --days 90 --json     # Review last 90 days

Milestone Celebrations

Acknowledge progress at key milestones:

  • 10 sessions: "First 10 Pomodoros complete - building the habit!"
  • 50 sessions: "50 sessions milestone - over 20 hours of focused work!"
  • 100 sessions: "100 Pomodoros! That's 40+ hours of deep focus time."
  • High completion rates: "95% completion this week - excellent focus!"

To check milestone status: ./pomodoro stats --period year --json

Common Pitfalls

Starting When Session Already Active

❌ Don't start a new session without checking status first ✅ Do run ./pomodoro status before starting

Why: Only one session can run at a time. Starting when active causes error.

Pattern to follow:

# Check first
./pomodoro status
# If "No active session", then start
./pomodoro start --task "New task"

Non-Descriptive Task Names

❌ Don't use vague names: "Work", "Stuff", "Things" ✅ Do use specific names: "Refactor auth module", "Write API docs", "Review PR #123"

Why: Descriptive names enable better analytics. Pattern recognition needs specificity to identify which task types work best.

Interrupting Long-Running Sessions

❌ Don't let terminal close or process be killed during session ✅ Do use ./pomodoro stop if interruption is necessary

Why: Interrupted sessions aren't saved to database. Use stop command to record partial session.

Ignoring Completion Rate Signals

❌ Don't ignore consistent low completion rates for certain task types ✅ Do adjust session length based on task type patterns

Why: If documentation tasks show 60% completion vs 90% for coding, shorter sessions (15 min) may work better for documentation.

How to identify:

./pomodoro stats --period month --json
# Review completion rates by task type
# Suggest duration adjustments based on patterns

Best Practices

Session Management

  • Use descriptive task names for better analytics
  • Complete full 25 minutes when possible
  • Take breaks between sessions
  • Adjust duration based on task type (use --work flag)
  • Stop explicitly if interrupted (don't let process be killed)

User Interaction

  • Celebrate milestones (10, 50, 100, 250, 500 sessions)
  • Acknowledge completion rates: "Excellent focus - 90% this week!"
  • Suggest optimal times based on historical data
  • Encourage consistent practice
  • Point out improvements: "Completion rate up from 75% to 85%"

Data Analysis

  • Review daily stats at end of each day
  • Check weekly patterns for scheduling insights
  • Track trends over time (month, year)
  • Use JSON output for custom analytics
  • Cross-reference task types with completion rates
  • Identify peak productive hours

Command Composition

Combine commands for deeper insights:

# Morning check-in: status + daily stats
./pomodoro status
./pomodoro stats --period day

# Weekly review: history + stats
./pomodoro history --days 7 --json
./pomodoro stats --period week --json

# Long-term analysis: monthly trends
./pomodoro stats --period month --json
./pomodoro history --days 90 --json

Technical Notes

JSON Output

All commands support --json flag for programmatic access:

./pomodoro status --json
./pomodoro history --json
./pomodoro stats --json

Use JSON output when:

  • Parsing data programmatically
  • Building custom analytics
  • Feeding into other tools
  • Need structured output

Database

  • Location: ~/.claude/skills/pomodoro/pomodoro.db
  • Format: SQLite database with single sessions table
  • Persistence: All sessions saved permanently
  • Growth: Database grows with use (each session ~100 bytes)
  • Analytics: Richer insights as data accumulates
  • Maintenance: No cleanup or archiving needed

Schema:

CREATE TABLE sessions (
  id INTEGER PRIMARY KEY,
  task TEXT NOT NULL,
  duration INTEGER NOT NULL,
  started_at TEXT NOT NULL,
  completed_at TEXT
);

Timer Behavior

  • Runs in foreground process (blocks terminal)
  • Shows progress every minute during work sessions
  • Shows progress every minute during break sessions
  • Automatically transitions from work → break → work
  • Each work session saved separately to database
  • Supports custom durations via flags

Example session flow (3 cycles):

Work 25min → Break 5min → Work 25min → Break 5min → Work 25min → Break 5min → Done

Result: 3 separate database entries (one per work session)

Binary Location

  • Path: ~/.claude/skills/pomodoro/pomodoro
  • Always use: ./pomodoro when running from skill directory
  • Full path: ~/.claude/skills/pomodoro/pomodoro from anywhere

To run from skill directory:

cd ~/.claude/skills/pomodoro
./pomodoro start --task "Task name"

The System Skill Pattern in Action

This skill demonstrates the System Skill Pattern (CLI + SKILL.md + Database):

  1. CLI Binary: Handles to operate the system - start sessions, query history, analyze patterns
  2. SKILL.md: Operating procedure for the OODA loop (Observe → Orient → Decide → Act)
  3. SQLite Database: Persistent memory where every session adds context

The key insight: With these three components, the skill animates a system rather than just responding to requests. Each interaction builds on the last. Analytics become richer. Insights get sharper. The tool compounds in value.

Example of compounding value:

  • Week 1: "Started 5 sessions"
  • Week 4: "Morning sessions: 95% completion. Afternoon: 70%. Schedule deep work mornings."
  • Month 3: "Coding: 90% completion. Docs: 72%. Try 15-minute sessions for documentation."

This pattern works for any skill where accumulating data adds value and where giving Claude handles to operate a system creates more utility than one-time responses.

See also: README.md for deeper technical details and implementation guide.

平台分布

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29.76%
按下载量换算113

windsurf

21.27%
按下载量换算81

OpenCode

19.39%
按下载量换算74

Codex

14.44%
按下载量换算55

Antigravity

7.82%
按下载量换算30

Gemini CLI

3.56%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/jakedahn/pomodoro --skill pomodoro;npx skills add jakedahn/pomodoro --skill "pomodoro" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。

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