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task-detection-thinking任务检测思维

Agent Skill

task-detection-thinking 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

3,608

周安装

155

GitHub Stars

公开资料未说明

下载量

1,265
OpenClaw

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-0

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:task-detection-thinking(任务检测思维)
来源仓库:https://github.com/opendolph/task-detection-thinking
安装命令:
openclaw skills install task-detection-thinking
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install task-detection-thinking

简介

不完整的任务检测+主动思考。自动扫描任务状态、识别异常、生成解决方案并尝试自动修复。

SKILL.md

name
task-detection-thinking
description
Incomplete task detection + proactive thinking. Automatically scans task status, identifies anomalies, generates solutions, and attempts auto-fixes.
version
1.0.0
author
OpenDolph
source
https://github.com/OpenDolph/skills/tree/main/task-detection-thinking

Task Detection + Proactive Thinking Skill

Automatically detect task anomalies, intelligently analyze causes, and proactively propose solutions

Trigger Conditions

ScenarioTrigger Method
Auto-triggerExecute during Heartbeat detection
Manual triggerUser inputs "check tasks", "task status", "anomaly detection"
Scheduled triggerAuto-scan every 6 hours

Task Management File Standards

HEARTBEAT.md - Global Task Board Template

## Global Task Board
| TaskID | Task Name | Status | Progress | Deadline | Last Update | Block Reason |
|--------|-----------|--------|----------|----------|-------------|--------------|
| T001 | Initialize three-layer memory | Done | 100% | 2026-03-10 | 2026-03-10 | None |
| T002 | Integrate vector retrieval | Active | 60% | 2026-03-15 | 2026-03-12 | Waiting for API key |
| T003 | Test proactive thinking | Waiting | 0% | 2026-03-20 | 2026-03-11 | Depends on T002 |

Status Definitions:

StatusMeaning
QueueWaiting to start
ActiveIn progress
WaitingBlocked/Waiting
DoneCompleted
AbortedCancelled

WORKING.md - Project-Level Task Rules

All subtasks must include:

  • Status: Queue/Active/Waiting/Done
  • Progress: Percentage (0-100%)
  • Owner: Person responsible
  • Dependencies: Task IDs this task depends on

Auto-Detection Rules:

  • Active tasks stalled >24h → Auto-marked as "Abnormal" 🔴
  • Blocked tasks must fill: "Block Reason" + "Support Needed"
  • Daily 23:00 → Auto-summary to HEARTBEAT.md

Detection Rules (Auto-execute)

1. Scan HEARTBEAT.md

Detection ItemConditionMark
Stalled tasksActive status + last update > 24h🔴 Stalled
Pending confirmationWaiting status + empty block reason🟡 Pending
Overdue tasksProgress < 100% + deadline < current time🔴 Overdue
No progress tasksActive status + 0% progress for > 48h🟡 No progress
Abnormal tasksActive + no update > 24h🔴 Abnormal

2. Scan WORKING.md

Detection ItemConditionMark
Dependency blockDownstream blocked by incomplete upstream🔗 Dependency block
Duplicate tasksTask name/content similarity > 80%⚠️ Duplicate
Zombie tasksDone status but no completion time👻 Zombie
Meaningless tasksEmpty title or content < 10 chars🗑️ To clean
Missing required fieldsNo status/progress/owner⚠️ Incomplete

Proactive Thinking Logic

For "Stalled Tasks"

Analysis Steps:

  1. Check last update content → Determine stall type
  2. Scan related memories → Find context
  3. Generate 3 advancement solutions

Auto-attempt (No human needed):

  • Supplement missing info (extract from memory)
  • Retry failed interfaces/commands
  • Update task status to Waiting (if needed)

Human intervention required:

  • Generate detailed reminder, push via Feishu

For "Blocked Tasks"

Analysis Steps:

  1. Identify block type (resource/dependency/decision/external)
  2. Determine if auto-solvable
  3. Record solution to warm memory

Auto-resolve scenarios:

  • Dependency task completed → Auto-unblock
  • Resource now available → Auto-retry
  • Info supplemented → Auto-advance

For "Overdue Tasks"

Analysis Steps:

  1. Assess remaining workload
  2. Determine delay impact
  3. Generate adjustment plan

Auto-adjust:

  • Update deadline to reasonable value
  • Adjust downstream task schedule
  • Mark as high priority

Output Rules

Output TypeLocationTrigger Condition
Detection resultsmemory/hot/task-alert.mdAfter each detection
Thinking conclusionsmemory/hot/thinking-log.mdAfter each analysis
Critical alertsFeishu pushOverdue/serious block
Solutionsmemory/warm/lessons_learned.mdRecord after resolution

Usage Examples

# Manual trigger detection
node skills/task-detection-thinking/scripts/detect.js

# View detection results
cat memory/hot/task-alert.md

# View thinking log
cat memory/hot/thinking-log.md

Configuration Parameters

task_detection:
  # Detection frequency
  heartbeat_check: true      # Detect during Heartbeat
  cron_schedule: "0 */6 * * *"  # Every 6 hours
  
  # Threshold settings
  stale_threshold_hours: 24   # Stall threshold
  overdue_check: true         # Check overdue
  dependency_check: true      # Check dependency chain
  
  # Auto-fix
  auto_fix_enabled: true      # Enable auto-fix
  auto_fix_max_attempts: 3    # Max auto-attempts
  
  # Notification settings
  feishu_alert: true          # Critical alert push
  alert_on_overdue: true      # Overdue alert
  alert_on_blocking: true     # Serious block alert

Workflow

Heartbeat trigger / Scheduled trigger / Manual trigger
    ↓
Scan HEARTBEAT.md + WORKING.md
    ↓
Identify anomaly tasks (stalled/blocked/overdue/duplicate)
    ↓
Analyze causes (context + historical memory)
    ↓
Generate solutions (3 options)
    ↓
Attempt auto-fix (no-human-needed solutions)
    ↓
Write detection results + thinking log
    ↓
Push critical alerts to Feishu

Integration with Existing Systems

  • HEARTBEAT.md - Read global task board
  • WORKING.md - Read subtask details
  • Three-layer memory system - Store detection results and thinking logs
  • ClawMemory - Query historical solutions
  • Feishu - Push critical alerts

*Transform task management from reactive response to proactive prevention*

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

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

能力 5

展示第三方安全扫描或审计结果

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

OpenClaw

74.22%
按下载量换算939

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

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安装前确认

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来源信息

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