skills/claude-skills-open/skills/channels/email-monitor/SKILL.md
AI inbox classification + Telegram notification
npx skillsauth add aaaaqwq/claude-code-skills email-monitorInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Automatic pipeline: Gmail -> AI classification -> CRM activities -> PM tasks -> draft replies -> Telegram
email_monitor.py → Gmail API, extracts full body
↓ JSON (stdout)
email_agent.py → AI classification (claude CLI haiku)
↓ actionable emails JSON (stdin)
email_action_agent.py → CRM + PM + drafts + git commit + Telegram
| What | Path |
|------|------|
| Monitor tool | $GOOGLE_TOOLS_PATH/email_monitor.py |
| Classify agent | $GOOGLE_TOOLS_PATH/email_agent.py |
| Action agent | $GOOGLE_TOOLS_PATH/email_action_agent.py |
| State | $GOOGLE_TOOLS_PATH/data/email_monitor_state.json |
| Summaries | $GOOGLE_TOOLS_PATH/data/email_summaries/ |
| Drafts | $GOOGLE_TOOLS_PATH/data/email_drafts/ |
| Agent log | $GOOGLE_TOOLS_PATH/data/email_agent_log.json |
| LaunchAgent | ~/Library/LaunchAgents/com.yourcompany.email-monitor.plist |
# Everything automatic: check → classify → CRM → tasks → drafts → notify
$GOOGLE_TOOLS_PATH/.venv/bin/python3 $GOOGLE_TOOLS_PATH/email_agent.py
# Dry-run (classification without writing records or notifications)
$GOOGLE_TOOLS_PATH/.venv/bin/python3 $GOOGLE_TOOLS_PATH/email_agent.py --dry-run
# Without AI (rule-based classification)
$GOOGLE_TOOLS_PATH/.venv/bin/python3 $GOOGLE_TOOLS_PATH/email_agent.py --no-ai
# JSON with full body of each email
$GOOGLE_TOOLS_PATH/.venv/bin/python3 $GOOGLE_TOOLS_PATH/email_monitor.py
# Human-readable
$GOOGLE_TOOLS_PATH/.venv/bin/python3 $GOOGLE_TOOLS_PATH/email_monitor.py --pretty
# Reset state (reprocess last 20)
rm $GOOGLE_TOOLS_PATH/data/email_monitor_state.json
# Emails from the last N hours
$GOOGLE_TOOLS_PATH/.venv/bin/python3 $GOOGLE_TOOLS_PATH/email_monitor.py --since 2h
# From file
$GOOGLE_TOOLS_PATH/.venv/bin/python3 $GOOGLE_TOOLS_PATH/email_action_agent.py --file input.json
# Dry-run (shows what it will do, without writing records)
echo '<json>' | $GOOGLE_TOOLS_PATH/.venv/bin/python3 $GOOGLE_TOOLS_PATH/email_action_agent.py --dry-run
# Without drafts
echo '<json>' | $GOOGLE_TOOLS_PATH/.venv/bin/python3 $GOOGLE_TOOLS_PATH/email_action_agent.py --no-draft
# Summary for today
cat $GOOGLE_TOOLS_PATH/data/email_summaries/$(date +%Y-%m-%d).md
# Draft replies
ls $GOOGLE_TOOLS_PATH/data/email_drafts/
cat $GOOGLE_TOOLS_PATH/data/email_drafts/2026-02-09_task-055.txt
# launchd status
launchctl list | grep email-monitor
| Category | Action Agent action | |----------|---------------------| | URGENT | Activity + draft | | REPLY_NEEDED | Activity + draft | | INFO | Activity only | | SPAM | Skipped |
Note (2026-03-02): Task creation is DISABLED. Sales follow-ups are tracked in
leads.csvvianext_action. pm_tasks is for dev/project tasks only. To re-enable task creation, uncomment the block inemail_action_agent.pyaround line 420.
people.csv (email), fallback by domain in companies.csvactivities.csv (type: email, direction: inbound)pm_tasks_master.csvclaude -p --model haiku, saves to data/email_drafts/Unknown contacts are tagged with unknown-contact -- need to be added to CRM.
$CRM_PATH/contacts/people.csv$CRM_PATH/contacts/companies.csv$CRM_PATH/activities.csvemail-send-direct -- single emailemail-send-bulk -- mass email sendingdaily-briefing -- morning overview (reads email summaries)log-activity -- manual activity loggingtelegram-session -- if Telegram notifications are not workingtesting
通用自媒体文章自动发布工具。支持百家号、搜狐号、知乎、微信公众号、小红书、抖音号六个平台的自动化发布流程。使用Playwright自动化实现平台导航和发布,支持通过storageState管理Cookie实现账号切换。
development
# SKILL.md - Model Configuration Status (mcstatus) ## 触发条件 - `/mcstatus` 命令 - 用户询问模型配备、模型配置、model status、模型列表等 ## 功能 实时生成 Agent + Cron 的模型配置报告,展示当前所有 agent 的主模型/fallback链和所有 cron 任务的模型分配。 ## 执行步骤 ### Step 1: 收集 Agent 模型配置 读取各 agent 的 models.json 获取主模型和 fallback 链: ```bash for agent in main ops code quant data research content market finance pm law product sales batch; do config=$(cat ~/.openclaw/agents/$agent/agent/models.json 2>/dev/null) if [ -n "$config" ]; then echo "=== $agent
tools
MCP 服务器智能管理助手。自动检测 MCP 可用性、智能开关、功能问答,提供人性化的 MCP 管理体验。
tools
从GitHub搜索并自动安装配置MCP(Model Context Protocol)服务器工具到Claude配置文件。当用户需要安装MCP工具时触发此技能。工作流程:搜索GitHub上的MCP项目 -> 提取npx配置 -> 添加到~/.claude.json -> 处理API密钥(如有)。