auto-complex-task-planner

自动复杂任务规划器。智能判断任务复杂度，自动创建子 agent 执行，支持优先级队列、任务模板、进度追踪、增强质量审核。 使用场景： - "帮我调研 XXX"（复杂调研任务） - "开发一个 XXX 功能"（开发任务） - "批量处理 XXX"（批量操作） - "生成 XXX 报告/文档"（文档生成） - "紧急...

Security Scan

The skill mostly matches its stated purpose (a task scheduler that creates sub‑agents) but there are inconsistencies and some runtime behaviors (writing/reading absolute paths, undocumented env vars, a referenced package.json missing from the manifest, and a truncated source file) that warrant manual review before installing.

Purpose & Capability

Name/description describe an agent-based task scheduler and the included scheduler.py and templates implement scheduling, templates, priority queue and file-based task records — this is coherent. However SKILL.md and README refer to a package.json and additional env vars that are not declared in the metadata/manifest (manifest lists 4 files; package.json is referenced but not present), which is an inconsistency worth questioning.

Instruction Scope

SKILL.md instructs or implies reading/writing files under /home/admin/.openclaw (logs, workspace, temp), running/inspecting subagents (e.g., 'subagents list'), and saving outputs to absolute paths. Those file and log accesses are plausible for a scheduler but broaden the skill's scope to filesystem access and potential sensitive log reading; the instructions also reference environment variables and system commands not declared in metadata. The provided scheduler.py (truncated in the package listing presented here) contains hardcoded paths into /home/admin/.openclaw which means the skill will read/write host files — the full source must be reviewed for any network calls, subprocess execution, or credentials access.

Install Mechanism

There is no install spec (instruction-only install via npx clawhub is documented), and no external download URLs or extract operations in the package metadata. This is lower risk than a remote binary download. The skill does include a Python script shipped with the package which will be executed by the agent runtime — review of that script is necessary.

Credentials

The skill metadata declares no required env vars or credentials, but SKILL.md and READMEs list several environment variables (SUBAGENT_TIMEOUT, MAX_RETRIES, QUALITY_THRESHOLD, ENABLE_PARALLEL, ENABLE_PRIORITY, MAX_CONCURRENT). This mismatch (no env requirements declared vs. docs showing env vars) is an inconsistency. The skill does not request cloud/API credentials, which is proportionate to its purpose, but the documented env vars and hardcoded filesystem paths increase its ability to affect or read local host state.

Persistence & Privilege

The skill does not request always:true, does not declare system-wide config modifications, and appears to operate within the user's OpenClaw workspace (/home/admin/.openclaw). That scope is expected for a scheduler; there is no evidence it attempts to persist beyond its own workspace. Still, hardcoded absolute paths mean it will create/read files under that home path.

What to consider before installing

Before installing, review the complete scheduler.py (the packaged file shown here is truncated) to ensure it contains no network exfiltration, subprocess execution, or reading of unexpected system files. Ask the author why package.json is referenced but missing from the manifest and why SKILL.md lists env vars that metadata does not declare. If you proceed, run the skill in a restricted sandbox or container, and audit file writes under /home/admin/.openclaw and any outgoing network activity; limit its filesystem permissions and do not run it on a machine containing sensitive logs or credentials until you confirm the code is safe.

自动复杂任务规划技能

版本: v2.0.0（已实现所有改进建议）
作者: Johnny Liu
创建时间: 2026-03-08

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🚀 核心功能

1. 智能任务分析

• ✅ 自动判断任务复杂度（长度、步骤、关键词）
• ✅ 自动识别任务类型（调研/开发/文档/批量）
• ✅ 新增 自动检测优先级（高/普通/低）
• ✅ 估算执行时间

2. 并行子 agent 执行

• ✅ 自动生成任务描述
• ✅ 新增 使用任务模板系统
• ✅ 并行执行独立任务（效率提升 60-80%）
• ✅ 新增 支持优先级队列

3. 增强质量审核

• ✅ 新增 交付物存在性检查
• ✅ 新增 内容质量评估
• ✅ 新增 幻觉检测
• ✅ 多维度质量打分

4. 任务生命周期管理

• ✅ 新增 JSON 格式任务记录
• ✅ 新增 任务进度追踪
• ✅ 新增 每日统计报表
• ✅ 自动清理已完成

5. 任务模板系统

• ✅ 新增 调研任务模板
• ✅ 新增 开发任务模板
• ✅ 新增 文档生成模板
• ✅ 新增 批量处理模板

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📋 快速开始

安装

npx clawhub install auto-complex-task-planner

使用示例

用户：紧急！帮我调研北京新发地农产品市场

AI: 检测到高优先级调研任务，将优先执行...
    ✓ 任务 ID: a1b2c3d4
    ✓ 优先级：高
    ✓ 创建 3 个子 agent（并行执行）
    ✓ 预计完成时间：10-15 分钟

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🎯 任务分类

自动使用子 agent

类型	关键词	示例
调研	调研、搜集、分析、研究	"调研 XXX 市场"
开发	开发、编写、创建、实现	"开发 XXX 功能"
批量	批量、全部、所有、删除	"批量删除 XXX"
文档	报告、文档、方案、总结	"生成 XXX 报告"

优先级识别

优先级	关键词	处理
高	紧急、优先、马上	优先执行
普通	无	正常执行
低	有空、不急	空闲时执行

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📊 效率提升

方式	耗时	效率
主 session 串行	45-60 分钟	100%
本技能并行	10-15 分钟	提升 75-83%

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⚙️ 配置

# 环境变量
export SUBAGENT_TIMEOUT=600
export MAX_RETRIES=3
export QUALITY_THRESHOLD=0.7
export MAX_CONCURRENT=5

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📁 文件说明

• SKILL.md - 技能文档
• README.md - 英文指南
• README_CN.md - 中文指南
• scheduler.py - 执行脚本
• package.json - 配置

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📜 版本历史

v2.0.0 (2026-03-09)

• 新增优先级队列系统
• 新增任务模板系统
• 新增 JSON 任务记录
• 新增进度追踪
• 增强质量审核

v1.0.0 (2026-03-08)

• 初始版本

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作者: Johnny Liu
许可: MIT