task-tracker

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Chinese

Task Tracker - ADHD State Machine

任务追踪器 - ADHD状态机

Overview

概述

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

专为ADHD行为模式设计的系统化任务追踪系统。通过主动干预防止任务放弃，同时在无评判的前提下保持任务问责性。

State Machine

状态机

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

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

State Definitions

状态定义

State	Trigger	Next Actions
INITIATED	Task request received	Assess complexity, provide solution
SOLUTION_PROVIDED	Solution given	Wait for execution signal
IN_PROGRESS	User confirms working	Monitor for completion
COMPLETED	User confirms done	Log success, update streak
ABANDONED	No response + context switch	Log pattern, intervention
BLOCKED	External dependency	Identify blocker, schedule retry
DEFERRED	Conscious postponement	Set reminder, capture reason

状态	触发条件	后续操作
已发起	收到任务请求	评估复杂度，提供解决方案
已提供解决方案	给出解决方案	等待执行信号
进行中	用户确认正在处理	监控完成状态
已完成	用户确认完成	记录成功，更新连续完成天数
已放弃	无响应+上下文切换	记录行为模式，触发干预
受阻	存在外部依赖	识别阻碍因素，安排重试
已推迟	主动选择推迟	设置提醒，记录原因

Task Metadata

任务元数据

Every task tracks:

python

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
}

每个任务都会追踪以下信息：

python

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

任务放弃检测触发条件

Monitor for these patterns:

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

监控以下行为模式：

上下文切换 - 未关闭当前任务即开启新话题
会话结束 - 会话结束时任务处于“已提供解决方案”或“进行中”状态
时间流逝 - 提供解决方案后超过30分钟无更新
话题偏离 - 用户在任务未完成时询问无关问题

Detection Algorithm

检测算法

python

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

python

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

干预协议

Level 1: Gentle Check (0-30 minutes)

1级：温和提醒（0-30分钟）

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

📌 快速确认：[任务描述] - 还在处理吗？

Level 2: Pattern Observation (30-60 minutes)

2级：模式提示（30-60分钟）

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

🔄 我注意到之前的[任务]。这是本周第[N]次出现此类模式。
继续处理还是主动推迟？

Level 3: Direct Accountability (>60 minutes)

3级：直接问责（超过60分钟）

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

⚠️ 问责提醒：[任务]在[时间]前已开始。
当前状态如何？请如实告知 - 无评判，仅记录事实。

ADHD Intervention Strategies

ADHD干预策略

When abandonment detected, apply these techniques:

检测到任务放弃时，应用以下技巧：

Micro-Commitment

微承诺

Break to smallest possible action:

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

将任务拆解为最小可行动作：

只做第一步？[具体微小动作]就好。
当前无需完成其他步骤。

Body Doubling

虚拟陪伴

Create virtual co-working presence:

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

创建虚拟协作场景：

我们一起完成它。你：[具体动作]
我：⏱️ 等待中...（5分钟后我会再次确认）

Chunking

分块处理

Focus tunnel vision:

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

聚焦单一环节：

只做第一步。完成后请告知。
暂时不要考虑第二步。

Energy Matching

能量匹配

Align with daily patterns:

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

贴合日常精力模式：

现在是[时间] - 你的[高峰/低谷]时段。
[建议匹配的任务复杂度]

Workflow: Task Creation

工作流：任务创建

Trigger: Any request that implies work to be done

Extract task description from message
Assess complexity (1-10) based on:
- Number of steps
- External dependencies
- Decision-making required
- Time estimate
Assess clarity (1-10) based on:
- Specificity of request
- Known vs unknown elements
- Ambiguity level
Assign domain (BUSINESS/MICHAEL/FAMILY/PERSONAL)
Set state to INITIATED
Provide solution → state to SOLUTION_PROVIDED

触发条件： 任何隐含需要完成工作的请求

从消息中提取任务描述
基于以下维度评估复杂度（1-10分）：
- 步骤数量
- 外部依赖
- 所需决策量
- 时间预估
基于以下维度评估清晰度（1-10分）：
- 请求的具体程度
- 已知与未知要素
- 模糊程度
分配领域（BUSINESS/MICHAEL/FAMILY/PERSONAL）
将状态设置为“已发起”
提供解决方案 → 状态更新为“已提供解决方案”

Workflow: State Transitions

工作流：状态转换

INITIATED → SOLUTION_PROVIDED

已发起 → 已提供解决方案

python

undefined

python

undefined

After providing solution

task["state"] = "SOLUTION_PROVIDED" task["solution_provided_at"] = now()

undefined

task["state"] = "SOLUTION_PROVIDED" task["solution_provided_at"] = now()

undefined

SOLUTION_PROVIDED → IN_PROGRESS

已提供解决方案 → 进行中

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

python

task["state"] = "IN_PROGRESS"

触发条件： 用户表示“正在处理”“现在开始”“做这个”

python

task["state"] = "IN_PROGRESS"

IN_PROGRESS → COMPLETED

进行中 → 已完成

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

python

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

触发条件： 用户表示“完成”“做完了”“结束了”

python

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

Any → ABANDONED

任意状态 → 已放弃

Trigger: Abandonment detection + no response to intervention

python

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

触发条件： 检测到任务放弃 + 对干预无响应

python

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

Any → BLOCKED

任意状态 → 受阻

Trigger: User identifies external dependency

python

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

触发条件： 用户指出存在外部依赖

python

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

Any → DEFERRED

任意状态 → 已推迟

Trigger: Conscious postponement with reason

python

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

触发条件： 用户主动选择推迟并说明原因

python

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

Streak Tracking

连续完成天数追踪

Maintain completion streak for motivation:

python

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

记录连续完成天数以提升动力：

python

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."

undefined

"Day 6 starts now. Keep the streak alive."

undefined

Domain-Specific Behavior

领域专属行为

BUSINESS (Everest Capital)

BUSINESS（Everest Capital）

Higher urgency weighting
Deadline awareness
Revenue impact assessment

更高的紧急权重
截止日期提醒
营收影响评估

MICHAEL (D1 Swimming)

MICHAEL（D1游泳队）

Connect to swim schedule
Nutrition/training alignment
Recruiting deadlines

关联游泳日程
营养/训练协同
招募截止日期追踪

FAMILY (Orthodox Observance)

FAMILY（东正教守规）

Shabbat/holiday awareness
No work pressure evenings
Family event priority

安息日/节假日提醒
晚间无工作压力
家庭活动优先

PERSONAL (Health/Learning)

PERSONAL（健康/学习）

Energy level consideration
Learning capture integration
Health metric correlation

精力水平考量
学习内容整合
健康指标关联

LangGraph Integration

LangGraph集成

State Schema

状态模式

python

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

python

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

节点

```
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

```
create_task
```
- 从用户消息初始化任务
```
provide_solution
```
- 生成回复，更新状态
```
check_abandonment
```
- 定期检查任务是否被放弃
```
intervene
```
- 应用干预策略
```
complete_task
```
- 记录完成状态，更新连续完成天数

Scripts

脚本

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

```
scripts/task_state_machine.py
```
- 状态转换逻辑
```
scripts/abandonment_detector.py
```
- 模式检测
```
scripts/streak_calculator.py
```
- 连续完成天数维护

References

参考资料

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

```
references/intervention_templates.md
```
- 完整干预脚本
```
references/adhd_patterns.md
```
- 常见行为模式与应对方案