复杂任务指挥子代理
Complex task orchestration and subagent command framework. Execute multi-stage complex tasks via subagent (sessions_spawn), including task breakdown, state m...
MIT-0 · Free to use, modify, and redistribute. No attribution required.
⭐ 0 · 28 · 0 current installs · 0 all-time installs
bysundayplus@miyan1221
MIT-0
Security Scan
OpenClaw
Suspicious
medium confidencePurpose & Capability
Name/description match what is present: tooling for spawning/managing subagents, checkpoints, heartbeat, notifications and optional Gitee sync. Files and scripts operate on task-progress.json, checkpoints and session spawning which is coherent for an orchestration skill. The presence of git/sessions_spawn/openclaw calls is expected for the stated goal.
Instruction Scope
Runtime instructions and bundled scripts instruct the agent or user to run sessions_spawn with free-form task text that can cause subagents to read/write arbitrary workspace files. The skill relies on reading/writing files under /root/.openclaw and running git push and sessions_spawn commands. references/advanced-patterns.md shows use of eval(condition, {...}) for branch selection — a potential code-execution/data-injection hazard if checkpoint contents are attacker-controlled. Instructions also describe automatic unattended fallback and automatic git pushes to remote repos; these behaviors can lead to unintended data exposure if not tightly controlled.
Install Mechanism
No remote download/install spec is bundled; it is instruction-only plus local scripts. That lowers supply-chain risk. Installation guidance references ClawHub/ClawHub CLI and git clone from a named Gitee repo which are standard but rely on user to run commands. No suspicious external URLs or archive extraction was found in the skill manifest.
Credentials
The skill declares no required env vars or credentials (proportionate), but it assumes the runtime has git credentials/SSH keys and OpenClaw / sessions_spawn available. That means it can leverage existing system credentials (e.g., repo push access or configured Git identity) without explicitly requesting them — sensible for a deploy/orchestration tool but worth noting because the skill can push content to remotes or run actions using the host's existing auth.
Persistence & Privilege
always:false and no special platform privileges requested. The skill writes files under its own workspace paths and does not attempt to modify other skills or global agent config. Autonomous invocation (model can invoke) is allowed (default) — combine that with the instruction-scope concerns above when deciding whether to enable autonomous runs.
What to consider before installing
This skill appears to implement what it claims, but it operates with powerful primitives — spawning subagents with arbitrary task text, reading/writing files under /root/.openclaw, and automating git push/sync. Before installing or running it:
- Inspect the scripts (checkpoint-writer, cache-manager, monitor, notification) and remove or sandbox any behavior you don't want (especially automated git push steps).
- Do not run as root; run in a restricted workspace to avoid exposing sensitive files under /root. Update default paths to a non-privileged directory.
- Confirm what sessions_spawn/subagent runtimes are allowed to access — because tasks in examples ask subagents to read other SKILL.md files or workspace files, which could leak secrets.
- Search for any use of eval or dynamic code execution (references/advanced-patterns shows eval in a sample) and replace with a safe expression parser if you will evaluate user-supplied checkpoint data.
- If you plan to enable unattended/auto-fallback modes, enforce strong safeguards: limit which phases can run unattended, restrict what subagents may do, and require explicit approval for actions that touch network endpoints or push to repositories.
- If automatic syncing to Gitee or external notifications are used, review repository remotes, Git credentials, and notification channel integrations (Feishu) and prefer manual pushes until you trust the setup.
If you want, I can: (a) point out the exact lines that call git/sessions_spawn and eval, (b) produce a checklist to harden defaults (paths, file permissions, sandboxing), or (c) suggest safe replacements for the eval usage.Like a lobster shell, security has layers — review code before you run it.
Current versionv2.0.0
Download ziplatest
License
MIT-0
Free to use, modify, and redistribute. No attribution required.
SKILL.md
复杂任务指挥子代理（Complex Task Subagent）
安装
方法 1：通过 ClawHub 安装（推荐）
# 安装 ClawHub CLI
npm i -g clawhub
# 安装 skill
clawhub install complex-task-subagent
更新 skill：
clawhub update complex-task-subagent
方法 2：从 GitHub/Gitee 手动安装
# 克隆仓库
git clone https://gitee.com/GoSundayPlus/complex-task-subagent-skill.git ~/.openclaw/workspace/skills/complex-task-subagent
# 或者使用 .skill 文件直接安装
# 1. 下载 .skill 文件
# 2. 将文件移动到 ~/.openclaw/skills/ 目录
# 3. 重启 OpenClaw Gateway
openclaw gateway restart
手动更新：
cd ~/.openclaw/workspace/skills/complex-task-subagent
git pull
openclaw gateway restart
方法 3：从 ClawHub 下载并手动安装
访问 https://clawhub.com/skills/complex-task-subagent 下载 .skill 文件，然后按照方法 2 的步骤 2-3 进行安装。
快速开始
适用场景：当你需要通过子代理执行多阶段复杂任务时使用此技能。
核心价值：
- 可靠的任务编排和状态管理
- 自动检测和推进已完成的阶段
- 超时和重试机制，提高鲁棒性
- 检查点驱动，支持任务恢复
- 集成 OpenClaw Heartbeat 实现无人值守
- 🌙 夜间无人模式：提前收集必要信息，在用户休息时自助决策完成任务
- 🔑 关键节点确认模式：重要决策点自动提醒用户，超时自动切换无人模式
- 💾 智能缓存管理：子代理临时缓存，正常完成自动回收，异常中断可恢复
- ⚡ 深度工作模式：完全无人值守的自动化任务执行框架
架构概览
┌─────────────────────────────────────────────┐
│ 主会话（指挥官） │
│ - 任务编排和状态管理 │
│ - 超时检测和重试 │
│ - 自动推进下一阶段 │
│ - 同步到 Gitee │
└─────────────────────────────────────────────┘
│
├──────────────┬──────────────┐
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│ 子代理 1 │ │ 子代理 2 │ │ 子代理 3 │
└──────────┘ └──────────┘ └──────────┘
│ │ │
└──────────────┴──────────────┘
│
▼
checkpoints/*.json
(任务完成标记)
│
▼
OpenClaw Heartbeat
(定期检查和自动推进)
核心原则
1. 单一事实来源（SSOT）
所有状态变更应该更新到一个中心化的文件：task-progress.json。
为什么重要：
- 避免状态不一致
- 简化调试和恢复
- 确保可追溯性
2. 检查点驱动
子代理完成任务后必须写入检查点文件，主会话基于检查点推进。
为什么重要：
- 可靠性：同步写入，不会丢失
- 可恢复：任务中断后可以继续
- 可验证：可以检查任务完整性
3. 主会话主导
主会话应该掌握控制权，定期检查并推进任务。
为什么重要：
- 逻辑清晰，易于维护
- 可以实现自动化
- 避免分布式协调的复杂性
4. 超时和重试
每个阶段都应该有超时机制和重试策略。
为什么重要：
- 提高系统鲁棒性
- 可以自动恢复临时性故障
- 避免长时间卡死
5. 渐进式披露
使用 OpenClaw Heartbeat 实现无人值守的定期检查。
为什么重要：
- 不依赖系统权限（如 cron）
- 与 OpenClaw 生态无缝集成
- 内置重试机制
6. 夜间无人模式
在任务开始前收集所有必要信息，在用户休息期间自助决策完成任务。
为什么重要：
- 充分利用夜间时间
- 避免打扰用户休息
- 提高整体效率
7. 关键节点确认模式
在关键决策点自动提醒用户，超时后自动切换到无人模式。
为什么重要：
- 平衡控制权和自动化
- 重要决策有人类参与
- 确保关键操作的安全性
8. 智能缓存管理
子代理工作期间使用临时缓存，正常完成自动回收，异常中断可恢复。
为什么重要：
- 避免重复工作
- 支持任务恢复
- 提高容错性
9. 深度工作模式
完全无人值守的自动化任务执行，包括进度监控、自动推进、异常恢复。
为什么重要：
- 最大化自动化程度
- 减少人为干预
- 实现真正的无人值守
任务结构
单一状态文件：task-progress.json
{
"taskId": "unique-task-id",
"taskName": "任务名称",
"status": "in_progress",
"currentPhase": 3,
"completedPhases": 2,
"totalPhases": 4,
"lastUpdated": "2026-03-10T00:00:00Z",
"checkpointsDir": "/root/.openclaw/workspace/complex-task-subagent-experience/checkpoints",
"cacheDir": "/root/.openclaw/workspace/complex-task-subagent-experience/cache",
"executionMode": "confirmation",
"userPreferences": {
"preferredAction": "ask",
"autoFallbackToUnattended": true,
"fallbackTimeout": 7200000,
"nightModeEnabled": false,
"nightModeStart": "22:00",
"nightModeEnd": "08:00"
},
"notification": {
"lastReminder": null,
"reminderCount": 0,
"remindersSent": []
},
"phases": {
"phase1": {
"name": "审核现有指南",
"status": "completed",
"completedAt": "2026-03-09T16:53:00Z",
"subagent": "subagent-audit",
"timeout": 1800000,
"maxRetries": 3,
"retries": 0,
"checkpoint": "phase1-audit.json",
"output": "/root/.openclaw/workspace/output/phase1-result.md",
"cacheFile": "phase1-cache.json",
"requiresConfirmation": false,
"critical": false
},
"phase2": {...},
"phase3": {
"name": "创建 CDP 直连方案指南",
"status": "running",
"startedAt": "2026-03-09T18:56:00Z",
"subagent": "subagent-cdp-guide",
"timeout": 1800000,
"maxRetries": 3,
"retries": 0,
"checkpoint": "phase3-cdp-guide.json",
"output": "/root/.openclaw/workspace/output/phase3-result.md",
"cacheFile": "phase3-cache.json",
"requiresConfirmation": true,
"critical": true,
"confirmationTimeout": 3600000,
"requiresGatewayRestart": false
},
"phase4": {...}
}
}
字段说明
| 字段 | 说明 | 必需 |
|---|---|---|
taskId | 任务唯一标识 | ✅ |
taskName | 任务名称 | ✅ |
status | 状态：in_progress/completed/failed | ✅ |
currentPhase | 当前阶段编号 | ✅ |
completedPhases | 已完成阶段数 | ✅ |
totalPhases | 总阶段数 | ✅ |
lastUpdated | 最后更新时间 | ✅ |
checkpointsDir | 检查点目录路径 | ✅ |
cacheDir | 子代理缓存目录路径 | ⚠️ |
executionMode | 执行模式：unattended/confirmation | ✅ |
userPreferences | 用户偏好设置 | ⚠️ |
notification | 通知状态追踪 | ⚠️ |
phases | 各阶段详细配置 | ✅ |
UserPreferences 字段说明
| 字段 | 说明 | 默认值 |
|---|---|---|
preferredAction | 默认操作：ask/auto/ask-critical | ask |
autoFallbackToUnattended | 是否自动降级到无人模式 | true |
fallbackTimeout | 降级超时时间（毫秒） | 7200000 (2小时) |
nightModeEnabled | 是否启用夜间模式 | false |
nightModeStart | 夜间模式开始时间 | 22:00 |
nightModeEnd | 夜间模式结束时间 | 08:00 |
Notification 字段说明
| 字段 | 说明 |
|---|---|
lastReminder | 最后一次提醒时间 |
reminderCount | 已发送提醒次数 |
remindersSent | 已发送提醒的列表 |
Phase 字段说明
| 字段 | 说明 | 必需 |
|---|---|---|
name | 阶段名称 | ✅ |
status | 状态：pending/starting/running/completed/failed | ✅ |
startedAt | 开始时间（running 状态） | ⚠️ |
completedAt | 完成时间（completed 状态） | ⚠️ |
subagent | 子代理标签（用于 sessions_spawn） | ⚠️ |
timeout | 超时时间（毫秒） | ⚠️ |
maxRetries | 最大重试次数 | ⚠️ |
retries | 当前重试次数 | ⚠️ |
checkpoint | 检查点文件名 | ⚠️ |
output | 输出文件路径 | ⚠️ |
cacheFile | 子代理缓存文件名 | ⚠️ |
requiresConfirmation | 是否需要用户确认 | ⚠️ |
critical | 是否为关键操作 | ⚠️ |
confirmationTimeout | 确认超时时间（毫秒） | ⚠️ |
requiresGatewayRestart | 是否需要重启 Gateway | ⚠️ |
工作流程
阶段 0：模式选择（新增）
-
选择执行模式
夜间无人模式：
- 提前收集所有必要信息
- 设置
executionMode: "unattended" - 用户休息期间自助决策
关键节点确认模式：
- 设置
executionMode: "confirmation" - 关键操作需要用户确认
- 超时自动降级到无人模式
-
收集必要信息（无人模式）
# 创建预配置模板 cat > /root/.openclaw/workspace/task-preferences.json << 'EOF' { "confirmations": { "gatewayRestart": { "allowed": false, "alternative": "使用缓存或降级方案" }, "fileOperations": { "allowed": true, "safePaths": ["/root/.openclaw/workspace"] }, "apiCalls": { "allowed": true, "rateLimit": 100 } }, "fallbackStrategies": { "critical": "ask_user", "nonCritical": "auto_proceed" } } EOF -
配置用户偏好
编辑
task-progress.json中的userPreferences：{ "preferredAction": "ask-critical", "autoFallbackToUnattended": true, "fallbackTimeout": 7200000, "nightModeEnabled": true, "nightModeStart": "22:00", "nightModeEnd": "08:00" }
阶段 1：任务初始化
-
创建 task-progress.json
- 定义所有阶段和配置
- 设置初始状态为 "in_progress"
- 所有阶段状态为 "pending"
- 设置执行模式和用户偏好
-
创建 checkpoints 目录
mkdir -p /root/.openclaw/workspace/complex-task-subagent-experience/checkpoints -
创建 cache 目录（新增）
mkdir -p /root/.openclaw/workspace/complex-task-subagent-experience/cache -
配置 OpenClaw Heartbeat
- 编辑
HEARTBEAT.md（见参考文档） - 调整心跳频率（推荐 10 分钟）
- 编辑
阶段 2：执行任务
-
启动子代理
# 基础启动 sessions_spawn \ --task "任务描述" \ --label "subagent-name" \ --runtime "subagent" \ --mode "run" \ --timeoutSeconds 3600 # 带缓存启动（新增） sessions_spawn \ --task "任务描述" \ --label "subagent-name" \ --runtime "subagent" \ --mode "run" \ --timeoutSeconds 3600 \ --cwd "/root/.openclaw/workspace/xianyu-automation" -
子代理缓存管理（新增）
在子代理任务描述中明确要求使用缓存：
执行以下任务： 1. 使用 /root/.openclaw/workspace/complex-task-subagent-experience/cache/phase3-cache.json 作为临时缓存文件 2. 任务过程中定期写入缓存（每10分钟或每个重要步骤后） 3. 缓存格式：{"step": 1, "data": {...}, "timestamp": "2026-03-14T18:00:00Z"} 4. 任务正常完成后，将最终结果写入检查点文件，并标记缓存可回收 5. 如果任务异常中断，缓存文件保留用于恢复缓存文件示例：
{ "phase": "phase3", "subagent": "subagent-cdp-guide", "status": "in_progress", "currentStep": 2, "totalSteps": 5, "data": { "intermediateResults": [], "state": {} }, "timestamp": "2026-03-14T18:05:00Z" } -
关键节点确认（新增）
在需要用户确认的阶段：
准备执行需要用户确认的操作： - 操作类型：${type} - 风险等级：${risk} - 需要重启 Gateway：${needsRestart} 请确认是否继续执行？回复"确认"或"同意"继续，其他回复跳过此操作。 如果1小时内未回复，将自动降级到无人模式。提醒机制：
# 第一次提醒（开始等待时） echo "[$(date '+%Y-%m-%d %H:%M:%S')] 📌 需要用户确认" >> task-notification.log # 1小时后第二次提醒 if [ $(( $(date +%s) - lastConfirmation )) -gt 3600 ]; then echo "[$(date '+%Y-%m-%d %H:%M:%S')] 📌 仍需用户确认（已等待1小时）" >> task-notification.log fi # 2小时后自动降级 if [ $(( $(date +%s) - lastConfirmation )) -gt 7200 ]; then executionMode="unattended" echo "[$(date '+%Y-%m-%d %H:%M:%S')] 🌙 自动切换到无人模式" >> task-notification.log fi -
子代理执行任务
- 子代理完成任务后写入检查点文件
- 检查点文件包含任务结果和元数据
- 正常完成后标记缓存可回收
-
主会话检测到检查点
- Heartbeat 定期检查 checkpoints 目录
- 发现新检查点 → 验证完整性
- 更新 task-progress.json
-
自动推进下一阶段
- 检查下一阶段依赖条件
- 如果需要确认且未收到回复，进入等待状态
- 如果满足条件，启动下一阶段子代理
-
缓存回收（新增）
在子代理正常完成后：
# 检查任务状态 if [ "$phase_status" = "completed" ]; then # 回收缓存 rm -f /root/.openclaw/workspace/complex-task-subagent-experience/cache/$cacheFile echo "[$(date '+%Y-%m-%d %H:%M:%S')] ♻️ 缓存已回收: $cacheFile" >> task-cache.log fi在子代理异常中断后恢复：
# 检查缓存文件 if [ -f "$cacheFile" ]; then # 读取缓存 cache_data=$(cat "$cacheFile") echo "[$(date '+%Y-%m-%d %H:%M:%S')] 📦 从缓存恢复: $cacheFile" >> task-cache.log # 重新启动子代理并传入缓存 sessions_spawn \ --task "任务描述 - 从缓存恢复: $cache_data" \ --label "subagent-name-retry" \ --runtime "subagent" \ --mode "run" \ --timeoutSeconds 3600 fi
阶段 3：超时和重试
-
超时检测
if phase.status == "running": elapsed = now() - phase.startedAt if elapsed > phase.timeout: if phase.retries < phase.maxRetries: # 重试 phase.retries += 1 restart_subagent(phase) else: # 失败 phase.status = "failed" notify_user() -
重新启动子代理
- 使用相同的 label 和任务描述
- 增加重试计数器
阶段 4：任务完成
-
所有阶段完成
- 检查所有阶段状态为 "completed"
- 更新任务状态为 "completed"
-
同步到 Gitee
cd /root/.openclaw # 添加所有修改 git add workspace/output/ workspace/experience/ # 提交 COMMIT_MSG="任务完成：$(date '+%Y-%m-%d %H:%M')" git commit -m "$COMMIT_MSG" # 推送 git push -
记录日志
echo "[$(date '+%Y-%m-%d %H:%M:%S')] ✅ 任务已完成并同步到 Gitee" >> /root/.openclaw/workspace/task-monitor.log
检查点格式
检查点文件结构
{
"checkpointId": "phase1-audit",
"phase": "phase1",
"phaseName": "审核现有指南",
"status": "completed",
"completedAt": "2026-03-09T16:53:00Z",
"subagent": "subagent-audit",
"output": "/root/.openclaw/workspace/output/phase1-result.md",
"result": {
"success": true,
"message": "审核完成，发现 3 个问题",
"issues": [
"问题 1",
"问题 2",
"问题 3"
]
},
"metadata": {
"totalIssues": 3,
"criticalIssues": 1,
"warnings": 2
}
}
写入检查点
在子代理中：
def write_checkpoint(checkpoint_file, data):
import json
from pathlib import Path
checkpoint_path = Path("/root/.openclaw/workspace/complex-task-subagent-experience/checkpoints") / checkpoint_file
with open(checkpoint_path, 'w') as f:
json.dump(data, f, indent=2)
print(f"✅ 检查点已写入: {checkpoint_path}")
OpenClaw Heartbeat 集成
配置 HEARTBEAT.md
将以下内容添加到 HEARTBEAT.md（或创建独立的 HEARTBEAT-TASK.md）：
# 任务检查清单
1. 读取 task-progress.json
2. 检查 checkpoints/ 目录
3. 比对检查点和任务进度，更新状态
4. 如果阶段完成但下一阶段未启动，自动推进
5. 如果所有阶段完成，同步到 Gitee
6. 记录操作日志
7. 如果没有需要推进的内容，回复 HEARTBEAT_OK
配置 openclaw.json
{
"agents": {
"defaults": {
"heartbeat": {
"every": "10m",
"target": "last",
"prompt": "Read HEARTBEAT-TASK.md if it exists (workspace context). Follow it strictly. Do not infer or repeat old tasks from prior chats. If nothing needs attention, reply HEARTBEAT_OK."
}
}
}
}
心跳频率选择
| 频率 | 适用场景 | 说明 |
|---|---|---|
| 5 分钟 | 高优先级任务 | 快速响应，但消耗更多 token |
| 10 分钟 | 一般任务（推荐） | 平衡响应和成本 |
| 30 分钟 | 低优先级任务 | 节省 token，响应较慢 |
| 1 小时 | 后台任务 | 最小化 token 消耗 |
子代理最佳实践
子代理任务设计
好的任务描述：
- ✅ "审核 /root/.openclaw/workspace/guide.md 文件，对比官方文档，记录所有虚构内容和不准确信息，输出到 /root/.openclaw/workspace/output/audit-report.md"
不好的任务描述：
- ❌ "审核指南"
- ❌ "看看这个文件有没有问题"
- ❌ "帮我检查一下"
子代理超时设置
| 任务类型 | 超时时间 | 说明 |
|---|---|---|
| 文本审核/分析 | 30 分钟 | 读取、分析、输出 |
| 文档编写 | 1 小时 | 可能需要多次迭代 |
| 代码生成 | 45 分钟 | 需要测试和调试 |
| 数据处理 | 2 小时 | 取决于数据量 |
| Gitee 同步 | 5 分钟 | 快速操作 |
子代理标签规范
使用描述性的标签，格式：subagent-<任务简述>
| 任务 | 标签示例 |
|---|---|
| 审核指南 | subagent-audit-guide |
| 创建文档 | subagent-create-doc |
| 测试代码 | subagent-test-code |
| 同步 Gitee | subagent-sync-gitee |
常见问题和解决方案
问题 1：子代理完成后未推进下一阶段
症状：
- 子代理显示完成
- 但 task-progress.json 状态未更新
- 下一阶段未启动
原因：
- 子代理未写入检查点文件
- Heartbeat 未检测到检查点
- 检查点路径配置错误
解决方案：
- 检查 checkpoints 目录是否存在
- 检查检查点文件是否有效 JSON
- 检查 Heartbeat 配置是否正确
问题 2：子代理超时
症状：
- 阶段状态一直是 "running"
- 超时时间已过
原因：
- 子代理卡死
- 任务过于复杂
- 网络问题
解决方案：
- 检查子代理日志
- 增加超时时间
- 重试机制自动重启
问题 3：状态不一致
症状：
- task-progress.json 和 checkpoints 不一致
- 已完成的阶段显示为 "running"
原因：
- 手动修改了状态文件
- 多个进程同时修改
解决方案：
- 以 task-progress.json 为准（SSOT）
- 使用检查点验证
- 避免手动修改状态文件
问题 4：Gitee 同步失败
症状：
- Git push 返回错误
- 任务标记为失败
原因：
- 网络问题
- 认证问题
- 冲突
解决方案：
- 检查网络连接
- 验证 SSH 密钥
- 手动解决冲突后重试
完整示例
参见以下参考文档获取详细示例：
- references/quick-start.md - 快速开始示例
- references/advanced-patterns.md - 高级模式
- references/troubleshooting.md - 故障排查
深度工作模式完整配置指南
以 xianyu-automation 项目为例，展示如何完整配置深度工作模式。
1. 项目工作区配置
确保所有相关 agent 共享同一个工作区：
# 工作区路径
WORKSPACE="/root/.openclaw/workspace/xianyu-automation"
# 创建必要的目录结构
cd $WORKSPACE
mkdir -p cache output 配置
2. 配置绘图模型（第三方 API）
方法 1：手工配置
编辑 ~/.openclaw/openclaw.json：
{
"agents": {
"defaults": {
"imageModel": "https://your-third-party-api.com/v1/images/generations",
"imageModelProvider": "openai",
"imageModelKey": "your-api-key"
},
"customAgents": {
"content-creator": {
"model": "zai/glm-4.7",
"imageModel": "https://your-third-party-api.com/v1/images/generations",
"imageModelKey": "your-specific-api-key"
}
}
}
}
方法 2：热加载配置
# 步骤 1：添加图像模型配置
openclaw config set agents.defaults.imageModel "https://your-third-party-api.com/v1/images/generations"
openclaw config set agents.defaults.imageModelProvider "openai"
openclaw config set agents.defaults.imageModelKey "your-api-key"
# 步骤 2：为特定 agent 配置不同的模型
openclaw config set agents.customAgents.content-creator.imageModel "https://your-specific-api.com/v1/images/generations"
openclaw config set agents.customAgents.content-creator.imageModelKey "your-specific-api-key"
# 步骤 3：重启 Gateway 以应用配置
openclaw gateway restart
使用 jq 修改配置
# 设置默认图像模型
jq '.agents.defaults.imageModel = "https://your-third-party-api.com/v1/images/generations"' \
~/.openclaw/openclaw.json > /tmp/openclaw.json
mv /tmp/openclaw.json ~/.openclaw/openclaw.json
# 设置图像模型提供商
jq '.agents.defaults.imageModelProvider = "openai"' \
~/.openclaw/openclaw.json > /tmp/openclaw.json
mv /tmp/openclaw.json ~/.openclaw/openclaw.json
# 设置 API 密钥
jq '.agents.defaults.imageModelKey = "your-api-key"' \
~/.openclaw/openclaw.json > /tmp/openclaw.json
mv /tmp/openclaw.json ~/.openclaw/openclaw.json
# 为特定 agent 配置
jq '.agents.customAgents["content-creator"] = {"model": "zai/glm-4.7", "imageModel": "https://your-specific-api.com/v1/images/generations", "imageModelKey": "your-specific-api-key"}' \
~/.openclaw/openclaw.json > /tmp/openclaw.json
mv /tmp/openclaw.json ~/.openclaw/openclaw.json
3. 配置多 Agent 共享工作区
在 ~/.openclaw/openclaw.json 中配置：
{
"agents": {
"customAgents": {
"xianyu-commander": {
"model": "zai/glm-4.7",
"cwd": "/root/.openclaw/workspace/xianyu-automation",
"skills": ["complex-task-subagent", "tavily-search"]
},
"xianyu-data-analyst": {
"model": "zai/glm-4.7",
"cwd": "/root/.openclaw/workspace/xianyu-automation",
"skills": ["tavily-search"]
},
"xianyu-content-creator": {
"model": "zai/glm-4.7",
"cwd": "/root/.openclaw/workspace/xianyu-automation",
"skills": ["complex-task-subagent"]
},
"xianyu-operator": {
"model": "zai/glm-4.7",
"cwd": "/root/.openclaw/workspace/xianyu-automation",
"skills": ["complex-task-subagent", "tavily-search"]
}
}
}
}
热加载配置
# 添加咸鱼总指挥 agent
openclaw config set agents.customAgents.xianyu-commander.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-commander.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-commander.skills '["complex-task-subagent", "tavily-search"]'
# 添加咸鱼数据分析 agent
openclaw config set agents.customAgents.xianyu-data-analyst.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-data-analyst.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-data-analyst.skills '["tavily-search"]'
# 添加咸鱼内容创作 agent
openclaw config set agents.customAgents.xianyu-content-creator.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-content-creator.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-content-creator.skills '["complex-task-subagent"]'
# 添加咸鱼操作员 agent
openclaw config set agents.customAgents.xianyu-operator.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-operator.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-operator.skills '["complex-task-subagent", "tavily-search"]'
# 重启 Gateway
openclaw gateway restart
4. 配置 Skill 使用
在 agent 配置中启用需要的 skill：
{
"agents": {
"customAgents": {
"xianyu-commander": {
"model": "zai/glm-4.7",
"skills": {
"complex-task-subagent": {
"enabled": true,
"executionMode": "confirmation",
"userPreferences": {
"preferredAction": "ask-critical",
"autoFallbackToUnattended": true,
"nightModeEnabled": true
}
},
"tavily-search": {
"enabled": true,
"apiKey": "your-tavily-api-key"
}
}
}
}
}
}
5. 限制 Agent 调用权限
只允许咸鱼总指挥 agent 调用其他咸鱼相关 agent：
{
"agents": {
"accessControl": {
"xianyu-commander": {
"canCall": ["xianyu-data-analyst", "xianyu-content-creator", "xianyu-operator"],
"cannotCall": []
},
"xianyu-data-analyst": {
"canCall": [],
"cannotCall": ["xianyu-commander", "xianyu-content-creator", "xianyu-operator"]
},
"xianyu-content-creator": {
"canCall": [],
"cannotCall": ["xianyu-commander", "xianyu-data-analyst", "xianyu-operator"]
},
"xianyu-operator": {
"canCall": [],
"cannotCall": ["xianyu-commander", "xianyu-data-analyst", "xianyu-content-creator"]
}
}
}
}
热加载权限配置
# 设置咸鱼总指挥的调用权限
openclaw config set agents.accessControl.xianyu-commander.canCall '["xianyu-data-analyst", "xianyu-content-creator", "xianyu-operator"]'
openclaw config set agents.accessControl.xianyu-commander.cannotCall '[]'
# 限制子 agent 的调用权限
openclaw config set agents.accessControl.xianyu-data-analyst.canCall '[]'
openclaw config set agents.accessControl.xianyu-data-analyst.cannotCall '["xianyu-commander", "xianyu-content-creator", "xianyu-operator"]'
openclaw config set agents.accessControl.xianyu-content-creator.canCall '[]'
openclaw config set agents.accessControl.xianyu-content-creator.cannotCall '["xianyu-commander", "xianyu-data-analyst", "xianyu-operator"]'
openclaw config set agents.accessControl.xianyu-operator.canCall '[]'
openclaw config set agents.accessControl.xianyu-operator.cannotCall '["xianyu-commander", "xianyu-data-analyst", "xianyu-content-creator"]'
# 重启 Gateway
openclaw gateway restart
6. 飞书群聊配置
新建飞书群聊并设置机器人
- 通过飞书 API 创建群聊
# 首先需要飞书 API 的 app_access_token
curl -X POST "https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal" \
-H "Content-Type: application/json" \
-d '{
"app_id": "cli_a92f97ca9b799cd4",
"app_secret": "your-app-secret"
}'
- 添加机器人到群聊
# 使用群聊 ID 和机器人 ID
curl -X POST "https://open.feishu.cn/open-apis/contact/v3/group/add_bot" \
-H "Authorization: Bearer YOUR_APP_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"group_id": "YOUR_GROUP_ID",
"bot_id": "ou_xxx"
}'
- 设置机器人为管理员
curl -X POST "https://open.feishu.cn/open-apis/contact/v3/group/set_group_admin" \
-H "Authorization: Bearer YOUR_APP_ACCESS_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"group_id": "YOUR_GROUP_ID",
"user_id_list": ["ou_xxx"],
"user_id_type": "open_id"
}'
- 配置 OpenClaw 默认机器人
编辑 ~/.openclaw/openclaw.json：
{
"feishu": {
"defaultAgentForGroup": {
"oc_2495bf92d31c385fc9818642325fb3d0": "xianyu-commander"
}
}
}
热加载飞书配置
# 设置飞书群聊默认 agent
openclaw config set feishu.defaultAgentForGroup.oc_2495bf92d31c385fc9818642325fb3d0 "xianyu-commander"
# 重启 Gateway
openclaw gateway restart
7. 唤醒 Agent 并获取回应
方法 1：通过飞书群聊
在配置好的飞书群聊中，直接 @ 机器人：
@xianyu-commander 启动今日例行任务
方法 2：通过 OpenClaw CLI
# 直接向 agent 发送消息
openclaw agent send --agent xianyu-commander --message "启动今日例行任务"
方法 3：通过 API
curl -X POST "http://localhost:18789/api/agent/send" \
-H "Content-Type: application/json" \
-d '{
"agent": "xianyu-commander",
"message": "启动今日例行任务"
}'
8. 深度工作模式完整示例
创建任务配置文件
cat > /root/.openclaw/workspace/xianyu-automation/task-progress.json << 'EOF'
{
"taskId": "xianyu-daily-2026-03-14",
"taskName": "咸鱼每日例行任务",
"status": "in_progress",
"currentPhase": 0,
"completedPhases": 0,
"totalPhases": 5,
"lastUpdated": "2026-03-14T18:00:00Z",
"checkpointsDir": "/root/.openclaw/workspace/xianyu-automation/cache/checkpoints",
"cacheDir": "/root/.openclaw/workspace/xianyu-automation/cache/temp",
"executionMode": "confirmation",
"userPreferences": {
"preferredAction": "ask-critical",
"autoFallbackToUnattended": true,
"fallbackTimeout": 7200000,
"nightModeEnabled": true,
"nightModeStart": "22:00",
"nightModeEnd": "08:00"
},
"notification": {
"lastReminder": null,
"reminderCount": 0,
"remindersSent": []
},
"phases": {
"phase1": {
"name": "数据分析",
"status": "pending",
"subagent": "xianyu-data-analyst",
"timeout": 1800000,
"maxRetries": 3,
"retries": 0,
"checkpoint": "phase1-data-analysis.json",
"output": "输出/每日复盘报告.md",
"cacheFile": "phase1-cache.json",
"requiresConfirmation": false,
"critical": false
},
"phase2": {
"name": "内容创作",
"status": "pending",
"subagent": "xianyu-content-creator",
"timeout": 1800000,
"maxRetries": 3,
"retries": 0,
"checkpoint": "phase2-content.json",
"output": {
"文案": "输出/商品文案.md",
"图片": "输出/封面图片.png"
},
"cacheFile": "phase2-cache.json",
"requiresConfirmation": false,
"critical": false
},
"phase3": {
"name": "违禁词审核",
"status": "pending",
"subagent": "xianyu-content-creator",
"timeout": 900000,
"maxRetries": 3,
"retries": 0,
"checkpoint": "phase3-audit.json",
"output": "输出/违禁词审核报告.md",
"cacheFile": "phase3-cache.json",
"requiresConfirmation": false,
"critical": false
},
"phase4": {
"name": "商品上架",
"status": "pending",
"subagent": "xianyu-operator",
"timeout": 1800000,
"maxRetries": 3,
"retries": 0,
"checkpoint": "phase4-listing.json",
"output": "输出/上架结果.json",
"cacheFile": "phase4-cache.json",
"requiresConfirmation": true,
"critical": true,
"confirmationTimeout": 3600000,
"requiresGatewayRestart": false
},
"phase5": {
"name": "同步到 Gitee",
"status": "pending",
"subagent": "xianyu-commander",
"timeout": 300000,
"maxRetries": 3,
"retries": 0,
"checkpoint": "phase5-sync.json",
"output": "输出/同步日志.md",
"cacheFile": "phase5-cache.json",
"requiresConfirmation": false,
"critical": false
}
}
}
EOF
创建 HEARTBEAT-TASK.md
cat > /root/.openclaw/workspace/xianyu-automation/HEARTBEAT-TASK.md << 'EOF'
# 咸鱼任务检查清单
1. 读取 /root/.openclaw/workspace/xianyu-automation/task-progress.json
2. 检查 /root/.openclaw/workspace/xianyu-automation/cache/checkpoints/ 目录
3. 比对检查点和任务进度，更新状态
4. 如果阶段完成但下一阶段未启动，自动推进
5. 如果下一阶段需要确认，检查是否已收到用户回复
6. 如果确认超时，自动降级到无人模式
7. 如果所有阶段完成，同步到 Gitee
8. 记录操作日志
9. 如果没有需要推进的内容，回复 HEARTBEAT_OK
EOF
配置 Heartbeat
# 在 openclaw.json 中配置
openclaw config set agents.defaults.heartbeat.every "10m"
openclaw config set agents.defaults.heartbeat.target "last"
openclaw config set agents.defaults.heartbeat.prompt "Read /root/.openclaw/workspace/xianyu-automation/HEARTBEAT-TASK.md if it exists (workspace context). Follow it strictly. Do not infer or repeat old tasks from prior chats. If nothing needs attention, reply HEARTBEAT_OK."
# 重启 Gateway
openclaw gateway restart
9. 完整的热加载指令序列
以下是一次性配置整个咸鱼自动化项目的完整指令：
# ===== 1. 配置绘图模型 =====
openclaw config set agents.defaults.imageModel "https://your-third-party-api.com/v1/images/generations"
openclaw config set agents.defaults.imageModelProvider "openai"
openclaw config set agents.defaults.imageModelKey "your-api-key"
# ===== 2. 配置咸鱼 agents =====
# 咸鱼总指挥
openclaw config set agents.customAgents.xianyu-commander.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-commander.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-commander.skills '["complex-task-subagent", "tavily-search"]'
# 咸鱼数据分析
openclaw config set agents.customAgents.xianyu-data-analyst.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-data-analyst.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-data-analyst.skills '["tavily-search"]'
# 咸鱼内容创作
openclaw config set agents.customAgents.xianyu-content-creator.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-content-creator.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-content-creator.skills '["complex-task-subagent"]'
# 咸鱼操作员
openclaw config set agents.customAgents.xianyu-operator.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-operator.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-operator.skills '["complex-task-subagent", "tavily-search"]'
# ===== 3. 配置权限控制 =====
openclaw config set agents.accessControl.xianyu-commander.canCall '["xianyu-data-analyst", "xianyu-content-creator", "xianyu-operator"]'
openclaw config set agents.accessControl.xianyu-commander.cannotCall '[]'
openclaw config set agents.accessControl.xianyu-data-analyst.canCall '[]'
openclaw config set agents.accessControl.xianyu-data-analyst.cannotCall '["xianyu-commander", "xianyu-content-creator", "xianyu-operator"]'
openclaw config set agents.accessControl.xianyu-content-creator.canCall '[]'
openclaw config set agents.accessControl.xianyu-content-creator.cannotCall '["xianyu-commander", "xianyu-data-analyst", "xianyu-operator"]'
openclaw config set agents.accessControl.xianyu-operator.canCall '[]'
openclaw config set agents.accessControl.xianyu-operator.cannotCall '["xianyu-commander", "xianyu-data-analyst", "xianyu-content-creator"]'
# ===== 4. 配置飞书群聊默认 agent =====
openclaw config set feishu.defaultAgentForGroup.oc_2495bf92d31c385fc9818642325fb3d0 "xianyu-commander"
# ===== 5. 配置 Heartbeat =====
openclaw config set agents.defaults.heartbeat.every "10m"
openclaw config set agents.defaults.heartbeat.target "last"
openclaw config set agents.defaults.heartbeat.prompt "Read /root/.openclaw/workspace/xianyu-automation/HEARTBEAT-TASK.md if it exists (workspace context). Follow it strictly. Do not infer or repeat old tasks from prior chats. If nothing needs attention, reply HEARTBEAT_OK."
# ===== 6. 重启 Gateway =====
openclaw gateway restart
10. 使用 jq 修改配置的完整指令
# ===== 1. 备份原配置 =====
cp ~/.openclaw/openclaw.json ~/.openclaw/openclaw.json.backup
# ===== 2. 配置绘图模型 =====
jq '.agents.defaults.imageModel = "https://your-third-party-api.com/v1/images/generations"' \
~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
jq '.agents.defaults.imageModelProvider = "openai"' \
~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
jq '.agents.defaults.imageModelKey = "your-api-key"' \
~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
# ===== 3. 配置咸鱼 agents =====
jq '.agents.customAgents["xianyu-commander"] = {
"model": "zai/glm-4.7",
"cwd": "/root/.openclaw/workspace/xianyu-automation",
"skills": ["complex-task-subagent", "tavily-search"]
}' ~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
jq '.agents.customAgents["xianyu-data-analyst"] = {
"model": "zai/glm-4.7",
"cwd": "/root/.openclaw/workspace/xianyu-automation",
"skills": ["tavily-search"]
}' ~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
jq '.agents.customAgents["xianyu-content-creator"] = {
"model": "zai/glm-4.7",
"cwd": "/root/.openclaw/workspace/xianyu-automation",
"skills": ["complex-task-subagent"]
}' ~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
jq '.agents.customAgents["xianyu-operator"] = {
"model": "zai/glm-4.7",
"cwd": "/root/.openclaw/workspace/xianyu-automation",
"skills": ["complex-task-subagent", "tavily-search"]
}' ~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
# ===== 4. 配置权限控制 =====
jq '.agents.accessControl["xianyu-commander"] = {
"canCall": ["xianyu-data-analyst", "xianyu-content-creator", "xianyu-operator"],
"cannotCall": []
}' ~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
jq '.agents.accessControl["xianyu-data-analyst"] = {
"canCall": [],
"cannotCall": ["xianyu-commander", "xianyu-content-creator", "xianyu-operator"]
}' ~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
jq '.agents.accessControl["xianyu-content-creator"] = {
"canCall": [],
"cannotCall": ["xianyu-commander", "xianyu-data-analyst", "xianyu-operator"]
}' ~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
jq '.agents.accessControl["xianyu-operator"] = {
"canCall": [],
"cannotCall": ["xianyu-commander", "xianyu-data-analyst", "xianyu-content-creator"]
}' ~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
# ===== 5. 配置飞书群聊默认 agent =====
jq '.feishu.defaultAgentForGroup["oc_2495bf92d31c385fc9818642325fb3d0"] = "xianyu-commander"' \
~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
# ===== 6. 配置 Heartbeat =====
jq '.agents.defaults.heartbeat = {
"every": "10m",
"target": "last",
"prompt": "Read /root/.openclaw/workspace/xianyu-automation/HEARTBEAT-TASK.md if it exists (workspace context). Follow it strictly. Do not infer or repeat old tasks from prior chats. If nothing needs attention, reply HEARTBEAT_OK."
}' ~/.openclaw/openclaw.json > /tmp/openclaw.json && mv /tmp/openclaw.json ~/.openclaw/openclaw.json
# ===== 7. 验证配置 =====
cat ~/.openclaw/openclaw.json | jq '.agents'
# ===== 8. 重启 Gateway =====
openclaw gateway restart
11. 创建初始化脚本
为了方便后续使用，创建一个初始化脚本：
cat > /root/.openclaw/workspace/xianyu-automation/scripts/init-xianyu-config.sh << 'EOF'
#!/bin/bash
# 咸鱼自动化项目配置初始化脚本
echo "开始配置咸鱼自动化项目..."
# 检查 OpenClaw 是否运行
if ! openclaw gateway status &>/dev/null; then
echo "OpenClaw Gateway 未运行，正在启动..."
openclaw gateway start
fi
# 1. 配置绘图模型
echo "[1/6] 配置绘图模型..."
openclaw config set agents.defaults.imageModel "https://your-third-party-api.com/v1/images/generations"
openclaw config set agents.defaults.imageModelProvider "openai"
openclaw config set agents.defaults.imageModelKey "your-api-key"
# 2. 配置咸鱼 agents
echo "[2/6] 配置咸鱼 agents..."
openclaw config set agents.customAgents.xianyu-commander.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-commander.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-commander.skills '["complex-task-subagent", "tavily-search"]'
openclaw config set agents.customAgents.xianyu-data-analyst.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-data-analyst.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-data-analyst.skills '["tavily-search"]'
openclaw config set agents.customAgents.xianyu-content-creator.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-content-creator.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-content-creator.skills '["complex-task-subagent"]'
openclaw config set agents.customAgents.xianyu-operator.model "zai/glm-4.7"
openclaw config set agents.customAgents.xianyu-operator.cwd "/root/.openclaw/workspace/xianyu-automation"
openclaw config set agents.customAgents.xianyu-operator.skills '["complex-task-subagent", "tavily-search"]'
# 3. 配置权限控制
echo "[3/6] 配置权限控制..."
openclaw config set agents.accessControl.xianyu-commander.canCall '["xianyu-data-analyst", "xianyu-content-creator", "xianyu-operator"]'
openclaw config set agents.accessControl.xianyu-commander.cannotCall '[]'
openclaw config set agents.accessControl.xianyu-data-analyst.canCall '[]'
openclaw config set agents.accessControl.xianyu-data-analyst.cannotCall '["xianyu-commander", "xianyu-content-creator", "xianyu-operator"]'
openclaw config set agents.accessControl.xianyu-content-creator.canCall '[]'
openclaw config set agents.accessControl.xianyu-content-creator.cannotCall '["xianyu-commander", "xianyu-data-analyst", "xianyu-operator"]'
openclaw config set agents.accessControl.xianyu-operator.canCall '[]'
openclaw config set agents.accessControl.xianyu-operator.cannotCall '["xianyu-commander", "xianyu-data-analyst", "xianyu-content-creator"]'
# 4. 配置飞书群聊默认 agent
echo "[4/6] 配置飞书群聊默认 agent..."
openclaw config set feishu.defaultAgentForGroup.oc_2495bf92d31c385fc9818642325fb3d0 "xianyu-commander"
# 5. 配置 Heartbeat
echo "[5/6] 配置 Heartbeat..."
openclaw config set agents.defaults.heartbeat.every "10m"
openclaw config set agents.defaults.heartbeat.target "last"
openclaw config set agents.defaults.heartbeat.prompt "Read /root/.openclaw/workspace/xianyu-automation/HEARTBEAT-TASK.md if it exists (workspace context). Follow it strictly. Do not infer or repeat old tasks from prior chats. If nothing needs attention, reply HEARTBEAT_OK."
# 6. 重启 Gateway
echo "[6/6] 重启 Gateway..."
openclaw gateway restart
echo "✅ 咸鱼自动化项目配置完成！"
echo ""
echo "使用方法："
echo "1. 在飞书群聊中 @xianyu-commander 启动任务"
echo "2. 或使用命令: openclaw agent send --agent xianyu-commander --message '启动任务'"
EOF
chmod +x /root/.openclaw/workspace/xianyu-automation/scripts/init-xianyu-config.sh
技能版本：2.0.0 最后更新：2026-03-15
更新日志
v2.0.0 (2026-03-15)
新增功能：
-
🌙 夜间无人模式
- 提前收集用户偏好和必要信息
- 在用户休息期间自助决策完成任务
- 支持预配置操作权限和降级策略
-
🔑 关键节点确认模式
- 重要决策点自动提醒用户
- 超时自动降级到无人模式
- 可配置提醒间隔和最大提醒次数
-
💾 智能缓存管理
- 子代理工作期间使用临时缓存
- 正常完成自动回收缓存
- 异常中断可从缓存恢复进度
- 支持缓存清理和统计
-
⚡ 深度工作模式
- 完全无人值守的自动化任务执行
- 集成 Heartbeat 实现自动推进
- 支持多 Agent 协作工作区
- 完整的配置指南和热加载指令
新增脚本：
scripts/select-execution-mode.sh- 执行模式选择脚本scripts/cache-manager.sh- 子代理缓存管理脚本scripts/notification-manager.sh- 通知提醒管理脚本
文档改进：
- 添加了完整的深度工作模式配置指南（以 xianyu-automation 为例）
- 详细的热加载指令和 jq 配置示例
- 飞书群聊配置说明
- Agent 权限控制配置
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