# 1. 确认 tavily-search skill 已安装
ls ~/.openclaw/workspace/skills/tavily-search/SKILL.md

# 2. 设置 Tavily API Key
export TAVILY_API_KEY="your-key-here"

# 3. 注册 Cron 任务
python3 -m json.tool ~/.openclaw/cron/jobs.json  # 确认语法正确

# 4. 验证运行
openclaw doctor

# 确认 github skill 已安装
ls ~/.openclaw/workspace/skills/github/SKILL.md

# 配置 GitHub 认证
gh auth login

# 手动触发一次测试
openclaw message send --channel feishu --message "测试 GitHub 监控 workflow"

# 检查 Cron 任务状态
python3 -m json.tool ~/.openclaw/cron/jobs.json

# 查看资源占用
ps aux | grep openclaw
top -p $(pgrep -d',' openclaw)

# 快速备份
tar -czf ~/openclaw-backup-$(date +%Y%m%d).tar.gz ~/.openclaw/

# 或通过命令行切换
openclaw config set agent.model "gpt-4.1"
openclaw config set agent.provider "openai"
openclaw gateway reload

# 快速网络诊断
curl -s -o /dev/null -w "HTTP 状态: %{http_code}, 耗时: %{time_total}s\n" https://api.openai.com/v1/models

# 第 1 步：确认必要 Skills 已安装
ls ~/.openclaw/workspace/skills/tavily-search/SKILL.md 2>/dev/null \
  && echo "✅ tavily-search 已安装" \
  || echo "❌ 需要安装 tavily-search"

ls ~/.openclaw/workspace/skills/memory/SKILL.md 2>/dev/null \
  && echo "✅ memory 已安装" \
  || echo "❌ 需要安装 memory"

# 第 2 步：创建 workflow 配置文件
mkdir -p ~/.openclaw/workspace/workflows
cat > ~/.openclaw/workspace/workflows/knowledge-assistant.yaml << 'EOF'
name: 个人知识助手
schedule:
  type: cron
  cron: "0 9 * * *"
tasks:
  - name: daily-search
    prompt: |
      搜索今日 AI 领域热门话题，生成摘要并存入记忆
    timeout: 300
EOF

echo "✅ workflow 配置已创建"

# 第 3 步：验证配置
python3 -c "
import yaml
with open('$HOME/.openclaw/workspace/workflows/knowledge-assistant.yaml') as f:
    config = yaml.safe_load(f)
    print(f'Workflow: {config[\"name\"]}')
    print(f'任务数: {len(config[\"tasks\"])}')
"

# 第 1 步：创建检查脚本
cat > /tmp/gh-check.sh << 'EOF'
#!/bin/bash
# gh-check.sh — GitHub 项目快速状态检查
REPO=${1:-"nicepkg/openclaw"}

echo "=== $REPO 状态检查 ==="

# 检查 gh CLI 是否可用
if ! command -v gh &> /dev/null; then
  echo "❌ 需要安装 GitHub CLI: https://cli.github.com/"
  exit 1
fi

echo "📋 Open PRs:"
gh pr list --repo "$REPO" --state open --limit 5 2>/dev/null || echo "  (无法访问)"

echo ""
echo "🐛 Open Issues:"
gh issue list --repo "$REPO" --state open --limit 5 2>/dev/null || echo "  (无法访问)"

echo ""
echo "🔄 Recent CI Runs:"
gh run list --repo "$REPO" --limit 3 2>/dev/null || echo "  (无法访问)"

echo "=== 检查完成 ==="
EOF

chmod +x /tmp/gh-check.sh

# 第 2 步：运行检查（替换为你的仓库）
# bash /tmp/gh-check.sh owner/repo
echo "请运行: bash /tmp/gh-check.sh <owner/repo>"

# 第 1 步：创建质量检查脚本
cat > /tmp/quality-check.sh << 'QEOF'
#!/bin/bash
# quality-check.sh — Markdown 章节质量快速检查
FILE=${1:-"chapter.md"}

if [ ! -f "$FILE" ]; then
  echo "❌ 文件不存在: $FILE"
  exit 1
fi

echo "=== 质量检查: $FILE ==="

# 字数统计
CHARS=$(wc -m < "$FILE")
echo "📊 总字符数: $CHARS"
[ "$CHARS" -ge 1500 ] && echo "  ✅ >= 1500" || echo "  ❌ < 1500"

# 代码块语言检查
UNLABELED=$(grep -c '^```$' "$FILE" || true)
echo "📝 未标注语言的代码块: $UNLABELED"
[ "$UNLABELED" -eq 0 ] && echo "  ✅ 全部已标注" || echo "  ⚠️ 有 $UNLABELED 个需标注"

# 标题层级检查
echo "📑 标题结构:"
grep '^#' "$FILE" | head -15

echo "=== 检查完成 ==="
QEOF

chmod +x /tmp/quality-check.sh

# 第 2 步：对当前教程文件运行检查
# bash /tmp/quality-check.sh "03-Skills 插件体系与批量开发.md"
echo "请运行: bash /tmp/quality-check.sh <markdown-file>"

# 确认 ClawHub 源配置正确
openclaw config get hub.registry

# 刷新 Skill 索引缓存
clawhub update

# 重新安装指定 Skill
clawhub install tavily-search --force

# 如果仍然失败，检查网络连通性
curl -I https://hub.openclaw.ai

# 验证 jobs.json 格式是否正确
python3 -m json.tool ~/.openclaw/cron/jobs.json

# 重新加载 Cron 配置
openclaw cron reload

# 查看 Cron 任务状态
openclaw cron list

# 手动触发一次以验证
openclaw cron trigger <job-id>

# 检查飞书凭证是否有效
openclaw credential list | grep feishu

# 测试飞书 Webhook 连通性
curl -X POST <your-webhook-url>   -H "Content-Type: application/json"   -d '{"msg_type":"text","content":{"text":"OpenClaw 连通性测试"}}'

# 查看 delivery-queue 是否有积压
ls -la ~/.openclaw/delivery-queue/ | wc -l