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Agent Skill · 待分类

task-tracker(任务跟踪器)

task-tracker 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。

task-tracker 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 3,170。

总安装 1,128周安装 47GitHub Stars 5下载 376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
unknown

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:task-tracker(任务跟踪器)
来源仓库:https://github.com/breverdbidder/life-os
仓库路径:skills/task-tracker
安装命令:
npx skills add https://github.com/breverdbidder/life-os --skill task-tracker
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。

skills.shnpx skills
npx skills add https://github.com/breverdbidder/life-os --skill task-tracker

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

专为 ADHD 用户设计的任务管理系统,通过状态机防止任务 abandonment。支持 INITIATED → SOLUTION_PROVIDED → IN_PROGRESS → COMPLETED 流转。适用于需要高专注力和持续跟进的场景,提供主动干预机制。

使用前需明确任务初始状态和责任人,避免因模糊输入导致流程中断。输出结果应尊重用户节奏,不强推进度或施加额外压力。

来源仓库内路径:skills/task-tracker

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/breverdbidder/life-os --skill task-tracker;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

    它需要需要联网,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

task-tracker 怎么安装?

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

task-tracker 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。

task-tracker 需要什么权限?

权限级别是需要联网。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。

task-tracker 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

task-tracker 用的人多吗?

公开数据是累计安装 1,128 次,近一周安装 47 次,下载 376 次,GitHub 5 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。

task-tracker 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。
  • 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

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
task-tracker

任务跟踪器 · 本页

1,1285需要联网未明确通过

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

Task Tracker - ADHD State Machine

Overview

Systematic task tracking designed for ADHD patterns. Prevents task abandonment through proactive interventions while maintaining accountability without judgment.

State Machine

                    ┌──────────────────────────────────────────┐
                    │                                          │
                    ▼                                          │
┌──────────┐   ┌──────────────────┐   ┌─────────────┐         │
│ INITIATED│──▶│ SOLUTION_PROVIDED│──▶│ IN_PROGRESS │─────────┤
└──────────┘   └──────────────────┘   └─────────────┘         │
     │                  │                    │                 │
     │                  │                    ▼                 │
     │                  │              ┌───────────┐          │
     │                  │              │ COMPLETED │          │
     │                  │              └───────────┘          │
     │                  │                                      │
     │                  ├─────────────────┐                   │
     │                  │                 │                    │
     │                  ▼                 ▼                    │
     │           ┌───────────┐     ┌──────────┐               │
     └──────────▶│ ABANDONED │     │ BLOCKED  │               │
                 └───────────┘     └──────────┘               │
                        │                │                     │
                        ▼                ▼                     │
                 ┌───────────┐     ┌──────────┐               │
                 │  DEFERRED │◀────│ (Retry)  │───────────────┘
                 └───────────┘     └──────────┘

State Definitions

StateTriggerNext Actions
INITIATEDTask request receivedAssess complexity, provide solution
SOLUTION_PROVIDEDSolution givenWait for execution signal
IN_PROGRESSUser confirms workingMonitor for completion
COMPLETEDUser confirms doneLog success, update streak
ABANDONEDNo response + context switchLog pattern, intervention
BLOCKEDExternal dependencyIdentify blocker, schedule retry
DEFERREDConscious postponementSet reminder, capture reason

Task Metadata

Every task tracks:

task = {
    "id": "task_20251219_001",
    "description": "Review Q4 insurance renewals",
    "state": "INITIATED",
    "domain": "BUSINESS",  # BUSINESS | MICHAEL | FAMILY | PERSONAL
    "complexity": 6,       # 1-10 scale
    "clarity": 8,          # 1-10 scale (how clear were instructions)
    "estimated_minutes": 45,
    "actual_minutes": None,
    "initiated_at": "2025-12-19T10:30:00Z",
    "solution_provided_at": None,
    "completed_at": None,
    "abandonment_count": 0,
    "intervention_level": 0
}

Abandonment Detection Triggers

Monitor for these patterns:

  1. Context Switch - New topic without closing current task
  2. Session End - Chat ends with task in SOLUTION_PROVIDED or IN_PROGRESS
  3. Time Decay - >30 minutes since solution with no update
  4. Topic Drift - User asks unrelated question while task pending

Detection Algorithm

def check_abandonment(task, current_message, elapsed_minutes):
    if task["state"] not in ["SOLUTION_PROVIDED", "IN_PROGRESS"]:
        return False

    # Time-based trigger
    if elapsed_minutes > 30:
        return True

    # Context switch detection
    if not is_related_to_task(current_message, task):
        return True

    return False

Intervention Protocol

Level 1: Gentle Check (0-30 minutes)

📌 Quick check: [task description] - still on it?

Level 2: Pattern Observation (30-60 minutes)

🔄 I notice [task] from earlier. This is pattern #[N] this week.
Continue or consciously defer?

Level 3: Direct Accountability (>60 minutes)

⚠️ ACCOUNTABILITY: [task] started [time] ago.
Current status? Be honest - no judgment, just facts.

ADHD Intervention Strategies

When abandonment detected, apply these techniques:

Micro-Commitment

Break to smallest possible action:

Just step 1? [tiny specific action] That's it.
Nothing else required right now.

Body Doubling

Create virtual co-working presence:

Let's do this together. You: [specific action]
Me: ⏱️ Waiting... (I'll check back in 5 minutes)

Chunking

Focus tunnel vision:

Step 1 only. Confirm when done.
Don't think about step 2 yet.

Energy Matching

Align with daily patterns:

It's [time] - your [peak/dip] period.
[Suggest appropriate task complexity]

Workflow: Task Creation

Trigger: Any request that implies work to be done

  1. Extract task description from message
  2. Assess complexity (1-10) based on:

- Number of steps - External dependencies - Decision-making required - Time estimate

  1. Assess clarity (1-10) based on:

- Specificity of request - Known vs unknown elements - Ambiguity level

  1. Assign domain (BUSINESS/MICHAEL/FAMILY/PERSONAL)
  2. Set state to INITIATED
  3. Provide solution → state to SOLUTION_PROVIDED

Workflow: State Transitions

INITIATED → SOLUTION_PROVIDED

# After providing solution
task["state"] = "SOLUTION_PROVIDED"
task["solution_provided_at"] = now()

SOLUTION_PROVIDED → IN_PROGRESS

Trigger: User says "working on it", "starting now", "doing this"

task["state"] = "IN_PROGRESS"

IN_PROGRESS → COMPLETED

Trigger: User says "done", "finished", "completed"

task["state"] = "COMPLETED"
task["completed_at"] = now()
task["actual_minutes"] = elapsed_time()
update_streak()

Any → ABANDONED

Trigger: Abandonment detection + no response to intervention

task["state"] = "ABANDONED"
task["abandonment_count"] += 1
log_pattern()

Any → BLOCKED

Trigger: User identifies external dependency

task["state"] = "BLOCKED"
task["blocker"] = identified_dependency
schedule_retry()

Any → DEFERRED

Trigger: Conscious postponement with reason

task["state"] = "DEFERRED"
task["defer_reason"] = reason
task["defer_until"] = scheduled_time

Streak Tracking

Maintain completion streak for motivation:

streak = {
    "current": 5,  # Days with at least 1 completion
    "longest": 12,
    "total_completions": 47,
    "abandonment_rate": 0.23  # 23% tasks abandoned
}

# On completion
"✅ Done. Streak: 5 days. Total: 47 tasks."

# On first task of day
"Day 6 starts now. Keep the streak alive."

Domain-Specific Behavior

BUSINESS (Everest Capital)

  • Higher urgency weighting
  • Deadline awareness
  • Revenue impact assessment

MICHAEL (D1 Swimming)

  • Connect to swim schedule
  • Nutrition/training alignment
  • Recruiting deadlines

FAMILY (Orthodox Observance)

  • Shabbat/holiday awareness
  • No work pressure evenings
  • Family event priority

PERSONAL (Health/Learning)

  • Energy level consideration
  • Learning capture integration
  • Health metric correlation

LangGraph Integration

State Schema

class TaskState(TypedDict):
    task_id: str
    description: str
    state: str
    domain: str
    complexity: int
    clarity: int
    elapsed_minutes: int
    intervention_level: int
    streak_current: int

Nodes

  • create_task - Initialize from user message
  • provide_solution - Generate response, update state
  • check_abandonment - Periodic abandonment check
  • intervene - Apply intervention strategy
  • complete_task - Log completion, update streak

Scripts

  • scripts/task_state_machine.py - State transition logic
  • scripts/abandonment_detector.py - Pattern detection
  • scripts/streak_calculator.py - Streak maintenance

References

  • references/intervention_templates.md - Full intervention scripts
  • references/adhd_patterns.md - Common patterns and responses

平台分布

Codex

35.53%
按下载量换算134

Claude

28.22%
按下载量换算106

Cursor

18.13%
按下载量换算68

Gemini CLI

8.63%
按下载量换算32

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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