Skill flagged — suspicious patterns detected

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免费版

v1.4.0

专为中文自媒体博主设计,连接 Notion,实现选题生成、发布跟踪、数据复盘及内容日历管理的一体化内容中枢。

0· 141·0 current·0 all-time
byMrReiyWsL@a799549967-lang

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for a799549967-lang/notion-content-hub-cn.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "免费版" (a799549967-lang/notion-content-hub-cn) from ClawHub.
Skill page: https://clawhub.ai/a799549967-lang/notion-content-hub-cn
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install notion-content-hub-cn

ClawHub CLI

Package manager switcher

npx clawhub@latest install notion-content-hub-cn
Security Scan
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medium confidence
Purpose & Capability
The described purpose (connect Feishu/多维表格 to pull hot topics, write/read records, and run analysis) aligns with the runtime instructions which require a Feishu App ID/Secret and the table URL. However the registry metadata claims no required environment variables or primary credential while SKILL.md explicitly requires FEISHU_APP_ID, FEISHU_APP_SECRET and FEISHU_BITABLE_URL — a clear metadata/instruction mismatch.
Instruction Scope
Instructions stay within the stated domain: they fetch trending data from public endpoints, obtain a Feishu tenant access token, read and write the user's Feishu bitable, and analyze that data. The agent is instructed to read the user's recent entries and the whole table for recap — expected for the stated features. No instructions ask for unrelated system files or other unrelated credentials.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, which minimizes surface area. Nothing is downloaded or written to disk by an installer in the skill bundle itself.
!
Credentials
The skill legitimately needs a Feishu App ID and App Secret to call Feishu APIs. But the package metadata lists no required env vars while SKILL.md instructs the agent to check for FEISHU_APP_ID, FEISHU_APP_SECRET, and FEISHU_BITABLE_URL at session start — inconsistent and misleading. Also the SKILL.md refers to third‑party trending APIs (tenapi.cn, v2.xxapi.cn) which are unauthenticated proxies/scrapers; depending on these unverified endpoints increases operational and privacy risk (they could be unreliable or change behavior). The skill also suggests guiding the user to paste their App Secret into OpenClaw chat — users should be aware this is a sensitive secret and should only provide it to trusted agent contexts.
Persistence & Privilege
The skill is not marked always:true and does not request persistent system privileges. Autonomous invocation is allowed by default (normal for skills) and nothing in the materials indicates it modifies other skills or system-wide settings.
Scan Findings in Context
[no_findings] expected: Static scanner found no regex matches because this is instruction-only (no code files). The runtime behavior is entirely described in SKILL.md, so manual review of the prose is the primary signal.
[third_party_endpoints_listed] unexpected: SKILL.md lists multiple unauthenticated third‑party endpoints (tenapi.cn, v2.xxapi.cn) used to fetch hot lists. Using such proxies is plausible for this purpose but introduces trust and availability risks; the metadata does not document or justify these choices.
What to consider before installing
This skill appears to do what it says (connect Feishu bitable, fetch hot topics, write/read records). However: 1) SKILL.md requires FEISHU_APP_ID and FEISHU_APP_SECRET even though the registry metadata claims no required env vars — treat that as a red flag and verify before providing secrets. 2) The Feishu App Secret is sensitive: create a dedicated, minimal‑permission Feishu app (only bitable:app), use a test account if possible, and rotate the secret after testing. 3) The hotlist endpoints are third‑party proxies (tenapi.cn, v2.xxapi.cn); consider the reliability and privacy implications — these endpoints could change or capture query data. If you proceed, test with limited data and a throwaway Feishu app first, confirm that the skill only performs the expected API calls, and avoid pasting production credentials until you trust the source. If the publisher/source cannot be verified (no homepage, unknown owner), prefer caution or request a version with transparent code or an official upstream source.

Like a lobster shell, security has layers — review code before you run it.

latestvk976mrpe6aja57fvx409wyhzp183t3rg
141downloads
0stars
7versions
Updated 1mo ago
v1.4.0
MIT-0

飞书自媒体内容管理中枢

把飞书多维表格变成你的内容大脑:接入实时热榜生成选题、追踪发布数据、AI 月度复盘分析 —— 专为中文自媒体博主设计,无需翻墙,全程中文。


这套工具是什么

飞书多维表格 = 你的内容数据库(可视化界面,手机电脑都能看,免费) 本 skill = AI 助理(生成选题、存数据、做分析) 一稿多发助手(配合使用)= 一个选题自动生成多平台内容版本

三者组合成完整流水线,你只需要做两件事:决策选题 + 复制内容去各平台发布。


完整工作流

周一:AI 拉热榜 → 生成5个选题 → 自动存飞书(10分钟)
         ↓
    你在飞书看板里选哪个做
         ↓
内容生产:告诉AI生成哪个 → 一稿多发生成各平台版本(5分钟/篇)
         ↓
    你复制粘贴到各平台发布
         ↓
发布后:说一句话录数据 → AI自动更新飞书(1分钟)
         ↓
月底:说"帮我做复盘" → AI读飞书数据 → 出爆款规律报告(5分钟)

📖 配置说明(一次性,约20分钟)

第一步:创建飞书多维表格

  1. 打开飞书(feishu.cn 或手机 App)
  2. 左侧点「+」新建 → 选「多维表格
  3. 名称填:自媒体内容管理
  4. 创建完成后复制浏览器地址栏链接备用

表格字段不需要手动建,第一次使用时 AI 自动创建所有字段

第二步:创建飞书 API 应用

  1. 浏览器打开 open.feishu.cn,用飞书账号登录
  2. 点「开发者后台」→「创建企业自建应用
  3. 应用名称填 内容助手,点确定
  4. 进入应用 → 左侧「凭证与基础信息
  5. 复制 App IDcli_ 开头)和 App Secret(点查看后复制)

⚠️ App Secret 只显示一次,立刻复制保存

第三步:开通权限并发布

  1. 左侧「权限管理」→ 搜索 bitable → 开通 bitable:app
  2. 左侧「版本管理与发布」→「创建版本」→ 填 1.0.0 → 提交
  3. 点「申请线上发布」→ 选「无需审核直接发布」

第四步:把应用连接到你的表格

  1. 打开「自媒体内容管理」多维表格
  2. 右上角「···」→「添加应用」→ 找到「内容助手」→ 添加

第五步:配置到 OpenClaw

我的飞书 App ID 是 cli_xxx,App Secret 是 xxx,多维表格链接是 https://feishu.cn/base/xxx

AI 自动验证并创建所有字段,提示「✅ 已连接」即配置完成。


飞书4种视图(可视化管理)

配置完后,在飞书里点「+ 新增视图」可切换:

视图用途
📋 表格视图看所有文章状态和数据,直接在格子里填数字
🗂 看板视图按「选题中/写作中/已发布」分组,拖拽改状态
📅 日历视图按发布日期展示,看内容节奏
📊 图表视图阅读/点赞趋势图、平台对比、TOP文章排行

开始用

今天知乎/微博有什么热点,帮我选 3 个适合我账号的选题
把「用 AI 做副业」标记为已发布,阅读 8000,点赞 320,涨粉 45
帮我做本月内容复盘
我有哪些草稿超过一周没动了

🔥 核心功能一:热榜选题生成

这是这个 skill 最核心的功能。

选题不靠拍脑袋,直接拉取实时热榜数据,结合你的账号方向,生成有流量基础的选题。

支持的热榜数据源

热榜内容类型适合平台
知乎热榜深度问答、社会话题知乎、公众号
微博热搜实时事件、娱乐热点微博、小红书
百度热搜搜索趋势、大众话题公众号、头条
今日头条热榜资讯类热点头条号、公众号
抖音热点短视频话题抖音、小红书
B站热门年轻圈层话题B站、小红书

使用示例

今天有什么热点适合做成公众号文章?我的方向是副业和 AI 工具
抓一下微博和知乎的热榜,找 3 个适合我的选题,写到飞书
帮我出本周内容计划,参考热榜数据,5 个选题

生成结果示例

假设你说:「帮我基于今天热榜,出 3 个公众号选题,方向是 AI 工具」

skill 会:

  1. 拉取知乎热榜 + 百度热搜实时数据
  2. 筛选与"AI工具"相关或可关联的热点
  3. 生成 3 个选题,每个包含:
📌 选题 1
标题:《普通人怎么用 AI 工具月入过万?我试了 3 个月》
热点来源:知乎热榜「AI 副业」相关话题(热度 82万)
为什么会点:结合热点 + 利益驱动标题,点击率高
目标读者:想做副业的上班族
核心角度:亲身经历 + 具体方法,不是泛泛而谈
建议发布:周三晚 8-10 点
  1. 全部自动写入飞书多维表格,状态标记「选题中」

📊 核心功能二:发布数据追踪

发完内容,一句话更新,告别手动填表。

昨天发的「DeepSeek 替代 ChatGPT」,公众号阅读 12000,点赞 450,涨粉 80

skill 自动:

  • 在飞书里找到那篇文章(模糊匹配标题)
  • 更新全部数据字段
  • 顺带告诉你这篇在你历史里排第几
✅ 已更新「DeepSeek替代ChatGPT」
📊 阅读 12,000 — 近30天排名第 2
💡 「工具对比」类选题在你账号表现持续很好,建议加大这类比例

📈 核心功能三:月度复盘分析

帮我做 3 月内容复盘

自动读取飞书全部数据,生成结构化报告:

## 3 月内容复盘报告

📊 发布 14 篇 | 平均阅读 6,800(↑23%)| 总涨粉 312

### 平台对比
公众号  均值 9,200  ✅ 最强
小红书  均值点赞 180  ✅ 互动最好
知乎    均值 2,100  ⚠️ 产出比低

### 爆款规律(阅读 >10,000 的共同特征)
- 标题带数字:占爆款 80%
- 话题:AI工具 > 副业方法 > 效率提升
- 最佳发布时间:周三晚 8-10 点

### 下月建议
1. 公众号主推「AI工具测评」,标题必须带数字
2. 小红书加大频率,互动率高但内容量不够
3. 知乎减少投入,性价比低
4. 参考热榜追热点,本月追热点的 3 篇均破万

⏰ 核心功能四:拖稿提醒

我有哪些草稿超过一周没动了
⚠️ 3 篇草稿超过 7 天未更新

1. 「如何用 AI 写周报」— 搁置 12 天
2. 「2026年最值得学的技能」— 搁置 9 天
3. 「副业第一桶金怎么来的」— 搁置 8 天

帮你继续写某篇,还是标记归档?

🗂 飞书表格字段(自动创建)

字段类型说明
标题文本文章/视频标题
状态单选选题中 / 写作中 / 已发布 / 已归档
平台多选公众号 / 知乎 / 小红书 / 抖音 / B站
发布日期日期实际发布时间
阅读量数字
点赞数字
涨粉数字
热点来源文本知乎热榜 / 微博热搜 / 原创 等
选题来源单选AI生成 / 热榜追踪 / 读者建议 / 自选
关键词文本SEO 关键词
备注文本写作思路、参考链接

❓ 常见问题

  • 飞书要付费吗? 免费版完全够用,API 也免费
  • 热榜数据实时的吗? 是,每次调用都拉取最新数据
  • 没有历史数据可以用吗? 可以,新账号直接基于热榜+你说的方向生成选题
  • 手机上能看数据吗? 可以,飞书 App 实时同步
  • 需要额外配置吗? OpenClaw 配置好 AI 即可(支持阿里云百炼、DeepSeek 等),再加飞书 App ID 和 App Secret
  • 有问题找谁? ClawHub 页面留言或联系 @ShuaigeSkillBot
  • 需要帮你配置好直接用? Telegram 私信 @ShuaigeSkillBot,飞书配置服务 ¥99,配好即用

Trigger

When the user mentions any of: "飞书", "多维表格", "选题", "热榜", "热点", "内容计划", "内容日历", "内容库", "发布追踪", "内容复盘", "自媒体管理", "选题库", "内容管理", "草稿提醒", "知乎热榜", "微博热搜"

Or phrases like: "帮我生成选题", "今天有什么热点", "更新一下数据", "帮我做复盘", "哪些草稿没动"

Configuration

Check for these at session start:

  • FEISHU_APP_ID — starts with cli_
  • FEISHU_APP_SECRET
  • FEISHU_BITABLE_URL — the multidimensional table URL

If missing, guide user through setup with the step-by-step instructions above.

Get access token:

POST https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal
{"app_id": "{FEISHU_APP_ID}", "app_secret": "{FEISHU_APP_SECRET}"}

Token expires every 2 hours — re-fetch automatically when needed.

Hot Data Sources

Fetch trending data from these free, no-auth endpoints (all accessible from mainland China):

知乎热榜:    GET https://tenapi.cn/v2/zhihuhot
微博热搜:    GET https://v2.xxapi.cn/api/weibohot
百度热搜:    GET https://tenapi.cn/v2/baiduhot
今日头条:    GET https://tenapi.cn/v2/toutiaohotnew
抖音热点:    GET https://tenapi.cn/v2/douyinhot

Response format (all return similar structure):

{"code": 200, "data": [{"title": "热点标题", "url": "...", "hot": "热度数值"}]}

Fallback strategy: if one endpoint fails, try the next. If all fail, proceed with user's historical data only and note that hot data is temporarily unavailable.

Workflow

Step 1: Initialize

  1. Get Feishu access token
  2. Parse bitable URL → extract app_token and table_id
  3. Check table schema; if missing fields, offer to create them
  4. Confirm: "✅ 已连接飞书多维表格,共 XX 条记录"

Step 2: Route Request

ACTION: generate_topics (核心功能)

Triggered by: 选题, 热点, 内容计划, 帮我出选题

Process:

  1. Fetch hot data from relevant platforms based on user's target platform:

    • 公众号/知乎 → fetch 知乎热榜 + 百度热搜
    • 小红书/抖音 → fetch 微博热搜 + 抖音热点
    • 头条 → fetch 今日头条 + 百度热搜
    • If unspecified → fetch all 5 sources
  2. Read user's last 20 published entries from Feishu (if any) to understand:

    • Content niche and style
    • Which topic types performed best (highest reads/likes)
    • Which platforms they publish to
  3. Match hot topics to user's niche:

    • Filter irrelevant hot topics
    • Find angles that connect hot topics to user's vertical
    • Prioritize topics with high heat scores AND relevance
  4. Generate N topics (default 5), each containing:

    • 标题 (title — specific, clickable, ideally with numbers)
    • 热点来源 (which hot list + heat score)
    • 为什么适合 (why it fits this account)
    • 目标读者
    • 核心写作角度
    • 建议发布平台
    • 建议发布时间 (based on user's historical best times, or default Wed/Fri 8-10pm)
  5. Write all to Feishu with status="选题中", 选题来源="AI生成+热榜追踪"

  6. Output summary to user, then confirm Feishu write

ACTION: update_publish_status

Triggered by: 已发布, 标记发布, 更新数据, 阅读量

Process:

  1. Search Feishu records for matching title (fuzzy match on 标题 field)
  2. If multiple matches → list them, ask user to choose
  3. Update all provided fields: 状态, 发布日期, 平台, 阅读量, 点赞, 涨粉
  4. Compare to user's average → generate brief performance note
  5. Confirm update

ACTION: monthly_review

Triggered by: 复盘, 分析, 哪类内容, 表现, 爆款

Process:

  1. Query all records with 状态=已发布 in specified date range
  2. Calculate:
    • Total published, average reads/likes/followers
    • Per-platform performance table
    • Top 5 articles by reads and by likes
    • Common patterns in top performers (title style, topic category, publish time)
    • Month-over-month comparison if prior month data exists
  3. Output structured Chinese report (format shown in Core Feature 3 above)
  4. End with 3-5 specific, actionable recommendations

ACTION: overdue_drafts

Triggered by: 草稿, 没动, 超期, 拖稿

Process:

  1. Query records with 状态 IN (选题中, 写作中)
  2. Filter where creation/update time > 7 days ago
  3. List with days overdue, sorted by most overdue first
  4. Ask: "帮你继续写某篇,还是标记归档?"

ACTION: show_calendar

Triggered by: 本周计划, 内容日历, 几篇, 日历

Process:

  1. Query records with 发布日期 in requested range
  2. Display as day-by-day plan
  3. Show gap days with "⬜ 待安排"

Step 3: Feishu Bitable API

Headers for all requests:

Authorization: Bearer {tenant_access_token}
Content-Type: application/json

List records:

GET https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records?page_size=100

Search records:

POST https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records/search
{
  "filter": {
    "conjunction": "and",
    "conditions": [
      {"field_name": "状态", "operator": "is", "value": ["已发布"]}
    ]
  },
  "sort": [{"field_name": "发布日期", "order": "DESC"}]
}

Create record:

POST https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records
{
  "fields": {
    "标题": "文章标题",
    "状态": "选题中",
    "平台": ["小红书"],
    "热点来源": "知乎热榜 · 热度82万",
    "选题来源": "AI生成+热榜追踪"
  }
}

Update record:

PATCH https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/records/{record_id}
{
  "fields": {
    "状态": "已发布",
    "阅读量": 8000,
    "点赞": 320,
    "涨粉": 45,
    "发布日期": "2026-03-29"
  }
}

Create table fields (first-time setup):

POST https://open.feishu.cn/open-apis/bitable/v1/apps/{app_token}/tables/{table_id}/fields
{"field_name": "阅读量", "type": 2}

Field types: 1=Text, 2=Number, 3=SingleSelect, 4=MultiSelect, 5=Date

Step 4: Error Handling

ErrorResponse
401 Unauthorized"App ID 或 App Secret 有问题,重新粘贴一下"
403 Forbidden"应用没有权限访问这个表格,检查一下是否已添加应用"
404 Not Found"找不到这个表格,链接是否正确?"
Hot API timeout跳过该热榜,用其他数据源,最后告知用户"XX热榜暂时不可用"
Title not found列出最近 10 条记录,让用户选择
Token expired自动重新获取 token,无需用户操作

Rules

  1. 优先拉取热榜数据再生成选题,有数据支撑的选题才有价值
  2. 新用户没有历史数据时,直接基于热榜+用户说的方向生成,不报错
  3. 模糊匹配标题时,若有多个结果,必须让用户确认,不要猜
  4. 删除操作必须二次确认
  5. 全程中文输出,除非用户用英文提问
  6. 每次飞书写入后都要明确确认:"✅ 已存入飞书:[标题]"
  7. API credentials 只在会话内存中,不写入任何文件
  8. 热榜 API 失败时优雅降级,不影响其他功能

📢 每日市场数据播报,关注 Telegram 频道:https://t.me/shuaigeclaw

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